Week 12 [Apr 8]
Demo during tutorial
- The remaining members (who did not demo the previous week) do a timed demo in the tutorial this week
- Ensure that you have at least 20 meaningful data items
- E.g.,
aaa
,test 1
, etc., are not considered meaningful
- E.g.,
- Be aware of the requirements of v1.4 submission
Mock MCQ
- We will have a mock MCQ test in the last 30 min of the lecture, just for you to gain some practise.
- This is not graded.
[W12.1] Reuse: Frameworks, Libraries, Platforms
Reuse
Can explain software reuse
Reuse is a major theme in software engineering practices. By reusing tried-and-tested components, the robustness of a new software system can be enhanced while reducing the manpower and time requirement. Reusable components come in many forms; it can be reusing a piece of code, a subsystem, or a whole software.
Can explain the costs and benefits of reuse
While you may be tempted to use many libraries/frameworks/platform that seem to crop up on a regular basis and promise to bring great benefits, note that there are costs associated with reuse. Here are some:
- The reused code may be an overkill (think using a sledgehammer to crack a nut) increasing the size of, or/and degrading the performance of, your software.
- The reused software may not be mature/stable enough to be used in an important product. That means the software can change drastically and rapidly, possibly in ways that break your software.
- Non-mature software has the risk of dying off as fast as they emerged, leaving you with a dependency that is no longer maintained.
- The license of the reused software (or its dependencies) restrict how you can use/develop your software.
- The reused software might have bugs, missing features, or security vulnerabilities that are important to your product but not so important to the maintainers of that software, which means those flaws will not get fixed as fast as you need them to.
- Malicious code can sneak into your product via compromised dependencies.
One of your teammates is proposing to use a recently-released “cool” UI framework for your class project. List the pros and cons of this idea.
Pros
- The potential to create a much better product by reusing the framework.
- Learning a new framework is good for the future job prospects.
Cons
- Learning curve may be steep.
- May not be stable (it was recently released).
- May not allow us to do exactly what we want. While frameworks allow customization, such customization can be limited.
- Performance penalties.
- Might interfere with learning objectives of the module.
Note that having more cons does not mean we should not use this framework. Further investigation is required before we can make a final decision.
Libraries
Can explain libraries
A library is a collection of modular code that is general and can be used by other programs.
Java classes you get with the JDK (such as String
, ArrayList
, HashMap
, etc.) are library classes that are provided in the default Java distribution.
Natty is a Java library that can be used for parsing strings that represent dates e.g. The 31st of April in the year 2008
built-in modules you get with Python (such as csv
, random
, sys
, etc.) are libraries that are provided in the default Python distribution. Classes such as list
, str
, dict
are built-in library classes that you get with Python.
Colorama is a Python library that can be used for colorizing text in a CLI.
Can make use of a library
These are the typical steps required to use a library.
- Read the documentation to confirm that its functionality fits your needs
- Check the license to confirm that it allows reuse in the way you plan to reuse it. For example, some libraries might allow non-commercial use only.
- Download the library and make it accessible to your project. Alternatively, you can configure your
dependency management tool to do it for you. - Call the library API from your code where you need to use the library functionality.
Frameworks
Can explain frameworks
The overall structure and execution flow of a specific category of software systems can be very similar. The similarity is an opportunity to reuse at a high scale.
Running example:
IDEs for different programming languages are similar in how they support editing code, organizing project files, debugging, etc.
A software framework is a reusable implementation of a software (or part thereof) providing generic functionality that can be selectively customized to produce a specific application.
Running example:
Eclipse is an IDE framework that can be used to create IDEs for different programming languages.
Some frameworks provide a complete implementation of a default behavior which makes them immediately usable.
Running example:
Eclipse is a fully functional Java IDE out-of-the-box.
A framework facilitates the adaptation and customization of some desired functionality.
Running example:
Eclipse plugin system can be used to create an IDE for different programming languages while reusing most of the existing IDE features of Eclipse. E.g. https://marketplace.eclipse.org/content/pydev-python-ide-eclipse
Some frameworks cover only a specific components or an aspect.
JavaFx a framework for creating Java GUIs. TkInter is a GUI framework for Python.
More examples of frameworks
- Frameworks for Web-based applications: Drupal(PHP), Django(Python), Ruby on Rails (Ruby), Spring (Java)
- Frameworks for testing: JUnit (Java), unittest (Python), Jest (Java Script)
Can differentiate between frameworks and libraries
Although both frameworks and libraries are reuse mechanisms, there are notable differences:
-
Libraries are meant to be used ‘as is’ while frameworks are meant to be customized/extended. e.g., writing plugins for Eclipse so that it can be used as an IDE for different languages (C++, PHP, etc.), adding modules and themes to Drupal, and adding test cases to JUnit.
-
Your code calls the library code while the framework code calls your code. Frameworks use a technique called inversion of control, aka the “Hollywood principle” (i.e. don’t call us, we’ll call you!). That is, you write code that will be called by the framework, e.g. writing test methods that will be called by the JUnit framework. In the case of libraries, your code calls libraries.
Choose correct statements about software frameworks.
- a. They follow the hollywood principle, otherwise known as ‘inversion of control’
- b. They come with full or partial implementation.
- c. They are more concrete than patterns or principles.
- d. They are often configurable.
- e. They are reuse mechanisms.
- f. They are similar to reusable libraries but bigger.
(a)(b)(c)(d)(e)(f)
Explanation: While both libraries and frameworks are reuse mechanisms, and both more concrete than principles and patterns, libraries differ from frameworks in some key ways. One of them is the ‘inversion of control’ used by frameworks but not libraries. Furthermore, frameworks do not have to be bigger than libraries all the time.
Which one of these are frameworks ?
(a)(b)(c)(d)
Explanation: These are frameworks.
Platforms
Can explain platforms
A platform provides a runtime environment for applications. A platform is often bundled with various libraries, tools, frameworks, and technologies in addition to a runtime environment but the defining characteristic of a software platform is the presence of a runtime environment.
Technically, an operating system can be called a platform. For example, Windows PC is a platform for desktop applications while iOS is a platform for mobile apps.
Two well-known examples of platforms are JavaEE and .NET, both of which sit above Operating systems layer, and are used to develop
- JavaEE (Java Enterprise Edition) is both a framework and a platform for writing enterprise applications. The runtime used by the JavaEE applications is the JVM (Java Virtual Machine) that can run on different Operating Systems.
- .NET is a similar platform and a framework. Its runtime is called CLR (Common Language Runtime) and usually used on Windows machines.
Enterprise Application: ‘enterprise applications’ means software applications used at organizations level and therefore has to meet much higher demands (such as in scalability, security, performance, and robustness) than software meant for individual use.
[W12.2] Cloud Computing
Can explain cloud computing
Cloud computing is the delivery of computing as a service over the network, rather than a product running on a local machine. This means the actual hardware and software is located at a remote location, typically, at a large server farm, while users access them over the network. Maintenance of the hardware and software is managed by the cloud provider while users typically pay for only the amount of services they use. This model is similar to the consumption of electricity; the power company manages the power plant, while the consumers pay them only for the electricity used. The cloud computing model optimizes hardware and software utilization and reduces the cost to consumers. Furthermore, users can scale up/down their utilization at will without having to upgrade their hardware and software. The traditional non-cloud model of computing is similar to everyone buying their own generators to create electricity for their own use.
Can distinguish between IaaS, PaaS, and SaaS
source:https://commons.wikimedia.org
Cloud computing can deliver computing services at three levels:
-
Infrastructure as a service (IaaS) delivers computer infrastructure as a service. For example, a user can deploy virtual servers on the cloud instead of buying physical hardware and installing server software on them. Another example would be a customer using storage space on the cloud for off-site storage of data. Rackspace is an example of an IaaS cloud provider. Amazon Elastic Compute Cloud (Amazon EC2) is another one.
-
Platform as a service (PaaS) provides a platform on which developers can build applications. Developers do not have to worry about infrastructure issues such as deploying servers or load balancing as is required when using IaaS. Those aspects are automatically taken care of by the platform. The price to pay is reduced flexibility; applications written on PaaS are limited to facilities provided by the platform. A PaaS example is the Google App Engine where developers can build applications using Java, Python, PHP, or Go whereas Amazon EC2 allows users to deploy application written in any language on their virtual servers.
-
Software as a service (SaaS) allows applications to be accessed over the network instead of installing them on a local machine. For example, Google Docs is an SaaS word processing software, while Microsoft Word is a traditional word processing software.
Google Calendar belongs to which category of cloud computing services?
- a. IaaS
- b. PaaS
- c. SaaS
(c)
Explanation: It is a software as a service. Instead of installing a calendar software on your desktop, we can use the Google Calendar software that lives ‘on the cloud’.
[W12.3] Other UML Models
Can explain deployment diagrams
A deployment diagram shows a system's physical layout, revealing which pieces of software run on which pieces of hardware.
An example deployment diagram:
Can explain component diagrams
A component diagram is used to show how a system is divided into components and how they are connected to each other through interfaces.
An example component diagram:
Can explain package diagrams
A package diagram shows packages and their dependencies. A package is a grouping construct for grouping UML elements (classes, use cases, etc.).
Here is an example package diagram:
Can explain composite structure diagrams
A composite structure diagram hierarchically decomposes a class into its internal structure.
Here is an example composite structure diagram:
Can explain timing diagrams
A timing diagram focus on timing constraints.
Here is an example timing diagram:
Adapted from: UML Distilled by Martin Fowler
Can explain interaction overview diagrams
An Interaction overview diagrams is a combination of activity diagrams and sequence diagrams.
An example:
Can explain communication diagrams
A Communication diagrams are like sequence diagrams but emphasize the data links between the various participants in the interaction rather than the sequence of interactions.
An example:
Adapted from: UML Distilled by Martin Fowler
Can explain state machine diagrams
A State Machine Diagram models state-dependent behavior.
Consider how a CD player responds when the “eject CD” button is pushed:
- If the CD tray is already open, it does nothing.
- If the CD tray is already in the process of opening (opened half-way), it continues to open the CD tray.
- If the CD tray is closed and the CD is being played, it stops playing and opens the CD tray.
- If the CD tray is closed and CD is not being played, it simply opens the CD tray.
- If the CD tray is already in the process of closing (closed half-way), it waits until the CD tray is fully closed and opens it immediately afterwards.
What this means is that the CD player’s response to pushing the “eject CD” button depends on what it was doing at the time of the event. More generally, the CD player’s response to the event received depends on its internal state. Such a behavior is called a state-dependent behavior.
Often, state-dependent behavior displayed by an object in a system is simple enough that it needs no extra attention; such a behavior can be as simple as a conditional behavior like if x>y, then x=x-y
.
Occasionally, objects may exhibit state-dependent behavior that is complex enough such that it needs to be captured into a separate model. Such state-dependent behavior can be modelled using UML state machine diagrams (SMD for short, sometimes also called ‘state charts’, ‘state diagrams’ or ‘state machines’).
An SMD views the life-cycle of an object as consisting of a finite number of states where each state displays a unique behavior pattern. An SMD captures information such as the states an object can be in, during its lifetime, and how the object responds to various events while in each state and how the object transits from one state to another. In contrast to sequence diagrams that capture object behavior one scenario at a time, SMDs capture the object’s behavior over its full life cycle.
An SMD for the Minesweeper game.
Project Milestone: mid-v1.4
Tweak as per peer-testing results, draft Project Portfolio Page, practice product demo.
Project Management:
- Freeze features around this time. Ensure the current product have all the features you intend to release at v1.4. Adding major changes after this point is risky. The remaining time is better spent fixing problems discovered late or on fine-tuning the product.
- Ensure the code attributed to you by RepoSense is correct, as reported in the Project Activity Dashboard
Relevant: [
In previous semesters we asked students to annotate all their code using special @@author
tags so that we can extract each student's code for grading. This semester, we are trying out a tool called RepoSense that is expected to reduce the need for such tagging, and also make it easier for you to see (and learn from) code written by others.
1. View the current status of code authorship data:
- The report generated by the tool is available at Project Code Dashboard. The feature that is most relevant to you is the Code Panel (shown on the right side of the screenshot above). It shows the code attributed to a given author. You are welcome to play around with the other features (they are still under development and will not be used for grading this semester).
- Click on your name to load the code attributed to you (based on Git blame/log data) onto the code panel on the right.
- If the code shown roughly matches the code you wrote, all is fine and there is nothing for you to do.
2. If the code does not match:
-
Here are the possible reasons for the code shown not to match the code you wrote:
- the git username in some of your commits does not match your GitHub username (perhaps you missed our instructions to set your Git username to match GitHub username earlier in the project, or GitHub did not honor your Git username for some reason)
- the actual authorship does not match the authorship determined by git blame/log e.g., another student touched your code after you wrote it, and Git log attributed the code to that student instead
-
In those cases,
- Install RepoSense (see the Getting Started section of the RepoSense User Guide)
- Use the two methods described in the RepoSense User Guide section Configuring a Repo to Provide Additional Data to RepoSense to provide additional data to the authorship analysis to make it more accurate.
- If you add a
config.json
file to your repo (as specified by one of the two methods),- Please use the template json file given in the module website so that your display name matches the name we expect it to be.
- If your commits have multiple author names, specify all of them e.g.,
"authorNames": ["theMyth", "theLegend", "theGary"]
- Update the line
config.json
in the.gitignore
file of your repo as/config.json
so that it ignores theconfig.json
produced by the app but not the_reposense/config.json
.
- If you add
@@author
annotations, please follow the guidelines below:
Adding @@author
tags indicate authorship
-
Mark your code with a
//@@author {yourGithubUsername}
. Note the double@
.
The//@@author
tag should indicates the beginning of the code you wrote. The code up to the next//@@author
tag or the end of the file (whichever comes first) will be considered as was written by that author. Here is a sample code file://@@author johndoe method 1 ... method 2 ... //@@author sarahkhoo method 3 ... //@@author johndoe method 4 ...
-
If you don't know who wrote the code segment below yours, you may put an empty
//@@author
(i.e. no GitHub username) to indicate the end of the code segment you wrote. The author of code below yours can add the GitHub username to the empty tag later. Here is a sample code with an emptyauthor
tag:method 0 ... //@@author johndoe method 1 ... method 2 ... //@@author method 3 ... method 4 ...
-
The author tag syntax varies based on file type e.g. for java, css, fxml. Use the corresponding comment syntax for non-Java files.
Here is an example code from an xml/fxml file.<!-- @@author sereneWong --> <textbox> <label>...</label> <input>...</input> </textbox> ...
-
Do not put the
//@@author
inside java header comments.
👎/** * Returns true if ... * @@author johndoe */
👍
//@@author johndoe /** * Returns true if ... */
What to and what not to annotate
-
Annotate both functional and test code There is no need to annotate documentation files.
-
Annotate only significant size code blocks that can be reviewed on its own e.g., a class, a sequence of methods, a method.
Claiming credit for code blocks smaller than a method is discouraged but allowed. If you do, do it sparingly and only claim meaningful blocks of code such as a block of statements, a loop, or an if-else statement.- If an enhancement required you to do tiny changes in many places, there is no need to annotate all those tiny changes; you can describe those changes in the Project Portfolio page instead.
- If a code block was touched by more than one person, either let the person who wrote most of it (e.g. more than 80%) take credit for the entire block, or leave it as 'unclaimed' (i.e., no author tags).
- Related to the above point, if you claim a code block as your own, more than 80% of the code in that block should have been written by yourself. For example, no more than 20% of it can be code you reused from somewhere.
- 💡 GitHub has a blame feature and a history feature that can help you determine who wrote a piece of code.
-
Do not try to boost the quantity of your contribution using unethical means such as duplicating the same code in multiple places. In particular, do not copy-paste test cases to create redundant tests. Even repetitive code blocks within test methods should be extracted out as utility methods to reduce code duplication. Individual members are responsible for making sure code attributed to them are correct. If you notice a team member claiming credit for code that he/she did not write or use other questionable tactics, you can email us (after the final submission) to let us know.
-
If you wrote a significant amount of code that was not used in the final product,
- Create a folder called
{project root}/unused
- Move unused files (or copies of files containing unused code) to that folder
- use
//@@author {yourGithubUsername}-unused
to mark unused code in those files (note the suffixunused
) e.g.
//@@author johndoe-unused method 1 ... method 2 ...
Please put a comment in the code to explain why it was not used.
- Create a folder called
-
If you reused code from elsewhere, mark such code as
//@@author {yourGithubUsername}-reused
(note the suffixreused
) e.g.//@@author johndoe-reused method 1 ... method 2 ...
-
You can use empty
@@author
tags to mark code as not yours when RepoSense attribute the to you incorrectly.-
Code generated by the IDE/framework, should not be annotated as your own.
-
Code you modified in minor ways e.g. adding a parameter. These should not be claimed as yours but you can mention these additional contributions in the Project Portfolio page if you want to claim credit for them.
-
- After you are satisfied with the new results (i.e., results produced by running RepoSense locally), push the
config.json
file you added and/or the annotated code to your repo. We'll use that information the next time we run RepoSense (we run it at least once a week). - If you choose to annotate code, please annotate code chunks not smaller than a method. We do not grade code snippets smaller than a method.
- If you encounter any problem when doing the above or if you have questions, please post in the forum.
We recommend you ensure your code is RepoSense-compatible by v1.3
Product:
- Consider increasing code coverage by adding more tests if it is lower than the level you would like it to be. Take note of
our expectation on test code . - After you have sufficient code coverage, fix remaining code quality problems and bring up the quality to your target level.
- There is no requirement for a minimum coverage level. Note that in a production environment you are often required to have at least 90% of the code covered by tests. In this project, it can be less. The less coverage you have, the higher the risk of regression bugs, which will cost marks if not fixed before the final submission.
- You must write some tests so that we can evaluate your ability to write tests.
- How much of each type of testing should you do? We expect you to decide. You learned different types of testing and what they try to achieve. Based on that, you should decide how much of each type is required. Similarly, you can decide to what extent you want to automate tests, depending on the benefits and the effort required.
Relevant: [
-
Ensure your code has at least some evidence of these (see here for more info)
- logging
- exceptions
- assertions
- defensive coding
-
Ensure there are no coding standard violations e.g. all boolean variables/methods sounds like booleans. Checkstyle can prevent only some coding standard violations; others need to be checked manually.
-
Ensure SLAP is applied at a reasonable level. Long methods or deeply-nested code are symptoms of low-SLAP may be counted against your code quality.
-
Reduce code duplications i.e. if there multiple blocks of code that vary only in minor ways, try to extract out similarities into one place, especially in test code.
-
In addition, try to apply as many of the
code quality guidelines covered in the module as much as you can.
Code Quality
Can explain the importance of code quality
Always code as if the person who ends up maintaining your code will be a violent psychopath who knows where you live. -- Martin Golding
Can explain the importance of readability
Programs should be written and polished until they acquire publication quality. --Niklaus Wirth
Among various dimensions of code quality, such as run-time efficiency, security, and robustness, one of the most important is understandability. This is because in any non-trivial software project, code needs to be read, understood, and modified by other developers later on. Even if we do not intend to pass the code to someone else, code quality is still important because we all become 'strangers' to our own code someday.
The two code samples given below achieve the same functionality, but one is easier to read.
Bad
|
|
Good
|
Bad
|
|
Good
|
Can improve code quality using technique: avoid long methods
Be wary when a method is longer than the computer screen, and take corrective action when it goes beyond 30 LOC (lines of code). The bigger the haystack, the harder it is to find a needle.
Can improve code quality using technique: avoid deep nesting
If you need more than 3 levels of indentation, you're screwed anyway, and should fix your program. --Linux 1.3.53 CodingStyle
In particular, avoid arrowhead style code.
Example:
Can improve code quality using technique: avoid complicated expressions
Avoid complicated expressions, especially those having many negations and nested parentheses. If you must evaluate complicated expressions, have it done in steps (i.e. calculate some intermediate values first and use them to calculate the final value).
Example:
Bad
return ((length < MAX_LENGTH) || (previousSize != length)) && (typeCode == URGENT);
Good
boolean isWithinSizeLimit = length < MAX_LENGTH;
boolean isSameSize = previousSize != length;
boolean isValidCode = isWithinSizeLimit || isSameSize;
boolean isUrgent = typeCode == URGENT;
return isValidCode && isUrgent;
Example:
Bad
return ((length < MAX_LENGTH) or (previous_size != length)) and (type_code == URGENT)
Good
is_within_size_limit = length < MAX_LENGTH
is_same_size = previous_size != length
is_valid_code = is_within_size_limit or is_same_size
is_urgent = type_code == URGENT
return is_valid_code and is_urgent
The competent programmer is fully aware of the strictly limited size of his own skull; therefore he approaches the programming task in full humility, and among other things he avoids clever tricks like the plague. -- Edsger Dijkstra
Can improve code quality using technique: avoid magic numbers
When the code has a number that does not explain the meaning of the number, we call that a magic number (as in “the number appears as if by magic”). Using a
Example:
Bad
|
|
Good
|
Note: Python does not have a way to make a variable a constant. However, you can use a normal variable with an ALL_CAPS
name to simulate a constant.
Bad
|
|
Good
|
Similarly, we can have ‘magic’ values of other data types.
Bad
"Error 1432" // A magic string!
Can improve code quality using technique: make the code obvious
Make the code as explicit as possible, even if the language syntax allows them to be implicit. Here are some examples:
- [
Java
] Use explicit type conversion instead of implicit type conversion. - [
Java
,Python
] Use parentheses/braces to show grouping even when they can be skipped. - [
Java
,Python
] Useenumerations when a certain variable can take only a small number of finite values. For example, instead of declaring the variable 'state' as an integer and using values 0,1,2 to denote the states 'starting', 'enabled', and 'disabled' respectively, declare 'state' as typeSystemState
and define an enumerationSystemState
that has values'STARTING'
,'ENABLED'
, and'DISABLED'
.
Can improve code quality using technique: structure code logically
Lay out the code so that it adheres to the logical structure. The code should read like a story. Just like we use section breaks, chapters and paragraphs to organize a story, use classes, methods, indentation and line spacing in your code to group related segments of the code. For example, you can use blank lines to group related statements together. Sometimes, the correctness of your code does not depend on the order in which you perform certain intermediary steps. Nevertheless, this order may affect the clarity of the story you are trying to tell. Choose the order that makes the story most readable.
Can improve code quality using technique: do not 'trip up' reader
Avoid things that would make the reader go ‘huh?’, such as,
- unused parameters in the method signature
- similar things look different
- different things that look similar
- multiple statements in the same line
- data flow anomalies such as, pre-assigning values to variables and modifying it without any use of the pre-assigned value
Can improve code quality using technique: practice kissing
As the old adage goes, "keep it simple, stupid” (KISS). Do not try to write ‘clever’ code. For example, do not dismiss the brute-force yet simple solution in favor of a complicated one because of some ‘supposed benefits’ such as 'better reusability' unless you have a strong justification.
Debugging is twice as hard as writing the code in the first place. Therefore, if you write the code as cleverly as possible, you are, by definition, not smart enough to debug it. --Brian W. Kernighan
Programs must be written for people to read, and only incidentally for machines to execute. --Abelson and Sussman
Can improve code quality using technique: avoid premature optimizations
Optimizing code prematurely has several drawbacks:
- We may not know which parts are the real performance bottlenecks. This is especially the case when the code undergoes transformations (e.g. compiling, minifying, transpiling, etc.) before it becomes an executable. Ideally, you should use a profiler tool to identify the actual bottlenecks of the code first, and optimize only those parts.
- Optimizing can complicate the code, affecting correctness and understandability
- Hand-optimized code can be harder for the compiler to optimize (the simpler the code, the easier for the compiler to optimize it). In many cases a compiler can do a better job of optimizing the runtime code if you don't get in the way by trying to hand-optimize the source code.
A popular saying in the industry is make it work, make it right, make it fast which means in most cases getting the code to perform correctly should take priority over optimizing it. If the code doesn't work correctly, it has no value on matter how fast/efficient it it.
Premature optimization is the root of all evil in programming. --Donald Knuth
Note that there are cases where optimizing takes priority over other things e.g. when writing code for resource-constrained environments. This guideline simply a caution that you should optimize only when it is really needed.
Can improve code quality using technique: SLAP hard
Avoid varying the level of
Example:
Bad
readData();
salary = basic*rise+1000;
tax = (taxable?salary*0.07:0);
displayResult();
Good
readData();
processData();
displayResult();
Design → Design Fundamentals → Abstraction →
Abstraction is a technique for dealing with complexity. It works by establishing a level of complexity we are interested in, and suppressing the more complex details below that level.
The guiding principle of abstraction is that only details that are relevant to the current perspective or the task at hand needs to be considered. As most programs are written to solve complex problems involving large amounts of intricate details, it is impossible to deal with all these details at the same time. That is where abstraction can help.
Ignoring lower level data items and thinking in terms of bigger entities is called data abstraction.
Within a certain software component, we might deal with a user data type, while ignoring the details contained in the user data item such as name, and date of birth. These details have been ‘abstracted away’ as they do not affect the task of that software component.
Control abstraction abstracts away details of the actual control flow to focus on tasks at a simplified level.
print(“Hello”)
is an abstraction of the actual output mechanism within the computer.
Abstraction can be applied repeatedly to obtain progressively higher levels of abstractions.
An example of different levels of data abstraction: a File
is a data item that is at a higher level than an array and an array is at a higher level than a bit.
An example of different levels of control abstraction: execute(Game)
is at a higher level than print(Char)
which is at a higher than an Assembly language instruction MOV
.
Abstraction is a general concept that is not limited to just data or control abstractions.
Some more general examples of abstraction:
- An OOP class is an abstraction over related data and behaviors.
- An architecture is a higher-level abstraction of the design of a software.
- Models (e.g., UML models) are abstractions of some aspect of reality.
Can improve code quality using technique: make the happy path prominent
The happy path (i.e. the execution path taken when everything goes well) should be clear and prominent in your code. Restructure the code to make the happy path unindented as much as possible. It is the ‘unusual’ cases that should be indented. Someone reading the code should not get distracted by alternative paths taken when error conditions happen. One technique that could help in this regard is the use of guard clauses.
Example:
Bad
if (!isUnusualCase) { //detecting an unusual condition
if (!isErrorCase) {
start(); //main path
process();
cleanup();
exit();
} else {
handleError();
}
} else {
handleUnusualCase(); //handling that unusual condition
}
In the code above,
- Unusual condition detection is separated from their handling.
- Main path is nested deeply.
Good
if (isUnusualCase) { //Guard Clause
handleUnusualCase();
return;
}
if (isErrorCase) { //Guard Clause
handleError();
return;
}
start();
process();
cleanup();
exit();
In contrast, the above code
- deals with unusual conditions as soon as they are detected so that the reader doesn't have to remember them for long.
- keeps the main path un-indented.
Can explain the need for following a standard
One essential way to improve code quality is to follow a consistent style. That is why software engineers follow a strict coding standard (aka style guide).
The aim of a coding standard is to make the entire code base look like it was written by one person. A coding standard is usually specific to a programming language and specifies guidelines such as the location of opening and closing braces, indentation styles and naming styles (e.g. whether to use Hungarian style, Pascal casing, Camel casing, etc.). It is important that the whole team/company use the same coding standard and that standard is not generally inconsistent with typical industry practices. If a company's coding standards is very different from what is used typically in the industry, new recruits will take longer to get used to the company's coding style.
💡 IDEs can help to enforce some parts of a coding standard e.g. indentation rules.
What is the recommended approach regarding coding standards?
c
What is the aim of using a coding standard? How does it help?
Can follow simple mechanical style rules
Learn basic guidelines of the Java coding standard (by OSS-Generic)
Sample coding standard: PEP 8 Python Style Guide -- by Python.org
Consider the code given below:
import java.util.*;
public class Task {
public static final String descriptionPrefix = "description: ";
private String description;
private boolean important;
List<String> pastDescription = new ArrayList<>(); // a list of past descriptions
public Task(String d) {
this.description = d;
if (!d.isEmpty())
this.important = true;
}
public String getAsXML() { return "<task>"+description+"</task>"; }
/**
* Print the description as a string.
*/
public void printingDescription(){ System.out.println(this); }
@Override
public String toString() { return descriptionPrefix + description; }
}
In what ways the code violate the basic guidelines (i.e., those marked with one ⭐️) of the OSS-Generic Java Coding Standard given here?
Here are three:
descriptionPrefix
is a constant and should be namedDESCRIPTION_PREFIX
- method name
printingDescription()
should be named asprintDescription()
- boolean variable
important
should be named to sound boolean e.g.,isImportant
There are many more.
Can follow intermediate style rules
Go through the provided Java coding standard and learn the intermediate style rules.
According to the given Java coding standard, which one of these is not a good name?
b
Explanation: checkWeight
is an action. Naming variables as actions makes the code harder to follow. isWeightValid
may be a better name.
Repeat the exercise in the panel below but also find violations of intermediate level guidelines.
Consider the code given below:
import java.util.*;
public class Task {
public static final String descriptionPrefix = "description: ";
private String description;
private boolean important;
List<String> pastDescription = new ArrayList<>(); // a list of past descriptions
public Task(String d) {
this.description = d;
if (!d.isEmpty())
this.important = true;
}
public String getAsXML() { return "<task>"+description+"</task>"; }
/**
* Print the description as a string.
*/
public void printingDescription(){ System.out.println(this); }
@Override
public String toString() { return descriptionPrefix + description; }
}
In what ways the code violate the basic guidelines (i.e., those marked with one ⭐️) of the OSS-Generic Java Coding Standard given here?
Here are three:
descriptionPrefix
is a constant and should be namedDESCRIPTION_PREFIX
- method name
printingDescription()
should be named asprintDescription()
- boolean variable
important
should be named to sound boolean e.g.,isImportant
There are many more.
Here's one you are more likely to miss:
* Print the description as a string.
→* Prints the description as a string.
There are more.
Can explain the need for good names in code
Proper naming improves the readability. It also reduces bugs caused by ambiguities regarding the intent of a variable or a method.
There are only two hard things in Computer Science: cache invalidation and naming things. -- Phil Karlton
Can improve code quality using technique: use nouns for things and verbs for actions
Every system is built from a domain-specific language designed by the programmers to describe that system. Functions are the verbs of that language, and classes are the nouns. ― Robert C. Martin, Clean Code: A Handbook of Agile Software Craftsmanship
Use nouns for classes/variables and verbs for methods/functions.
Examples:
Name for a | Bad | Good |
---|---|---|
Class | CheckLimit |
LimitChecker |
method | result() |
calculate() |
Distinguish clearly between single-valued and multivalued variables.
Examples:
Good
Person student;
ArrayList<Person> students;
Good
student = Person('Jim')
students = [Person('Jim'), Person('Alice')]
Can improve code quality using technique: use standard words
Use correct spelling in names. Avoid 'texting-style' spelling. Avoid foreign language words, slang, and names that are only meaningful within specific contexts/times e.g. terms from private jokes, a TV show currently popular in your country
Can improve code quality using technique: use name to explain
A name is not just for differentiation; it should explain the named entity to the reader accurately and at a sufficient level of detail.
Examples:
Bad | Good |
---|---|
processInput() (what 'process'?) |
removeWhiteSpaceFromInput() |
flag |
isValidInput |
temp |
If the name has multiple words, they should be in a sensible order.
Examples:
Bad | Good |
---|---|
bySizeOrder() |
orderBySize() |
Imagine going to the doctor's and saying "My eye1 is swollen"! Don’t use numbers or case to distinguish names.
Examples:
Bad | Bad | Good |
---|---|---|
value1 , value2 |
value , Value |
originalValue , finalValue |
Can improve code quality using technique: not too long, not too short
While it is preferable not to have lengthy names, names that are 'too short' are even worse. If you must abbreviate or use acronyms, do it consistently. Explain their full meaning at an obvious location.
Can improve code quality using technique: avoid misleading names
Related things should be named similarly, while unrelated things should NOT.
Example: Consider these variables
colorBlack
: hex value for color blackcolorWhite
: hex value for color whitecolorBlue
: number of times blue is usedhexForRed
: : hex value for color red
This is misleading because colorBlue
is named similar to colorWhite
and colorBlack
but has a different purpose while hexForRed
is named differently but has very similar purpose to the first two variables. The following is better:
hexForBlack
hexForWhite
hexForRed
blueColorCount
Avoid misleading or ambiguous names (e.g. those with multiple meanings), similar sounding names, hard-to-pronounce ones (e.g. avoid ambiguities like "is that a lowercase L, capital I or number 1?", or "is that number 0 or letter O?"), almost similar names.
Examples:
Bad | Good | Reason |
---|---|---|
phase0 |
phaseZero |
Is that zero or letter O? |
rwrLgtDirn |
rowerLegitDirection |
Hard to pronounce |
right left wrong |
rightDirection leftDirection wrongResponse |
right is for 'correct' or 'opposite of 'left'? |
redBooks readBooks |
redColorBooks booksRead |
red and read (past tense) sounds the same |
FiletMignon |
egg |
If the requirement is just a name of a food, egg is a much easier to type/say choice than FiletMignon |
Can explain the need for avoiding error-prone shortcuts
It is safer to use language constructs in the way they are meant to be used, even if the language allows shortcuts. Some such coding practices are common sources of bugs. Know them and avoid them.
Can improve code quality using technique: use the default branch
Always include a default branch in case
statements.
Furthermore, use it for the intended default action and not just to execute the last option. If there is no default action, you can use the 'default' branch to detect errors (i.e. if execution reached the default
branch, throw an exception). This also applies to the final else
of an if-else
construct. That is, the final else
should mean 'everything else', and not the final option. Do not use else
when an if
condition can be explicitly specified, unless there is absolutely no other possibility.
Bad
if (red) print "red";
else print "blue";
Good
if (red) print "red";
else if (blue) print "blue";
else error("incorrect input");
Can improve code quality using technique: don't recycle variables or parameters
- Use one variable for one purpose. Do not reuse a variable for a different purpose other than its intended one, just because the data type is the same.
- Do not reuse formal parameters as local variables inside the method.
Bad
double computeRectangleArea(double length, double width) {
length = length * width;
return length;
}
Good
double computeRectangleArea(double length, double width) {
double area;
area = length * width;
return area;
}
Can improve code quality using technique: avoid empty catch blocks
Never write an empty catch
statement. At least give a comment to explain why the catch
block is left empty.
Can improve code quality using technique: delete dead code
We all feel reluctant to delete code we have painstakingly written, even if we have no use for that code any more ("I spent a lot of time writing that code; what if we need it again?"). Consider all code as baggage you have to carry; get rid of unused code the moment it becomes redundant. If you need that code again, simply recover it from the revision control tool you are using. Deleting code you wrote previously is a sign that you are improving.
Can improve code quality using technique: minimise scope of variables
Minimize global variables. Global variables may be the most convenient way to pass information around, but they do create implicit links between code segments that use the global variable. Avoid them as much as possible.
Define variables in the least possible scope. For example, if the variable is used only within the if
block of the conditional statement, it should be declared inside that if
block.
The most powerful technique for minimizing the scope of a local variable is to declare it where it is first used. -- Effective Java, by Joshua Bloch
Resources:
Can improve code quality using technique: minimise code duplication
Code duplication, especially when you copy-paste-modify code, often indicates a poor quality implementation. While it may not be possible to have zero duplication, always think twice before duplicating code; most often there is a better alternative.
This guideline is closely related to the
Supplmentary → Principles →
DRY (Don't Repeat Yourself) Principle: Every piece of knowledge must have a single, unambiguous, authoritative representation within a system The Pragmatic Programmer, by Andy Hunt and Dave Thomas
This principle guards against duplication of information.
The functionality implemented twice is a violation of the DRY principle even if the two implementations are different.
The value a system-wide timeout being defined in multiple places is a violation of DRY.
Can explain the need for commenting minimally but sufficiently
Good code is its own best documentation. As you’re about to add a comment, ask yourself, ‘How can I improve the code so that this comment isn’t needed?’ Improve the code and then document it to make it even clearer. --Steve McConnell, Author of Clean Code
Some think commenting heavily increases the 'code quality'. This is not so. Avoid writing comments to explain bad code. Improve the code to make it self-explanatory.
Can improve code quality using technique: do not repeat the obvious
If the code is self-explanatory, refrain from repeating the description in a comment just for the sake of 'good documentation'.
Bad
// increment x
x++;
//trim the input
trimInput();
Can improve code quality using technique: write to the reader
Do not write comments as if they are private notes to self. Instead, write them well enough to be understood by another programmer. One type of comments that is almost always useful is the header comment that you write for a class or an operation to explain its purpose.
Examples:
Bad Reason: this comment will only make sense to the person who wrote it
// a quick trim function used to fix bug I detected overnight
void trimInput(){
....
}
Good
/** Trims the input of leading and trailing spaces */
void trimInput(){
....
}
Bad Reason: this comment will only make sense to the person who wrote it
# a quick trim function used to fix bug I detected overnight
def trim_input():
...
Good
def trim_input():
"""Trim the input of leading and trailing spaces"""
...
Can improve code quality using technique: explain what and why, not how
Comments should explain what and why aspect of the code, rather than the how aspect.
What : The specification of what the code supposed to do. The reader can compare such comments to the implementation to verify if the implementation is correct
Example: This method is possibly buggy because the implementation does not seem to match the comment. In this case the comment could help the reader to detect the bug.
/** Removes all spaces from the {@code input} */
void compact(String input){
input.trim();
}
Why : The rationale for the current implementation.
Example: Without this comment, the reader will not know the reason for calling this method.
// Remove spaces to comply with IE23.5 formatting rules
compact(input);
How : The explanation for how the code works. This should already be apparent from the code, if the code is self-explanatory. Adding comments to explain the same thing is redundant.
Example:
Bad Reason: Comment explains how the code works.
// return true if both left end and right end are correct or the size has not incremented
return (left && right) || (input.size() == size);
Good Reason: Code refactored to be self-explanatory. Comment no longer needed.
boolean isSameSize = (input.size() == size) ;
return (isLeftEndCorrect && isRightEndCorrect) || isSameSize;
Documentation:
-
Update documentation to match the product.
-
Create the first version of your Project Portfolio Page (PPP). Reason: Each member needs to create a PPP to describe your contribution to the project. Creating a PPP takes a significant effort; it is too risky to leave it to the last week of the project.
Relevant: [
At the end of the project each student is required to submit a Project Portfolio Page.
-
Objective:
- For you to use (e.g. in your resume) as a well-documented data point of your SE experience
- For us to use as a data point to evaluate your,
- contributions to the project
- your documentation skills
-
Sections to include:
-
Overview: A short overview of your product to provide some context to the reader.
-
Summary of Contributions:
- Code contributed: Give a link to your code on Project Code Dashboard, which should be
https://nuscs2113-ay1819s2.github.io/dashboard-beta/#=undefined&search=github_username_in_lower_case
(replacegithub_username_in_lower_case
with your actual username in lower case e.g.,johndoe
). This link is also available in the Project List Page -- linked to the icon under your photo. - Features implemented: A summary of the features you implemented. If you implemented multiple features, you are recommended to indicate which one is the biggest feature.
- Other contributions:
- Contributions to project management e.g., setting up project tools, managing releases, managing issue tracker etc.
- Evidence of helping others e.g. responses you posted in our forum, bugs you reported in other team's products,
- Evidence of technical leadership e.g. sharing useful information in the forum
- Code contributed: Give a link to your code on Project Code Dashboard, which should be
-
Relevant descriptions/terms/conventions: Include all relevant details necessary to understand the document, e.g., conventions, symbols or labels introduced by you, even if it was not introduced by you.
-
Contributions to the User Guide: Reproduce the parts in the User Guide that you wrote. This can include features you implemented as well as features you propose to implement.
The purpose of allowing you to include proposed features is to provide you more flexibility to show your documentation skills. e.g. you can bring in a proposed feature just to give you an opportunity to use a UML diagram type not used by the actual features. -
Contributions to the Developer Guide: Reproduce the parts in the Developer Guide that you wrote. Ensure there is enough content to evaluate your technical documentation skills and UML modelling skills. You can include descriptions of your design/implementations, possible alternatives, pros and cons of alternatives, etc.
-
If you plan to use the PPP in your Resume, you can also include your SE work outside of the module (will not be graded)
-
-
Format:
-
File name:
docs/team/githbub_username_in_lower_case.adoc
e.g.,docs/team/johndoe.adoc
-
Follow the example in the AddressBook-Level4
-
💡 You can use the Asciidoc's
include
feature to include sections from the developer guide or the user guide in your PPP. Follow the example in the sample. -
It is assumed that all contents in the PPP were written primarily by you. If any section is written by someone else e.g. someone else wrote described the feature in the User Guide but you implemented the feature, clearly state that the section was written by someone else (e.g.
Start of Extract [from: User Guide] written by Jane Doe
). Reason: Your writing skills will be evaluated based on the PPP
-
-
Page limit:
Content Limit Overview + Summary of contributions 0.5-1 (soft limit) Contributions to the User Guide 1-3 (soft limit) Contributions to the Developer Guide 3-6 (soft limit) Total 5-10 (strict) - The page limits given above are after converting to PDF format. The actual amount of content you require is actually less than what these numbers suggest because the HTML → PDF conversion adds a lot of spacing around content.
- Reason for page limit: These submissions are peer-graded (in the PE) which needs to be done in a limited time span.
If you have more content than the limit given above, you can give a representative samples of UG and DG that showcase your documentation skills. Those samples should be understandable on their own. For the parts left-out, you can give an abbreviated version and refer the reader to the full UG/DG for more details.
It's similar to giving extra details as appendices; the reader will look at the UG/DG if the PPP is not enough to make a judgment. For example, when judging documentation quality, if the part in the PPP is not well-written, there is no point reading the rest in the main UG/DG. That's why you need to put the most representative part of your writings in the PPP and still give an abbreviated version of the rest in the PPP itself. Even when judging the quantity of work, the reader should be able to get a good sense of the quantity by combining what is quoted in the PPP and your abbreviated description of the missing part. There is no guarantee that the evaluator will read the full document.
Demo:
- Do a product demo to serve as a rehearsal for the final project demo at v1.4
- Follow
final demo instructions as much as possible. - Cover all features, not just the ones added in the recent iteration.
- Try to make it a 'well prepared' demo i.e., know in advance exactly what you'll do in the demo.
- Follow
-
Duration: Strictly 18 minutes for a 5-person team and 15 minutes for a 4-person team. Exceeding this limit will be penalized. Any set up time will be taken out of your allocated time.
-
Target audience: Assume you are giving a demo to a higher-level manager of your company, to brief him/her on the current capabilities of the product. This is the first time they are seeing the new product you developed but they are familiar with the AddressBook-level4 (AB4) product. The actual audience are the evaluators (the team supervisor and another tutor).
-
Scope:
- Each person should demo the enhancements they added. However, it's ok for one member to do all the typing.
- Subjected to the constraint mentioned in the previous point, as far as possible, organize the demo to present a cohesive picture of the product as a whole, presented in a logical order. Remember to explain the profile of the target user profile and value proposition early in the demo.
- It is recommended you showcase how the feature improves the user’s life rather than simply describe each feature.
- No need to cover design/implementation details as the manager is not interested in those details.
- Mention features you inherited from AB4 only if they are needed to explain your new features. Reason: existing features will not earn you marks, and the audience is already familiar with AB4 features.
- Each person should demo their features.
-
Structure:
- Demo the product using the same executable you submitted, on your own laptop, using the TV.
- It can be a sitting down demo: You'll be demonstrating the features using the TV while sitting down. But you may stand around the TV if you prefer that way.
- It will be an uninterrupted demo: The audience members will not interrupt you during the demo. That means you should finish within the given time.
- The demo should use a sufficient amount of
realistic demo data. e.g at least 20 contacts. Trying to demo a product using just 1-2 sample data creates a bad impression. - Dress code : The level of formality is up to you, but it is recommended that the whole team dress at the same level.
-
Optimizing the time:
- Spend as much time as possible on demonstrating the actual product. Not recommended to use slides (if you do, use them sparingly) or videos or lengthy narrations.
Avoid skits, re-enactments, dramatizations etc. This is not a sales pitch or an informercial. While you need to show how a user use the product to get value, but you don’t need to act like an imaginary user. For example, [Instead of this]Jim get’s a call from boss. "Ring ring", "hello", "oh hi Jim, can we postpone the meeting?" "Sure". Jim hang up and curses the boss under his breath. Now he starts typing ..etc.
[do this]If Jim needs to postpone the meeting, he can type …
It’s not that dramatization is bad or we don’t like it. We simply don’t have enough time for it.
Note that CS2101 demo requirements may differ. Different context → Different requirements. - Rehearse the steps well and ensure you can do a smooth demo. Poor quality demos can affect your grade.
- Don’t waste time repeating things the target audience already knows. e.g. no need to say things like "We are students from NUS, SoC".
- Plan the demo to be in sync with the impression you want to create. For example, if you are trying to convince that the product is easy to use, show the easiest way to perform a task before you show the full command with all the bells and whistles.
- Spend as much time as possible on demonstrating the actual product. Not recommended to use slides (if you do, use them sparingly) or videos or lengthy narrations.
-
Special circumstances:
- If a significant feature was not merged on time: inform the evaluator and get permission to show the unmerged feature using your own version of the code. Unmerged features earn much less marks than a merged equivalent but something is better than nothing.
- If you have no user visible features to show, you can still contribute to the demo by giving an overview of the product (at the start) and/or giving a wrap of of the product (at the end).
- If you are unable to come to the demo due to a valid reason, you can ask a team member to demo your feature. Remember to submit the evidence of your excuse e.g., MC to prof. The demo is part of module assessment and absence without a valid reason will cause you to lose marks.
Do a project demo dry run (as per project demo instructions given below) for your tutor.
Tweak as per peer-testing results, draft Project Portfolio Page, practice product demo.
Project Management:
- Freeze features around this time. Ensure the current product have all the features you intend to release at v1.4. Adding major changes after this point is risky. The remaining time is better spent fixing problems discovered late or on fine-tuning the product.
- Ensure the code attributed to you by RepoSense is correct, as reported in the Project Activity Dashboard
Relevant: [
In previous semesters we asked students to annotate all their code using special @@author
tags so that we can extract each student's code for grading. This semester, we are trying out a tool called RepoSense that is expected to reduce the need for such tagging, and also make it easier for you to see (and learn from) code written by others.
1. View the current status of code authorship data:
- The report generated by the tool is available at Project Code Dashboard. The feature that is most relevant to you is the Code Panel (shown on the right side of the screenshot above). It shows the code attributed to a given author. You are welcome to play around with the other features (they are still under development and will not be used for grading this semester).
- Click on your name to load the code attributed to you (based on Git blame/log data) onto the code panel on the right.
- If the code shown roughly matches the code you wrote, all is fine and there is nothing for you to do.
2. If the code does not match:
-
Here are the possible reasons for the code shown not to match the code you wrote:
- the git username in some of your commits does not match your GitHub username (perhaps you missed our instructions to set your Git username to match GitHub username earlier in the project, or GitHub did not honor your Git username for some reason)
- the actual authorship does not match the authorship determined by git blame/log e.g., another student touched your code after you wrote it, and Git log attributed the code to that student instead
-
In those cases,
- Install RepoSense (see the Getting Started section of the RepoSense User Guide)
- Use the two methods described in the RepoSense User Guide section Configuring a Repo to Provide Additional Data to RepoSense to provide additional data to the authorship analysis to make it more accurate.
- If you add a
config.json
file to your repo (as specified by one of the two methods),- Please use the template json file given in the module website so that your display name matches the name we expect it to be.
- If your commits have multiple author names, specify all of them e.g.,
"authorNames": ["theMyth", "theLegend", "theGary"]
- Update the line
config.json
in the.gitignore
file of your repo as/config.json
so that it ignores theconfig.json
produced by the app but not the_reposense/config.json
.
- If you add
@@author
annotations, please follow the guidelines below:
Adding @@author
tags indicate authorship
-
Mark your code with a
//@@author {yourGithubUsername}
. Note the double@
.
The//@@author
tag should indicates the beginning of the code you wrote. The code up to the next//@@author
tag or the end of the file (whichever comes first) will be considered as was written by that author. Here is a sample code file://@@author johndoe method 1 ... method 2 ... //@@author sarahkhoo method 3 ... //@@author johndoe method 4 ...
-
If you don't know who wrote the code segment below yours, you may put an empty
//@@author
(i.e. no GitHub username) to indicate the end of the code segment you wrote. The author of code below yours can add the GitHub username to the empty tag later. Here is a sample code with an emptyauthor
tag:method 0 ... //@@author johndoe method 1 ... method 2 ... //@@author method 3 ... method 4 ...
-
The author tag syntax varies based on file type e.g. for java, css, fxml. Use the corresponding comment syntax for non-Java files.
Here is an example code from an xml/fxml file.<!-- @@author sereneWong --> <textbox> <label>...</label> <input>...</input> </textbox> ...
-
Do not put the
//@@author
inside java header comments.
👎/** * Returns true if ... * @@author johndoe */
👍
//@@author johndoe /** * Returns true if ... */
What to and what not to annotate
-
Annotate both functional and test code There is no need to annotate documentation files.
-
Annotate only significant size code blocks that can be reviewed on its own e.g., a class, a sequence of methods, a method.
Claiming credit for code blocks smaller than a method is discouraged but allowed. If you do, do it sparingly and only claim meaningful blocks of code such as a block of statements, a loop, or an if-else statement.- If an enhancement required you to do tiny changes in many places, there is no need to annotate all those tiny changes; you can describe those changes in the Project Portfolio page instead.
- If a code block was touched by more than one person, either let the person who wrote most of it (e.g. more than 80%) take credit for the entire block, or leave it as 'unclaimed' (i.e., no author tags).
- Related to the above point, if you claim a code block as your own, more than 80% of the code in that block should have been written by yourself. For example, no more than 20% of it can be code you reused from somewhere.
- 💡 GitHub has a blame feature and a history feature that can help you determine who wrote a piece of code.
-
Do not try to boost the quantity of your contribution using unethical means such as duplicating the same code in multiple places. In particular, do not copy-paste test cases to create redundant tests. Even repetitive code blocks within test methods should be extracted out as utility methods to reduce code duplication. Individual members are responsible for making sure code attributed to them are correct. If you notice a team member claiming credit for code that he/she did not write or use other questionable tactics, you can email us (after the final submission) to let us know.
-
If you wrote a significant amount of code that was not used in the final product,
- Create a folder called
{project root}/unused
- Move unused files (or copies of files containing unused code) to that folder
- use
//@@author {yourGithubUsername}-unused
to mark unused code in those files (note the suffixunused
) e.g.
//@@author johndoe-unused method 1 ... method 2 ...
Please put a comment in the code to explain why it was not used.
- Create a folder called
-
If you reused code from elsewhere, mark such code as
//@@author {yourGithubUsername}-reused
(note the suffixreused
) e.g.//@@author johndoe-reused method 1 ... method 2 ...
-
You can use empty
@@author
tags to mark code as not yours when RepoSense attribute the to you incorrectly.-
Code generated by the IDE/framework, should not be annotated as your own.
-
Code you modified in minor ways e.g. adding a parameter. These should not be claimed as yours but you can mention these additional contributions in the Project Portfolio page if you want to claim credit for them.
-
- After you are satisfied with the new results (i.e., results produced by running RepoSense locally), push the
config.json
file you added and/or the annotated code to your repo. We'll use that information the next time we run RepoSense (we run it at least once a week). - If you choose to annotate code, please annotate code chunks not smaller than a method. We do not grade code snippets smaller than a method.
- If you encounter any problem when doing the above or if you have questions, please post in the forum.
We recommend you ensure your code is RepoSense-compatible by v1.3
Product:
- Consider increasing code coverage by adding more tests if it is lower than the level you would like it to be. Take note of
our expectation on test code . - After you have sufficient code coverage, fix remaining code quality problems and bring up the quality to your target level.
- There is no requirement for a minimum coverage level. Note that in a production environment you are often required to have at least 90% of the code covered by tests. In this project, it can be less. The less coverage you have, the higher the risk of regression bugs, which will cost marks if not fixed before the final submission.
- You must write some tests so that we can evaluate your ability to write tests.
- How much of each type of testing should you do? We expect you to decide. You learned different types of testing and what they try to achieve. Based on that, you should decide how much of each type is required. Similarly, you can decide to what extent you want to automate tests, depending on the benefits and the effort required.
Relevant: [
-
Ensure your code has at least some evidence of these (see here for more info)
- logging
- exceptions
- assertions
- defensive coding
-
Ensure there are no coding standard violations e.g. all boolean variables/methods sounds like booleans. Checkstyle can prevent only some coding standard violations; others need to be checked manually.
-
Ensure SLAP is applied at a reasonable level. Long methods or deeply-nested code are symptoms of low-SLAP may be counted against your code quality.
-
Reduce code duplications i.e. if there multiple blocks of code that vary only in minor ways, try to extract out similarities into one place, especially in test code.
-
In addition, try to apply as many of the
code quality guidelines covered in the module as much as you can.
Code Quality
Can explain the importance of code quality
Always code as if the person who ends up maintaining your code will be a violent psychopath who knows where you live. -- Martin Golding
Can explain the importance of readability
Programs should be written and polished until they acquire publication quality. --Niklaus Wirth
Among various dimensions of code quality, such as run-time efficiency, security, and robustness, one of the most important is understandability. This is because in any non-trivial software project, code needs to be read, understood, and modified by other developers later on. Even if we do not intend to pass the code to someone else, code quality is still important because we all become 'strangers' to our own code someday.
The two code samples given below achieve the same functionality, but one is easier to read.
Bad
|
|
Good
|
Bad
|
|
Good
|
Can improve code quality using technique: avoid long methods
Be wary when a method is longer than the computer screen, and take corrective action when it goes beyond 30 LOC (lines of code). The bigger the haystack, the harder it is to find a needle.
Can improve code quality using technique: avoid deep nesting
If you need more than 3 levels of indentation, you're screwed anyway, and should fix your program. --Linux 1.3.53 CodingStyle
In particular, avoid arrowhead style code.
Example:
Can improve code quality using technique: avoid complicated expressions
Avoid complicated expressions, especially those having many negations and nested parentheses. If you must evaluate complicated expressions, have it done in steps (i.e. calculate some intermediate values first and use them to calculate the final value).
Example:
Bad
return ((length < MAX_LENGTH) || (previousSize != length)) && (typeCode == URGENT);
Good
boolean isWithinSizeLimit = length < MAX_LENGTH;
boolean isSameSize = previousSize != length;
boolean isValidCode = isWithinSizeLimit || isSameSize;
boolean isUrgent = typeCode == URGENT;
return isValidCode && isUrgent;
Example:
Bad
return ((length < MAX_LENGTH) or (previous_size != length)) and (type_code == URGENT)
Good
is_within_size_limit = length < MAX_LENGTH
is_same_size = previous_size != length
is_valid_code = is_within_size_limit or is_same_size
is_urgent = type_code == URGENT
return is_valid_code and is_urgent
The competent programmer is fully aware of the strictly limited size of his own skull; therefore he approaches the programming task in full humility, and among other things he avoids clever tricks like the plague. -- Edsger Dijkstra
Can improve code quality using technique: avoid magic numbers
When the code has a number that does not explain the meaning of the number, we call that a magic number (as in “the number appears as if by magic”). Using a
Example:
Bad
|
|
Good
|
Note: Python does not have a way to make a variable a constant. However, you can use a normal variable with an ALL_CAPS
name to simulate a constant.
Bad
|
|
Good
|
Similarly, we can have ‘magic’ values of other data types.
Bad
"Error 1432" // A magic string!
Can improve code quality using technique: make the code obvious
Make the code as explicit as possible, even if the language syntax allows them to be implicit. Here are some examples:
- [
Java
] Use explicit type conversion instead of implicit type conversion. - [
Java
,Python
] Use parentheses/braces to show grouping even when they can be skipped. - [
Java
,Python
] Useenumerations when a certain variable can take only a small number of finite values. For example, instead of declaring the variable 'state' as an integer and using values 0,1,2 to denote the states 'starting', 'enabled', and 'disabled' respectively, declare 'state' as typeSystemState
and define an enumerationSystemState
that has values'STARTING'
,'ENABLED'
, and'DISABLED'
.
Can improve code quality using technique: structure code logically
Lay out the code so that it adheres to the logical structure. The code should read like a story. Just like we use section breaks, chapters and paragraphs to organize a story, use classes, methods, indentation and line spacing in your code to group related segments of the code. For example, you can use blank lines to group related statements together. Sometimes, the correctness of your code does not depend on the order in which you perform certain intermediary steps. Nevertheless, this order may affect the clarity of the story you are trying to tell. Choose the order that makes the story most readable.
Can improve code quality using technique: do not 'trip up' reader
Avoid things that would make the reader go ‘huh?’, such as,
- unused parameters in the method signature
- similar things look different
- different things that look similar
- multiple statements in the same line
- data flow anomalies such as, pre-assigning values to variables and modifying it without any use of the pre-assigned value
Can improve code quality using technique: practice kissing
As the old adage goes, "keep it simple, stupid” (KISS). Do not try to write ‘clever’ code. For example, do not dismiss the brute-force yet simple solution in favor of a complicated one because of some ‘supposed benefits’ such as 'better reusability' unless you have a strong justification.
Debugging is twice as hard as writing the code in the first place. Therefore, if you write the code as cleverly as possible, you are, by definition, not smart enough to debug it. --Brian W. Kernighan
Programs must be written for people to read, and only incidentally for machines to execute. --Abelson and Sussman
Can improve code quality using technique: avoid premature optimizations
Optimizing code prematurely has several drawbacks:
- We may not know which parts are the real performance bottlenecks. This is especially the case when the code undergoes transformations (e.g. compiling, minifying, transpiling, etc.) before it becomes an executable. Ideally, you should use a profiler tool to identify the actual bottlenecks of the code first, and optimize only those parts.
- Optimizing can complicate the code, affecting correctness and understandability
- Hand-optimized code can be harder for the compiler to optimize (the simpler the code, the easier for the compiler to optimize it). In many cases a compiler can do a better job of optimizing the runtime code if you don't get in the way by trying to hand-optimize the source code.
A popular saying in the industry is make it work, make it right, make it fast which means in most cases getting the code to perform correctly should take priority over optimizing it. If the code doesn't work correctly, it has no value on matter how fast/efficient it it.
Premature optimization is the root of all evil in programming. --Donald Knuth
Note that there are cases where optimizing takes priority over other things e.g. when writing code for resource-constrained environments. This guideline simply a caution that you should optimize only when it is really needed.
Can improve code quality using technique: SLAP hard
Avoid varying the level of
Example:
Bad
readData();
salary = basic*rise+1000;
tax = (taxable?salary*0.07:0);
displayResult();
Good
readData();
processData();
displayResult();
Design → Design Fundamentals → Abstraction →
Abstraction is a technique for dealing with complexity. It works by establishing a level of complexity we are interested in, and suppressing the more complex details below that level.
The guiding principle of abstraction is that only details that are relevant to the current perspective or the task at hand needs to be considered. As most programs are written to solve complex problems involving large amounts of intricate details, it is impossible to deal with all these details at the same time. That is where abstraction can help.
Ignoring lower level data items and thinking in terms of bigger entities is called data abstraction.
Within a certain software component, we might deal with a user data type, while ignoring the details contained in the user data item such as name, and date of birth. These details have been ‘abstracted away’ as they do not affect the task of that software component.
Control abstraction abstracts away details of the actual control flow to focus on tasks at a simplified level.
print(“Hello”)
is an abstraction of the actual output mechanism within the computer.
Abstraction can be applied repeatedly to obtain progressively higher levels of abstractions.
An example of different levels of data abstraction: a File
is a data item that is at a higher level than an array and an array is at a higher level than a bit.
An example of different levels of control abstraction: execute(Game)
is at a higher level than print(Char)
which is at a higher than an Assembly language instruction MOV
.
Abstraction is a general concept that is not limited to just data or control abstractions.
Some more general examples of abstraction:
- An OOP class is an abstraction over related data and behaviors.
- An architecture is a higher-level abstraction of the design of a software.
- Models (e.g., UML models) are abstractions of some aspect of reality.
Can improve code quality using technique: make the happy path prominent
The happy path (i.e. the execution path taken when everything goes well) should be clear and prominent in your code. Restructure the code to make the happy path unindented as much as possible. It is the ‘unusual’ cases that should be indented. Someone reading the code should not get distracted by alternative paths taken when error conditions happen. One technique that could help in this regard is the use of guard clauses.
Example:
Bad
if (!isUnusualCase) { //detecting an unusual condition
if (!isErrorCase) {
start(); //main path
process();
cleanup();
exit();
} else {
handleError();
}
} else {
handleUnusualCase(); //handling that unusual condition
}
In the code above,
- Unusual condition detection is separated from their handling.
- Main path is nested deeply.
Good
if (isUnusualCase) { //Guard Clause
handleUnusualCase();
return;
}
if (isErrorCase) { //Guard Clause
handleError();
return;
}
start();
process();
cleanup();
exit();
In contrast, the above code
- deals with unusual conditions as soon as they are detected so that the reader doesn't have to remember them for long.
- keeps the main path un-indented.
Can explain the need for following a standard
One essential way to improve code quality is to follow a consistent style. That is why software engineers follow a strict coding standard (aka style guide).
The aim of a coding standard is to make the entire code base look like it was written by one person. A coding standard is usually specific to a programming language and specifies guidelines such as the location of opening and closing braces, indentation styles and naming styles (e.g. whether to use Hungarian style, Pascal casing, Camel casing, etc.). It is important that the whole team/company use the same coding standard and that standard is not generally inconsistent with typical industry practices. If a company's coding standards is very different from what is used typically in the industry, new recruits will take longer to get used to the company's coding style.
💡 IDEs can help to enforce some parts of a coding standard e.g. indentation rules.
What is the recommended approach regarding coding standards?
c
What is the aim of using a coding standard? How does it help?
Can follow simple mechanical style rules
Learn basic guidelines of the Java coding standard (by OSS-Generic)
Sample coding standard: PEP 8 Python Style Guide -- by Python.org
Consider the code given below:
import java.util.*;
public class Task {
public static final String descriptionPrefix = "description: ";
private String description;
private boolean important;
List<String> pastDescription = new ArrayList<>(); // a list of past descriptions
public Task(String d) {
this.description = d;
if (!d.isEmpty())
this.important = true;
}
public String getAsXML() { return "<task>"+description+"</task>"; }
/**
* Print the description as a string.
*/
public void printingDescription(){ System.out.println(this); }
@Override
public String toString() { return descriptionPrefix + description; }
}
In what ways the code violate the basic guidelines (i.e., those marked with one ⭐️) of the OSS-Generic Java Coding Standard given here?
Here are three:
descriptionPrefix
is a constant and should be namedDESCRIPTION_PREFIX
- method name
printingDescription()
should be named asprintDescription()
- boolean variable
important
should be named to sound boolean e.g.,isImportant
There are many more.
Can follow intermediate style rules
Go through the provided Java coding standard and learn the intermediate style rules.
According to the given Java coding standard, which one of these is not a good name?
b
Explanation: checkWeight
is an action. Naming variables as actions makes the code harder to follow. isWeightValid
may be a better name.
Repeat the exercise in the panel below but also find violations of intermediate level guidelines.
Consider the code given below:
import java.util.*;
public class Task {
public static final String descriptionPrefix = "description: ";
private String description;
private boolean important;
List<String> pastDescription = new ArrayList<>(); // a list of past descriptions
public Task(String d) {
this.description = d;
if (!d.isEmpty())
this.important = true;
}
public String getAsXML() { return "<task>"+description+"</task>"; }
/**
* Print the description as a string.
*/
public void printingDescription(){ System.out.println(this); }
@Override
public String toString() { return descriptionPrefix + description; }
}
In what ways the code violate the basic guidelines (i.e., those marked with one ⭐️) of the OSS-Generic Java Coding Standard given here?
Here are three:
descriptionPrefix
is a constant and should be namedDESCRIPTION_PREFIX
- method name
printingDescription()
should be named asprintDescription()
- boolean variable
important
should be named to sound boolean e.g.,isImportant
There are many more.
Here's one you are more likely to miss:
* Print the description as a string.
→* Prints the description as a string.
There are more.
Can explain the need for good names in code
Proper naming improves the readability. It also reduces bugs caused by ambiguities regarding the intent of a variable or a method.
There are only two hard things in Computer Science: cache invalidation and naming things. -- Phil Karlton
Can improve code quality using technique: use nouns for things and verbs for actions
Every system is built from a domain-specific language designed by the programmers to describe that system. Functions are the verbs of that language, and classes are the nouns. ― Robert C. Martin, Clean Code: A Handbook of Agile Software Craftsmanship
Use nouns for classes/variables and verbs for methods/functions.
Examples:
Name for a | Bad | Good |
---|---|---|
Class | CheckLimit |
LimitChecker |
method | result() |
calculate() |
Distinguish clearly between single-valued and multivalued variables.
Examples:
Good
Person student;
ArrayList<Person> students;
Good
student = Person('Jim')
students = [Person('Jim'), Person('Alice')]
Can improve code quality using technique: use standard words
Use correct spelling in names. Avoid 'texting-style' spelling. Avoid foreign language words, slang, and names that are only meaningful within specific contexts/times e.g. terms from private jokes, a TV show currently popular in your country
Can improve code quality using technique: use name to explain
A name is not just for differentiation; it should explain the named entity to the reader accurately and at a sufficient level of detail.
Examples:
Bad | Good |
---|---|
processInput() (what 'process'?) |
removeWhiteSpaceFromInput() |
flag |
isValidInput |
temp |
If the name has multiple words, they should be in a sensible order.
Examples:
Bad | Good |
---|---|
bySizeOrder() |
orderBySize() |
Imagine going to the doctor's and saying "My eye1 is swollen"! Don’t use numbers or case to distinguish names.
Examples:
Bad | Bad | Good |
---|---|---|
value1 , value2 |
value , Value |
originalValue , finalValue |
Can improve code quality using technique: not too long, not too short
While it is preferable not to have lengthy names, names that are 'too short' are even worse. If you must abbreviate or use acronyms, do it consistently. Explain their full meaning at an obvious location.
Can improve code quality using technique: avoid misleading names
Related things should be named similarly, while unrelated things should NOT.
Example: Consider these variables
colorBlack
: hex value for color blackcolorWhite
: hex value for color whitecolorBlue
: number of times blue is usedhexForRed
: : hex value for color red
This is misleading because colorBlue
is named similar to colorWhite
and colorBlack
but has a different purpose while hexForRed
is named differently but has very similar purpose to the first two variables. The following is better:
hexForBlack
hexForWhite
hexForRed
blueColorCount
Avoid misleading or ambiguous names (e.g. those with multiple meanings), similar sounding names, hard-to-pronounce ones (e.g. avoid ambiguities like "is that a lowercase L, capital I or number 1?", or "is that number 0 or letter O?"), almost similar names.
Examples:
Bad | Good | Reason |
---|---|---|
phase0 |
phaseZero |
Is that zero or letter O? |
rwrLgtDirn |
rowerLegitDirection |
Hard to pronounce |
right left wrong |
rightDirection leftDirection wrongResponse |
right is for 'correct' or 'opposite of 'left'? |
redBooks readBooks |
redColorBooks booksRead |
red and read (past tense) sounds the same |
FiletMignon |
egg |
If the requirement is just a name of a food, egg is a much easier to type/say choice than FiletMignon |
Can explain the need for avoiding error-prone shortcuts
It is safer to use language constructs in the way they are meant to be used, even if the language allows shortcuts. Some such coding practices are common sources of bugs. Know them and avoid them.
Can improve code quality using technique: use the default branch
Always include a default branch in case
statements.
Furthermore, use it for the intended default action and not just to execute the last option. If there is no default action, you can use the 'default' branch to detect errors (i.e. if execution reached the default
branch, throw an exception). This also applies to the final else
of an if-else
construct. That is, the final else
should mean 'everything else', and not the final option. Do not use else
when an if
condition can be explicitly specified, unless there is absolutely no other possibility.
Bad
if (red) print "red";
else print "blue";
Good
if (red) print "red";
else if (blue) print "blue";
else error("incorrect input");
Can improve code quality using technique: don't recycle variables or parameters
- Use one variable for one purpose. Do not reuse a variable for a different purpose other than its intended one, just because the data type is the same.
- Do not reuse formal parameters as local variables inside the method.
Bad
double computeRectangleArea(double length, double width) {
length = length * width;
return length;
}
Good
double computeRectangleArea(double length, double width) {
double area;
area = length * width;
return area;
}
Can improve code quality using technique: avoid empty catch blocks
Never write an empty catch
statement. At least give a comment to explain why the catch
block is left empty.
Can improve code quality using technique: delete dead code
We all feel reluctant to delete code we have painstakingly written, even if we have no use for that code any more ("I spent a lot of time writing that code; what if we need it again?"). Consider all code as baggage you have to carry; get rid of unused code the moment it becomes redundant. If you need that code again, simply recover it from the revision control tool you are using. Deleting code you wrote previously is a sign that you are improving.
Can improve code quality using technique: minimise scope of variables
Minimize global variables. Global variables may be the most convenient way to pass information around, but they do create implicit links between code segments that use the global variable. Avoid them as much as possible.
Define variables in the least possible scope. For example, if the variable is used only within the if
block of the conditional statement, it should be declared inside that if
block.
The most powerful technique for minimizing the scope of a local variable is to declare it where it is first used. -- Effective Java, by Joshua Bloch
Resources:
Can improve code quality using technique: minimise code duplication
Code duplication, especially when you copy-paste-modify code, often indicates a poor quality implementation. While it may not be possible to have zero duplication, always think twice before duplicating code; most often there is a better alternative.
This guideline is closely related to the
Supplmentary → Principles →
DRY (Don't Repeat Yourself) Principle: Every piece of knowledge must have a single, unambiguous, authoritative representation within a system The Pragmatic Programmer, by Andy Hunt and Dave Thomas
This principle guards against duplication of information.
The functionality implemented twice is a violation of the DRY principle even if the two implementations are different.
The value a system-wide timeout being defined in multiple places is a violation of DRY.
Can explain the need for commenting minimally but sufficiently
Good code is its own best documentation. As you’re about to add a comment, ask yourself, ‘How can I improve the code so that this comment isn’t needed?’ Improve the code and then document it to make it even clearer. --Steve McConnell, Author of Clean Code
Some think commenting heavily increases the 'code quality'. This is not so. Avoid writing comments to explain bad code. Improve the code to make it self-explanatory.
Can improve code quality using technique: do not repeat the obvious
If the code is self-explanatory, refrain from repeating the description in a comment just for the sake of 'good documentation'.
Bad
// increment x
x++;
//trim the input
trimInput();
Can improve code quality using technique: write to the reader
Do not write comments as if they are private notes to self. Instead, write them well enough to be understood by another programmer. One type of comments that is almost always useful is the header comment that you write for a class or an operation to explain its purpose.
Examples:
Bad Reason: this comment will only make sense to the person who wrote it
// a quick trim function used to fix bug I detected overnight
void trimInput(){
....
}
Good
/** Trims the input of leading and trailing spaces */
void trimInput(){
....
}
Bad Reason: this comment will only make sense to the person who wrote it
# a quick trim function used to fix bug I detected overnight
def trim_input():
...
Good
def trim_input():
"""Trim the input of leading and trailing spaces"""
...
Can improve code quality using technique: explain what and why, not how
Comments should explain what and why aspect of the code, rather than the how aspect.
What : The specification of what the code supposed to do. The reader can compare such comments to the implementation to verify if the implementation is correct
Example: This method is possibly buggy because the implementation does not seem to match the comment. In this case the comment could help the reader to detect the bug.
/** Removes all spaces from the {@code input} */
void compact(String input){
input.trim();
}
Why : The rationale for the current implementation.
Example: Without this comment, the reader will not know the reason for calling this method.
// Remove spaces to comply with IE23.5 formatting rules
compact(input);
How : The explanation for how the code works. This should already be apparent from the code, if the code is self-explanatory. Adding comments to explain the same thing is redundant.
Example:
Bad Reason: Comment explains how the code works.
// return true if both left end and right end are correct or the size has not incremented
return (left && right) || (input.size() == size);
Good Reason: Code refactored to be self-explanatory. Comment no longer needed.
boolean isSameSize = (input.size() == size) ;
return (isLeftEndCorrect && isRightEndCorrect) || isSameSize;
Documentation:
-
Update documentation to match the product.
-
Create the first version of your Project Portfolio Page (PPP). Reason: Each member needs to create a PPP to describe your contribution to the project. Creating a PPP takes a significant effort; it is too risky to leave it to the last week of the project.
Relevant: [
At the end of the project each student is required to submit a Project Portfolio Page.
-
Objective:
- For you to use (e.g. in your resume) as a well-documented data point of your SE experience
- For us to use as a data point to evaluate your,
- contributions to the project
- your documentation skills
-
Sections to include:
-
Overview: A short overview of your product to provide some context to the reader.
-
Summary of Contributions:
- Code contributed: Give a link to your code on Project Code Dashboard, which should be
https://nuscs2113-ay1819s2.github.io/dashboard-beta/#=undefined&search=github_username_in_lower_case
(replacegithub_username_in_lower_case
with your actual username in lower case e.g.,johndoe
). This link is also available in the Project List Page -- linked to the icon under your photo. - Features implemented: A summary of the features you implemented. If you implemented multiple features, you are recommended to indicate which one is the biggest feature.
- Other contributions:
- Contributions to project management e.g., setting up project tools, managing releases, managing issue tracker etc.
- Evidence of helping others e.g. responses you posted in our forum, bugs you reported in other team's products,
- Evidence of technical leadership e.g. sharing useful information in the forum
- Code contributed: Give a link to your code on Project Code Dashboard, which should be
-
Relevant descriptions/terms/conventions: Include all relevant details necessary to understand the document, e.g., conventions, symbols or labels introduced by you, even if it was not introduced by you.
-
Contributions to the User Guide: Reproduce the parts in the User Guide that you wrote. This can include features you implemented as well as features you propose to implement.
The purpose of allowing you to include proposed features is to provide you more flexibility to show your documentation skills. e.g. you can bring in a proposed feature just to give you an opportunity to use a UML diagram type not used by the actual features. -
Contributions to the Developer Guide: Reproduce the parts in the Developer Guide that you wrote. Ensure there is enough content to evaluate your technical documentation skills and UML modelling skills. You can include descriptions of your design/implementations, possible alternatives, pros and cons of alternatives, etc.
-
If you plan to use the PPP in your Resume, you can also include your SE work outside of the module (will not be graded)
-
-
Format:
-
File name:
docs/team/githbub_username_in_lower_case.adoc
e.g.,docs/team/johndoe.adoc
-
Follow the example in the AddressBook-Level4
-
💡 You can use the Asciidoc's
include
feature to include sections from the developer guide or the user guide in your PPP. Follow the example in the sample. -
It is assumed that all contents in the PPP were written primarily by you. If any section is written by someone else e.g. someone else wrote described the feature in the User Guide but you implemented the feature, clearly state that the section was written by someone else (e.g.
Start of Extract [from: User Guide] written by Jane Doe
). Reason: Your writing skills will be evaluated based on the PPP
-
-
Page limit:
Content Limit Overview + Summary of contributions 0.5-1 (soft limit) Contributions to the User Guide 1-3 (soft limit) Contributions to the Developer Guide 3-6 (soft limit) Total 5-10 (strict) - The page limits given above are after converting to PDF format. The actual amount of content you require is actually less than what these numbers suggest because the HTML → PDF conversion adds a lot of spacing around content.
- Reason for page limit: These submissions are peer-graded (in the PE) which needs to be done in a limited time span.
If you have more content than the limit given above, you can give a representative samples of UG and DG that showcase your documentation skills. Those samples should be understandable on their own. For the parts left-out, you can give an abbreviated version and refer the reader to the full UG/DG for more details.
It's similar to giving extra details as appendices; the reader will look at the UG/DG if the PPP is not enough to make a judgment. For example, when judging documentation quality, if the part in the PPP is not well-written, there is no point reading the rest in the main UG/DG. That's why you need to put the most representative part of your writings in the PPP and still give an abbreviated version of the rest in the PPP itself. Even when judging the quantity of work, the reader should be able to get a good sense of the quantity by combining what is quoted in the PPP and your abbreviated description of the missing part. There is no guarantee that the evaluator will read the full document.
Demo:
- Do a product demo to serve as a rehearsal for the final project demo at v1.4
- Follow
final demo instructions as much as possible. - Cover all features, not just the ones added in the recent iteration.
- Try to make it a 'well prepared' demo i.e., know in advance exactly what you'll do in the demo.
- Follow
-
Duration: Strictly 18 minutes for a 5-person team and 15 minutes for a 4-person team. Exceeding this limit will be penalized. Any set up time will be taken out of your allocated time.
-
Target audience: Assume you are giving a demo to a higher-level manager of your company, to brief him/her on the current capabilities of the product. This is the first time they are seeing the new product you developed but they are familiar with the AddressBook-level4 (AB4) product. The actual audience are the evaluators (the team supervisor and another tutor).
-
Scope:
- Each person should demo the enhancements they added. However, it's ok for one member to do all the typing.
- Subjected to the constraint mentioned in the previous point, as far as possible, organize the demo to present a cohesive picture of the product as a whole, presented in a logical order. Remember to explain the profile of the target user profile and value proposition early in the demo.
- It is recommended you showcase how the feature improves the user’s life rather than simply describe each feature.
- No need to cover design/implementation details as the manager is not interested in those details.
- Mention features you inherited from AB4 only if they are needed to explain your new features. Reason: existing features will not earn you marks, and the audience is already familiar with AB4 features.
- Each person should demo their features.
-
Structure:
- Demo the product using the same executable you submitted, on your own laptop, using the TV.
- It can be a sitting down demo: You'll be demonstrating the features using the TV while sitting down. But you may stand around the TV if you prefer that way.
- It will be an uninterrupted demo: The audience members will not interrupt you during the demo. That means you should finish within the given time.
- The demo should use a sufficient amount of
realistic demo data. e.g at least 20 contacts. Trying to demo a product using just 1-2 sample data creates a bad impression. - Dress code : The level of formality is up to you, but it is recommended that the whole team dress at the same level.
-
Optimizing the time:
- Spend as much time as possible on demonstrating the actual product. Not recommended to use slides (if you do, use them sparingly) or videos or lengthy narrations.
Avoid skits, re-enactments, dramatizations etc. This is not a sales pitch or an informercial. While you need to show how a user use the product to get value, but you don’t need to act like an imaginary user. For example, [Instead of this]Jim get’s a call from boss. "Ring ring", "hello", "oh hi Jim, can we postpone the meeting?" "Sure". Jim hang up and curses the boss under his breath. Now he starts typing ..etc.
[do this]If Jim needs to postpone the meeting, he can type …
It’s not that dramatization is bad or we don’t like it. We simply don’t have enough time for it.
Note that CS2101 demo requirements may differ. Different context → Different requirements. - Rehearse the steps well and ensure you can do a smooth demo. Poor quality demos can affect your grade.
- Don’t waste time repeating things the target audience already knows. e.g. no need to say things like "We are students from NUS, SoC".
- Plan the demo to be in sync with the impression you want to create. For example, if you are trying to convince that the product is easy to use, show the easiest way to perform a task before you show the full command with all the bells and whistles.
- Spend as much time as possible on demonstrating the actual product. Not recommended to use slides (if you do, use them sparingly) or videos or lengthy narrations.
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Special circumstances:
- If a significant feature was not merged on time: inform the evaluator and get permission to show the unmerged feature using your own version of the code. Unmerged features earn much less marks than a merged equivalent but something is better than nothing.
- If you have no user visible features to show, you can still contribute to the demo by giving an overview of the product (at the start) and/or giving a wrap of of the product (at the end).
- If you are unable to come to the demo due to a valid reason, you can ask a team member to demo your feature. Remember to submit the evidence of your excuse e.g., MC to prof. The demo is part of module assessment and absence without a valid reason will cause you to lose marks.