Relevant: [
To receive full 10 marks allocated for participation, earn at least 15 participation points.
There are 30+ available points to choose from:
-
Good peer ratings - Criteria for professional conduct (1 point for each criterion, max 7)
- Competency criteria (2 points for each, max 6)
Only those who submit peer evaluations can earn participation points from peer evaluations they receive.
- In-lecture quizzes (1 each, max 10 points)
- Enhanced AB1-AB3 (2 points for AB-1, 3 points each for AB-2 and AB-3)
- Module admin tasks done on time and as instructed
- Peer evaluations (1 points each)
- Pre-module survey (1 points)
If your response in the pre-module survey is not usable, you will not earn points for this exercise.
Relevant: [
Peer evaluation criteria: professional conduct
- Professional Communication :
- Communicates sufficiently and professionally. e.g. Does not use offensive language or excessive slang in project communications.
- Responds to communication from team members in a timely manner (e.g. within 24 hours).
- Punctuality: Does not cause others to waste time or slow down project progress by frequent tardiness.
- Dependability: Promises what can be done, and delivers what was promised.
- Effort: Puts in sufficient effort to, and tries their best to keep up with the module/project pace. Seeks help from others when necessary.
- Quality: Does not deliver work products that seem to be below the student's competence level i.e. tries their best to make the work product as high quality as possible within her competency level.
- Meticulousness:
- Rarely overlooks submission requirements.
- Rarely misses compulsory module activities such as pre-module survey.
- Teamwork: How willing are you to act as part of a team, contribute to team-level tasks, adhere to team decisions, etc.
Peer evaluation criteria: competency
- Technical Competency: Able to gain competency in all the required tools and techniques.
- Mentoring skills: Helps others when possible. Able to mentor others well.
- Communication skills: Able to communicate (written and spoken) well. Takes initiative in discussions.
Relevant: [
There is no midterm.
The final exam has two parts:
- Part 1: MCQ questions (30 minutes, 25 marks)
- Part 2: Essay questions (1 hour 30 min, 30 marks)
Both papers will be given to you at the start but you need to answer Part 1 first (i.e. MCQ paper). It will be collected 1 hour after the exam start time (even if arrived late for the exam). You are free to start part 2 early if you finish Part 1 early.
Final Exam: Part 1 (MCQ)
Each MCQ question gives you a statement to evaluate.
An example statement
Testing is a Q&A activity
Unless stated otherwise, the meaning of answer options are
A: Agree. If the question has multiple statements, agree with all of them.
B: Disagree. If the question has multiple statements, disagree with at least one of them
C, D, E: Not used
The exam paper has 50 questions. All questions carry equal marks.
The weightage of the Part 1 of the final exam is 25 marks out of the total score of 100.
Note that you have slightly more than ½ minute for each question, which means you need to go through the questions fairly quickly.
Given the fast pace required by the paper, to be fair to all students, you will not be allowed to clarify doubts about questions (in Part 1) by talking to invigilators.
- If a question is not clear, you can circle the question number in the question paper and write your doubt in the question paper, near that question.
- If your doubt is justified (e.g. there is a typo in the question) or if many students found the question to be unclear, the examiner may decide to omit that question from grading.
Questions in Part 1 are confidential. You are not allowed to reveal Part 1 content to anyone after the exam. All pages of the assessment paper are to be returned at the end of the exam.
You will be given OCR forms (i.e., bubble sheets) to indicate your answers for Part 1. As each OCR form can accommodate only 50 answers, you will be given 2 OCR forms. Indicate your student number in both OCR forms.
Some questions will use underlines or highlighting to draw your attention to a specific part of the question. That is because those parts are highly relevant to the answer and we don’t want you to miss the relevance of that part.
Consider the statement below:
Technique ABC can be used to generate more test cases.
The word can is underlined because the decision you need to make is whether the ABC can or cannot be used to generate more test cases; the decision is not whether ABC can be used to generate more or better test cases.
The exam paper is open-book: you may bring any printed or written materials to the exam in hard copy format. However, given the fast pace required by Part 1, you will not have time left to refer notes during that part of the exam.
💡 Mark the OCR form as you go, rather than planning to transfer your answers to the OCR form near the end. Reason: Given there are 100 questions, it will be hard to estimate how much time you need to mass-transfer all answers to OCR forms.
💡 Write the answer in the exam paper as well when marking it in the OCR form. Reason: It will reduce the chance of missing a question. Furthermore, in case you missed a question, it will help you correct the OCR form quickly.
💡 We have tried to avoid deliberately misleading/tricky questions. If a question seems to take a very long time to figure out, you are probably over-thinking it.
You will be given a practice exam paper to familiarize yourself with this slightly unusual exam format.
Final Exam: Part 2 (Essay)
Unlike in part 1, you can ask invigilators for clarifications if you found a question to be unclear in part 2.
Yes, you may use pencils when answering part 2.
The weightage of the Part 2 of the final exam is 15 marks out of the total score of 100.
Resources
Past exam papers will be uploaded on IVLE.
Relevant: [
Note that project grading is not competitive (not bell curved). CS2113T projects will be assessed separately from CS2113 projects. Given below is the marking scheme.
Total: 50 marks ( 40 individual marks + 10 team marks)
Evaluates: How well do your features fit together to form a cohesive product (not how many features or how big the features are)?
Based on: user guide and the product demo. The quality of the demo will be factored in as well.
💡 Feature that fit well with the other features will earn more marks.
Evaluates:
A. Code quality/quantity:
How good your implementation is, in terms of the quality and the quantity of the code you have written yourself.
Based on: an inspection of the parts of the code you claim as written by you.
-
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;
B. Quality of your feature(s)
Evaluates: How good is your Quality Assurance?
Based on:
- bugs you found in the v1.4 Practical Exam
- bugs in your work found by others during the PE
- testability of your feature (you will lose marks if testers feel that your feature is hard to test manually)
- your test code (you will lose marks if you don't meet
our expectations for automated testing ) - our own manual testing (when necessary)
- 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.
Evaluates: How good are the sections you wrote for the user guide and the developer guide?
Based on: the relevant sections of your project portfolio. Criteria considered:
- Explanation should be clear and written to match the audience.
- Good use of visuals to complement text.
- Use of correct UML notations (where applicable)
A. Process:
Evaluates: How well you did in project management related aspects of the project, as an individual and as a team
Based on: Supervisor observations of project milestones and GitHub data.
Milestones need to be reached the midnight before of the tutorial for it to be counted as achieved. To get a good grade for this aspect, achieve at least 60% of the recommended milestone progress.
Other criteria:
- Good use of GitHub milestones
- Good use of GitHub release mechanism
- Good version control, based on the repo
- Reasonable attempt to use the forking workflow
- Good task definition, assignment and tracking, based on the issue tracker
- Good use of buffers (opposite: everything at the last minute)
- Project done iteratively and incrementally (opposite: doing most of the work in one big burst)
B. Team-tasks:
Evaluates: How much did you contribute to team-tasks?
Based on: peer evaluations and tutor observations
Relevant: [
Here is a non-exhaustive list of team-tasks:
- Necessary general code enhancements e.g.,
- Work related to renaming the product
- Work related to changing the product icon
- Morphing the product into a different product
- Setting up the GitHub, Travis, AppVeyor, etc.
- Maintaining the issue tracker
- Release management
- Updating user/developer docs that are not specific to a feature e.g. documenting the target user profile
- Incorporating more useful tools/libraries/frameworks into the product or the project workflow (e.g. automate more aspects of the project workflow using a GitHub plugin)