Detailed Table of Contents
Guidance for the item(s) below:
As you will be dealing with requirements aspects of the tP soon, it's a good time to learn a bit about techniques and tools used for managing requirements. Let's start with a higher-level introduction first.
Can explain requirements
A software requirement specifies a need to be fulfilled by the software product.
A software project may be,
In either case, requirements need to be gathered, analyzed, specified, and managed.
Requirements come from stakeholders.
Stakeholder: A party that is potentially affected by the software project. e.g. users, sponsors, developers, interest groups, government agencies, etc.
Identifying requirements is often not easy. For example, stakeholders may not be aware of their precise needs, may not know how to communicate their requirements correctly, may not be willing to spend effort in identifying requirements, etc.
Can explain non-functional requirements
Requirements can be divided into two in the following way:
Some examples of non-functional requirement categories:
Some concrete examples of NFRs
You may have to spend an extra effort in digging NFRs out as early as possible because,
Exercises
Can explain quality of requirements
Here are some characteristics of well-defined requirements [📖 zielczynski]:
Besides these criteria for individual requirements, the set of requirements as a whole should be
Can explain prioritizing requirements
Requirements can be prioritized based on the importance and urgency, while keeping in mind the constraints of schedule, budget, staff resources, quality goals, and other constraints.
A common approach is to group requirements into priority categories. Note that all such scales are subjective, and stakeholders define the meaning of each level in the scale for the project at hand.
An example scheme for categorizing requirements:
Essential
: The product must have this requirement fulfilled or else it does not get user acceptance.Typical
: Most similar systems have this feature although the product can survive without it.Novel
: New features that could differentiate this product from the rest.Other schemes:
High
, Medium
, Low
Must-have
, Nice-to-have
, Unlikely-to-have
Level 0
, Level 1
, Level 2
, ...Some requirements can be discarded if they are considered ‘out of ’.
The requirement given below is for a Calendar application. Stakeholders of the software (e.g. product designers) might decide the following requirement is not in the scope of the software.
The software records the actual time taken by each task and show the difference between the actual and scheduled time for the task.
Guidance for the item(s) below:
Next, a quick look at techniques used for gathering requirements. They are mostly common-sense but let's go through them for completeness' sake anyway.
Can explain brainstorming
Brainstorming: A group activity designed to generate a large number of diverse and creative ideas for the solution of a problem.
In a brainstorming session there are no "bad" ideas. The aim is to generate ideas; not to validate them. Brainstorming encourages you to "think outside the box" and put "crazy" ideas on the table without fear of rejection.
Exercises
Can explain product surveys
Studying existing products can unearth shortcomings of existing solutions that can be addressed by a new product. Product manuals and other forms of documentation of an existing system can tell us how the existing solutions work.
When developing a game for a mobile device, a look at a similar PC game can give insight into the kind of features and interactions the mobile game can offer.
Can explain observation
Observing users in their natural work environment can uncover product requirements. Usage data of an existing system can also be used to gather information about how an existing system is being used, which can help in building a better replacement e.g. to find the situations where the user makes mistakes when using the current system.
Can explain focus groups
[source]
Focus groups are a kind of informal interview within an interactive group setting. A group of people (e.g. potential users, beta testers) are asked about their understanding of a specific issue, process, product, advertisement, etc.
Can explain prototyping
Prototype: A prototype is a mock up, a scaled down version, or a partial system constructed
Prototyping can uncover requirements, in particular, those related to how users interact with the system. UI prototypes or mock ups are often used in brainstorming sessions, or in meetings with the users to get quick feedback from them.
A mock up (also called a wireframe diagram) of a dialog box:
[source: plantuml.com]
Prototyping can be used for discovering as well as specifying requirements e.g. a UI prototype can serve as a specification of what to build.
Guidance for the item(s) below:
As you may have noticed in the section about prototyping, some techniques can be used for both gathering and specifying requirements. The two things often go hand-in-hand any way. For example, you gather some requirements, specify them in some form, and show them to stakeholders to get feedback.
Now, let's look at other techniques used for specifying requirements.
Can explain prose
A textual description (i.e. prose) can be used to describe requirements. Prose is especially useful when describing abstract ideas such as the vision of a product.
The product vision of the TEAMMATES Project given below is described using prose.
TEAMMATES aims to become the biggest student project in the world (biggest here refers to 'many contributors, many users, large code base, evolving over a long period'). Furthermore, it aims to serve as a training tool for Software Engineering students who want to learn SE skills in the context of a non-trivial real software product.
Avoid using lengthy prose to describe requirements; they can be hard to follow.
Can explain feature list
Feature list: A list of features of a product grouped according to some criteria such as aspect, priority, order of delivery, etc.
A sample feature list from a simple Minesweeper game (only a brief description has been provided to save space):
Can write simple user stories
User story: User stories are short, simple descriptions of a feature told from the perspective of the person who desires the new capability, usually a user or customer of the system. [Mike Cohn]
A common format for writing user stories is:
User story format: As a {user type/role} I can {function} so that {benefit}
Examples (from a Learning Management System):
You can write user stories on index cards or sticky notes, and arrange them on walls or tables, to facilitate planning and discussion. Alternatively, you can use a software (e.g., GitHub Project Boards, Trello, Google Docs, ...) to manage user stories digitally.
User stories in use
With sticky notes
With paper
With software
Exercises
Can write more detailed user stories
The {benefit}
can be omitted if it is obvious.
As a user, I can login to the system so that I can access my data
It is recommended to confirm there is a concrete benefit even if you omit it from the user story. If not, you could end up adding features that have no real benefit.
You can add more characteristics to the {user role}
to provide more context to the user story.
You can write user stories at various levels. High-level user stories, called epics (or themes) cover bigger functionality. You can then break down these epics to multiple user stories of normal size.
[Epic] As a lecturer, I can monitor student participation levels
You can add conditions of satisfaction to a user story to specify things that need to be true for the user story implementation to be accepted as ‘done’.
As a lecturer, I can view the forum post count of each student so that I can identify the activity level of students in the forum.
Conditions:
Separate post count for each forum should be shown
Total post count of a student should be shown
The list should be sortable by student name and post count
Other useful info that can be added to a user story includes (but not limited to)
Exercises
Can use user stories to manage requirements of project
User stories capture user requirements in a way that is convenient for , , and .
[User stories] strongly shift the focus from writing about features to discussing them. In fact, these discussions are more important than whatever text is written. [Mike Cohn, MountainGoat Software 🔗]
User stories differ from mainly in the level of detail. User stories should only provide enough details to make a reasonably low risk estimate of how long the user story will take to implement. When the time comes to implement the user story, the developers will meet with the customer face-to-face to work out a more detailed description of the requirements. [more...]
User stories can capture non-functional requirements too because even NFRs must benefit some stakeholder.
An example of an NFR captured as a user story:
As a | I want to | so that |
---|---|---|
impatient user | to be able experience reasonable response time from the website while up to 1000 concurrent users are using it | I can use the app even when the traffic is at the maximum expected level |
Given their lightweight nature, user stories are quite handy for recording requirements during early stages of requirements gathering.
Given below is a possible recipe you can take when using user stories for early stages of requirement gathering.
Step 0: Clear your mind of preconceived product ideas
Even if you already have some idea of what your product will look/behave like in the end, clear your mind of those ideas. The product is the solution. At this point, we are still at the stage of figuring out the problem (i.e., user requirements). Let's try to get from the problem to the solution in a systematic way, one step at a time.
Step 1: Define the target user as a persona:
Decide your target user's profile (e.g. a student, office worker, programmer, salesperson) and work patterns (e.g. Does he work in groups or alone? Does he share his computer with others?). A clear understanding of the target user will help when deciding the importance of a user story. You can even narrow it down to a persona. Here is an example:
Jean is a university student studying in a non-IT field. She interacts with a lot of people due to her involvement in university clubs/societies. ...
Step 2: Define the problem scope:
Decide the exact problem you are going to solve for the target user. It is also useful to specify what related problems it will not solve so that the exact scope is clear.
ProductX helps Jean keep track of all her school contacts. It does not cover communicating with contacts.
Step 3: List scenarios to form a narrative:
Think of the various scenarios your target user is likely to go through as she uses your app. Following a chronological sequence as if you are telling a story might be helpful.
A. First use:
- Jean gets to know about ProductX. She downloads it and launches it to check out what it can do.
- After playing around with the product for a bit, Jean wants to start using it for real.
- ...
B. Second use: (Jean is still a beginner)
- Jean launches ProductX. She wants to find ...
- ...
C. 10th use: (Jean is a little bit familiar with the app)
- ...
D. 100th use: (Jean is an expert user)
- Jean launches the app and does ... and ... followed by ... as per her usual habit.
- Jean feels some of the data in the app are no longer needed. She wants to get rid of them to reduce clutter.
More examples that might apply to some products:
- Jean uses the app at the start of the day to ...
- Jean uses the app before going to sleep to ...
- Jean hasn't used the app for a while because she was on a three-month training programme. She is now back at work and wants to resume her daily use of the app.
- Jean moves to another company. Some of her clients come with her but some don't.
- Jean starts freelancing in her spare time. She wants to keep her freelancing clients separate from her other clients.
Step 4: List the user stories to support the scenarios:
Based on the scenarios, decide on the user stories you need to support. For example, based on the scenario 'A. First use', you might have user stories such as these:
- As a potential user exploring the app, I can see the app populated with sample data, so that I can easily see how the app will look like when it is in use.
- As a user ready to start using the app, I can purge all current data, so that I can get rid of sample/experimental data I used for exploring the app.
To give another example, based on the scenario 'D. 100th use', you might have user stories such as these:
- As an expert user, I can create shortcuts for tasks, so that I can save time on frequently performed tasks.
- As a long-time user, I can archive/hide unused data, so that I am not distracted by irrelevant data.
Do not 'evaluate' the value of user stories while brainstorming. Reason: an important aspect of brainstorming is not judging the ideas generated.
Other tips:
As a user, I want to see a list of tasks that need my attention most at the present time, so that I pay attention to them first.
While use cases can be recorded on in the initial stages, an online tool is more suitable for longer-term management of user stories, especially if the team is not .
Tool Examples: How to use some example online tools to manage user stories
Resources
Can explain glossary
Glossary: A glossary serves to ensure that all stakeholders have a common understanding of the noteworthy terms, abbreviations, acronyms etc.
Here is a partial glossary from a variant of the Snakes and Ladders game:
Guidance for the item(s) below:
Next, we switch our focus to the aspect of code quality, and learn a few more guidelines you can apply to improve the quality of your code.
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 you do not intend to pass the code to someone else, code quality is still important because you will become a 'stranger' to your 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 Coding Style
In particular, avoid arrowhead style code.
A real code example:
Bad |
|
Good |
|
Bad
| | Good
|
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, it is called a "magic number" (as in "the number appears as if by magic"). Using a makes the code easier to understand because the name tells us more about the meaning of the number.
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, you can have ‘magic’ values of other data types.
Bad
return "Error 1432"; // A magic string!
return "Error 1432" # A magic string!
In general, try to avoid any magic literals.
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 groupings even when they can be skipped.Java
, Python
] Use enumerations 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 type SystemState
and define an enumeration SystemState
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 how you 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,
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:
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 no matter how fast/efficient it is.
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 is 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 abstraction within a code fragment. Note: The book The Productive Programmer (by Neal Ford) calls this the Single Level of Abstraction Principle (SLAP) while the book Clean Code (by Robert C. Martin) calls this One Level of Abstraction per Function.
Example:
Bad (readData();
and salary = basic * rise + 1000;
are at different levels of abstraction)
readData();
salary = basic * rise + 1000;
tax = (taxable ? salary * 0.07 : 0);
displayResult();
Good (all statements are at the same level of abstraction)
readData();
processData();
displayResult();
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,
Good
if (isUnusualCase) { //Guard Clause
handleUnusualCase();
return;
}
if (isErrorCase) { //Guard Clause
handleError();
return;
}
start();
process();
cleanup();
exit();
In contrast, the above code
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. 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, raise a suitable error). 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
Bad
double computeRectangleArea(double length, double width) {
length = length * width;
return length;
}
def compute_rectangle_area(length, width):
length = length * width
return length
Good
double computeRectangleArea(double length, double width) {
double area;
area = length * width;
return area;
}
def compute_rectangle_area(length, width):
area = length * width
return area
}
Can improve code quality using technique: delete dead code
You might feel reluctant to delete code you have painstakingly written, even if you have no use for that code anymore ("I spent a lot of time writing that code; what if I 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: minimize 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: minimize 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 DRY Principle.
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'. That 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();
Bad
# increment x
x = x + 1
# trim the input
trim_input()
Can improve code quality using technique: write to the reader
Do not write comments as if they are private notes to yourself. Instead, write them well enough to be understood by another programmer. One type of comment 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
def trim_input():
"""a quick trim function used to fix bug I detected overnight"""
...
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 the what and why aspects of the code, rather than the how aspect.
What: The specification of what the code is 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;
Guidance for the item(s) below:
We've already started learning ways to improve the code quality e.g., following a coding standard. The next topic introduces you to a systematic way of changing the code to improve its quality.
Can explain refactoring
The first version of the code you write may not be of production quality. It is OK to first concentrate on making the code work, rather than worry over the quality of the code, as long as you improve the quality later. This process of improving a program's internal structure in small steps without modifying its external behavior is called refactoring.
Improving code structure can have many secondary benefits: e.g.
Given below are two common refactorings (more).
Refactoring Name: Consolidate Duplicate Conditional Fragments
Situation: The same fragment of code is in all branches of a conditional expression.
Method: Move it outside of the expression.
Example:
| → |
|
| → |
|
Refactoring Name: Extract Method
Situation: You have a code fragment that can be grouped together.
Method: Turn the fragment into a method whose name explains the purpose of the method.
Example:
void printOwing() {
printBanner();
// print details
System.out.println("name: " + name);
System.out.println("amount " + getOutstanding());
}
void printOwing() {
printBanner();
printDetails(getOutstanding());
}
void printDetails(double outstanding) {
System.out.println("name: " + name);
System.out.println("amount " + outstanding);
}
def print_owing():
print_banner()
# print details
print("name: " + name)
print("amount " + get_outstanding())
def print_owing():
print_banner()
print_details(get_outstanding())
def print_details(amount):
print("name: " + name)
print("amount " + amount)
Some IDEs have builtin support for basic refactorings such as automatically renaming a variable/method/class in all places it has been used.
Refactoring, even if done with the aid of an IDE, may still result in regressions. Therefore, each small refactoring should be followed by regression testing.
Exercises
Implementation → Refactoring → What
Can use automated refactoring features of the IDE
This video explains how to automate the 'Extract variable' refactoring using IntelliJ IDEA. Most other refactorings available work similarly. i.e. select the code to refactor
→ find the refactoring in the context menu
or use the keyboard shortcut
.
Here's another video explaining how to do some more useful refactorings in Intellij IDEA.
Can apply some basic refactoring
Given below are some more commonly used refactorings. A more comprehensive list is available at refactoring-catalog.
Can decide when to apply a given refactoring
One way to identify refactoring opportunities is by code smells.
A code smell is a surface indication that usually corresponds to a deeper problem in the system. First, a smell is by definition something that's quick to spot. Second, smells don't always indicate a problem.
--adapted from https://martinfowler.com/bliki/CodeSmell.html
An example (from the same source as above) is the code smell data class i.e., a class with all data and no behavior. When you encounter the such a class, you can explore if refactoring it to move the corresponding behavior into that class is appropriate. Some more examples:
Periodic refactoring is a good way to pay off the technical debt a code base has accumulated.
Software systems are prone to the build up of cruft - deficiencies in internal quality that make it harder than it would ideally be to modify and extend the system further.Technical Debt is a metaphor, coined by Ward Cunningham, that frames how to think about dealing with this cruft, thinking of it like a financial debt. The extra effort that it takes to add new features is the interest paid on the debt.
--https://martinfowler.com/bliki/TechnicalDebt.html
While it is important to refactor frequently so as to avoid the accumulation of ‘messy’ code (aka technical debt), an important question is how much refactoring is too much refactoring? It is too much refactoring when the benefits no longer justify the cost. The costs and the benefits depend on the context. That is why some refactorings are ‘opposites’ of each other (e.g. extract method vs inline method).
Resources
Exercises
Guidance for the item(s) below:
Given next are two prerequisite topics that you'll encounter in the tP. They are shown here in case you haven't learned them before you would like to refresh your memory.
Can explain assertions
Assertions are used to define assumptions about the program state so that the runtime can verify them. An assertion failure indicates a possible bug in the code because the code has resulted in a program state that violates an assumption about how the code should behave.
An assertion can be used to express something like when the execution comes to this point, the variable v
cannot be null.
If the runtime detects an assertion failure, it typically takes some drastic action such as terminating the execution with an error message. This is because an assertion failure indicates a possible bug and the sooner the execution stops, the safer it is.
In the Java code below, suppose you set an assertion that timeout
returned by Config.getTimeout()
is greater than 0
. Now, if Config.getTimeout()
returns -1
in a specific execution of this line, the runtime can detect it as an assertion failure -- i.e. an assumption about the expected behavior of the code turned out to be wrong which could potentially be the result of a bug -- and take some drastic action such as terminating the execution.
int timeout = Config.getTimeout();
Can use assertions
Use the assert
keyword to define assertions.
This assertion will fail with the message x should be 0
if x
is not 0 at this point.
x = getX();
assert x == 0 : "x should be 0";
...
Assertions can be disabled without modifying the code.
java -enableassertions HelloWorld
(or java -ea HelloWorld
) will run HelloWorld
with assertions enabled while java -disableassertions HelloWorld
will run it without verifying assertions.
Java disables assertions by default. This could create a situation where you think all assertions are being verified as true
while in fact they are not being verified at all. Therefore, remember to enable assertions when you run the program if you want them to be in effect.
Enable assertions in Intellij (how?) and get an assertion to fail temporarily (e.g. insert an assert false
into the code temporarily) to confirm assertions are being verified.
Java assert
vs JUnit assertions: They are similar in purpose but JUnit assertions are more powerful and customized for testing. In addition, JUnit assertions are not disabled by default. We recommend you use JUnit assertions in test code and Java assert
in functional code.
Resources
Tutorials:
Best practices:
Can use assertions optimally
It is recommended that assertions be used liberally in the code. Their impact on performance is considered low and worth the additional safety they provide.
Do not use assertions to do work because assertions can be disabled. If not, your program will stop working when assertions are not enabled.
The code below will not invoke the writeFile()
method when assertions are disabled. If that method is performing some work that is necessary for your program, your program will not work correctly when assertions are disabled.
...
assert writeFile() : "File writing is supposed to return true";
Assertions are suitable for verifying assumptions about Internal Invariants, Control-Flow Invariants, Preconditions, Postconditions, and Class Invariants. Refer to [Programming with Assertions (second half)] to learn more.
Exceptions and assertions are two complementary ways of handling errors in software but they serve different purposes. Therefore, both assertions and exceptions should be used in code.
Exercises
Can use Java8 streams
Java 8 introduced a number of new features (e.g. Lambdas, Streams) that are not trivial to learn but also extremely useful to know.
Here is an overview of new Java 8 features (written by Benjamin Winterberg).
Resources
Tutorials:
A video tutorial by well-known Java coach Venkat Subramaniam
A a more detailed version covering similar grounds
Can review and merge PRs on GitHub
Let's look at the steps involved in merging a PR, assuming the PR has been reviewed, refined, and approved for merging already.
Preparation: If you would like to try merging a PR yourself, you can create a dummy PR in the following manner.
feature1
) and add some commits to it.master
branch in your fork. Yes, it is possible to create a PR within the same repo.1. Locate the PR to be merged in your repo's GitHub page.
2. Click on the Conversation tab and scroll to the bottom. You'll see a panel containing the PR status summary.
3. If the PR is not merge-able in the current state, the Merge pull request will not be green. Here are the possible reasons and remedies:
master
branch has been updated since the PR code was last updated.
master
branch has been updated since the PR code was last updated, in a way that the PR code conflicts with the current master
branch. Those conflicts must be resolved before the PR can be merged.
3. Merge the PR by clicking on the Merge pull request button, followed by the Confirm merge
button. You should see a Pull request successfully merged and closed
message after the PR is merged.
Create merge commit
options are recommended.Next, sync your local repos (and forks). Merging a PR simply merges the code in the upstream remote repository in which it was merged. The PR author (and other members of the repo) needs to pull the merged code from the upstream repo to their local repos and push the new code to their respective forks to sync the fork with the upstream repo.