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linkDetailed Table of Contents
[W12.3a] Quality Assurance → Quality Assurance → Introduction → What
[W12.3b] Quality Assurance → Quality Assurance → Introduction → Validation versus verification
[W12.3c] Quality Assurance → Quality Assurance → Code Reviews → What
[W12.3d] Quality Assurance → Quality Assurance → Static Analysis → What
[W12.3e] Quality Assurance → Quality Assurance → Formal Verification → What
Guidance for the item(s) below:
Last week, we learned about equivalence partitions, a heuristic for improving E&E of testing. This week, let us learn another heuristic that builds on top of equivalence partitioning.
Guidance for the item(s) below:
The relevant video is here.
Can explain boundary value analysis
Boundary Value Analysis (BVA) is test case design heuristic that is based on the observation that bugs often result from incorrect handling of boundaries of equivalence partitions. This is not surprising, as the end points of the boundary are often used in branching instructions etc. where the programmer can make mistakes.
markCellAt(int x, int y)
operation could contain code such as if (x > 0 && x <= (W-1))
which involves boundaries of x’s equivalence partitions.
BVA suggests that when picking test inputs from an equivalence partition, values near boundaries (i.e. boundary values) are more likely to find bugs.
Boundary values are sometimes called corner cases.
Exercises
What BVA recommends
Boundary value analysis recommends testing only values that reside on the equivalence class boundary.
False
Explanation: It does not recommend testing only those values on the boundary. It merely suggests that values on and around a boundary are more likely to cause errors.
Guidance for the item(s) below:
The relevant video is here.
Can apply boundary value analysis
Typically, you should choose three values around the boundary to test: one value from the boundary, one value just below the boundary, and one value just above the boundary. The number of values to pick depends on other factors, such as the cost of each test case.
Some examples:
Equivalence partition | Some possible boundary values |
---|---|
[1-12] |
0,1,2, 11,12,13 |
[MIN_INT, 0] |
MIN_INT, MIN_INT+1, -1, 0 , 1 |
[any non-null String] |
Empty String, a String of maximum possible length |
[prime numbers] |
No specific boundary |
[non-empty Stack] |
Stack with: one element, two elements, no empty spaces, only one empty space |
Guidance for the item(s) below:
The number of test cases can increase when a the SUT takes multiple inputs. Let's have a brief peek into how we can deal with such situations.
Can explain the need for strategies to combine test inputs
An SUT can take multiple inputs. You can select values for each input (using equivalence partitioning, boundary value analysis, or some other technique).
an SUT that takes multiple inputs and some values chosen as values for each input:
calculateGrade(participation, projectGrade, isAbsent, examScore)
Input | valid values to test | invalid values to test |
---|---|---|
participation | 0, 1, 19, 20 | 21, 22 |
projectGrade | A, B, C, D, F | |
isAbsent | true, false | |
examScore | 0, 1, 69, 70, | 71, 72 |
Testing all possible combinations is effective but not efficient. If you test all possible combinations for the above example, you need to test 6x5x2x6=360 cases. Doing so has a higher chance of discovering bugs (i.e. effective) but the number of test cases can be too high (i.e. not efficient). Therefore, you need smarter ways to combine test inputs that are both effective and efficient.
Can explain some basic test input combination strategies
Given below are some basic strategies for generating a set of test cases by combining multiple test input combination strategies.
Let's assume the SUT has the following three inputs and you have selected the given values for testing:
SUT: foo(p1 char, p2 int, p3 boolean)
Values to test:
Input | Values |
---|---|
p1 | a, b, c |
p2 | 1, 2, 3 |
p3 | T, F |
The all combinations strategy generates test cases for each unique combination of test inputs.
the strategy generates 3x3x2=18 test cases
Test Case | p1 | p2 | p3 |
---|---|---|---|
1 | a | 1 | T |
2 | a | 1 | F |
3 | a | 2 | T |
... | ... | ... | ... |
18 | c | 3 | F |
The at least once strategy includes each test input at least once.
this strategy generates 3 test cases.
Test Case | p1 | p2 | p3 |
---|---|---|---|
1 | a | 1 | T |
2 | b | 2 | F |
3 | c | 3 | VV/IV |
VV/IV = Any Valid Value / Any Invalid Value
The all pairs strategy creates test cases so that for any given pair of inputs, all combinations between them are tested. It is based on the observations that a bug is rarely the result of more than two interacting factors. The resulting number of test cases is lower than the all combinations strategy, but higher than the at least once approach.
this strategy generates 9 test cases:
see steps
Let's first consider inputs p1 and p2:
Input | Values |
---|---|
p1 | a, b, c |
p2 | 1, 2, 3 |
These values can generate (a,1)(a,2)(a,3)(b,1)(b,2),...3x3=9 combinations, and the test cases should cover all of them.
Next, let's consider p1 and p3.
Input | Values |
---|---|
p1 | a, b, c |
p3 | T, F |
These values can generate (a,T)(a,F)(b,T)(b,F),...3x2=6 combinations, and the test cases should cover all of them.
Similarly, inputs p2 and p3 generates another 6 combinations.
The 9 test cases given below covers all those 9+6+6 combinations.
Test Case | p1 | p2 | p3 |
---|---|---|---|
1 | a | 1 | T |
2 | a | 2 | T |
3 | a | 3 | F |
4 | b | 1 | F |
5 | b | 2 | T |
6 | b | 3 | F |
7 | c | 1 | T |
8 | c | 2 | F |
9 | c | 3 | T |
A variation of this strategy is to test all pairs of inputs but only for inputs that could influence each other.
Testing all pairs between p1 and p3 only while ensuring all p2 values are tested at least once:
Test Case | p1 | p2 | p3 |
---|---|---|---|
1 | a | 1 | T |
2 | a | 2 | F |
3 | b | 3 | T |
4 | b | VV/IV | F |
5 | c | VV/IV | T |
6 | c | VV/IV | F |
The random strategy generates test cases using one of the other strategies and then pick a subset randomly (presumably because the original set of test cases is too big).
There are other strategies that can be used too.
Guidance for the item(s) below:
Testing is not the same as Quality Assurance. What else can be done for QA?
Can explain software quality assurance
Software Quality Assurance (QA) is the process of ensuring that the software being built has the required levels of quality.
While testing is the most common activity used in QA, there are other complementary techniques such as static analysis, code reviews, and formal verification.
Guidance for the item(s) below:
The relevant video is here.
Can explain validation and verification
Quality Assurance = Validation + Verification
QA involves checking two aspects:
Whether something belongs under validation or verification is not that important. What is more important is both are done, instead of limiting to verification (i.e., remember that the requirements can be wrong too).
Exercises
statements about validation and verification.
Choose the correct statements about validation and verification.
(a)(b)(c)(d)(e)(f)
Explanation:
Whether something belongs under validation or verification is not that important. What is more important is that we do both.
Developer testing is more about bugs in code, rather than bugs in the requirements.
In QA, system testing is more about verification (does the system follow the specification?) and acceptance testings is more about validation (does the system solve the user’s problem?).
A system crash is more likely to be a bug in the code, not in the requirements.
Guidance for the item(s) below:
The relevant video is here.
Can explain code reviews
Code review is the systematic examination code with the intention of finding where the code can be improved.
Reviews can be done in various forms. Some examples below:
Pull Request reviews
In pair programming
Pair programming:
Pair programming is an agile software development technique in which two programmers work together at one workstation. One, the driver, writes code while the other, the observer or navigator, reviews each line of code as it is typed in. The two programmers switch roles frequently. [source: Wikipedia]
A good introduction to pair programming:
Formal inspections
Inspections involve a group of people systematically examining a project artifacts to discover defects. Members of the inspection team play various roles during the process, such as:
Advantages of code reviews over testing:
Disadvantages:
Resources
Guidance for the item(s) below:
The relevant video is here.
Can explain static analysis
Static analysis: Static analysis is the analysis of code without actually executing the code.
Static analysis of code can find useful information such unused variables, unhandled exceptions, style errors, and statistics. Most modern IDEs come with some inbuilt static analysis capabilities. For example, an IDE can highlight unused variables as you type the code into the editor.
Higher-end static analyzer tools can perform more complex analysis such as locating potential bugs, memory leaks, inefficient code structures etc.
Some example static analyzer for Java: CheckStyle, PMD, FindBugs
Linters are a subset of static analyzers that specifically aim to locate areas where the code can be made 'cleaner'.
Guidance for the item(s) below:
The relevant video is here.
Can explain formal verification
Formal verification uses mathematical techniques to prove the correctness of a program.
An introduction to Formal Methods
by Eric Hehner
Advantages:
Disadvantages:
Exercises
Absence of errors
Testing cannot prove the absence of errors. It can only prove the presence of errors. However, formal methods can prove the absence of errors.
True
Explanation: While using formal methods is more expensive than testing, it indeed can prove the correctness of a piece of software conclusively, in certain contexts. Getting such proof via testing requires exhaustive testing, which is not practical to do in most cases.
Guidance for the item(s) below:
In a previous week, you learned about sequential and iterative ways of doing a software. Now, let us take a quick look at a couple of well-known processes used in the industry, both of which fall into a category called agile processes.
Can explain agile process models
In 2001, a group of prominent software engineering practitioners met and brainstormed for an alternative to documentation-driven, heavyweight software development processes that were used in most large projects at the time. This resulted in something called the agile manifesto (a vision statement of what they were looking to do).
You are uncovering better ways of developing software by doing it and helping others do it.
Through this work you have come to value:
- Individuals and interactions over processes and tools
- Working software over comprehensive documentation
- Customer collaboration over contract negotiation
- Responding to change over following a plan
That is, while there is value in the items on the right, you value the items on the left more.
Extract from the Agile Manifesto
Subsequently, some of the signatories of the manifesto went on to create process models that try to follow it. These processes are collectively called agile processes. Some of the key features of agile approaches are:
There are a number of agile processes in the development world today. eXtreme Programming (XP) and Scrum are two of the well-known ones.
Exercises
statements about agile processes
Choose the correct statements about agile processes.
(a)(b)(c)(d)
Can explain scrum
This description of Scrum was adapted from Wikipedia [retrieved on 18/10/2011], emphasis added:
Scrum is a process skeleton that contains sets of practices and predefined roles. The main roles in Scrum are:
A Scrum project is divided into iterations called Sprints. A sprint is the basic unit of development in Scrum. Sprints tend to last between one week and one month, and are a timeboxed (i.e. restricted to a specific duration) effort of a constant length.
Each sprint is preceded by a planning meeting, where the tasks for the sprint are identified and an estimated commitment for the sprint goal is made, and followed by a review or retrospective meeting, where the progress is reviewed and lessons for the next sprint are identified.
During each sprint, the team creates a potentially deliverable product increment (for example, working and tested software). The set of features that go into a sprint come from the product backlog, which is a prioritized set of high level requirements of work to be done. Which backlog items go into the sprint is determined during the sprint planning meeting. During this meeting, the Product Owner informs the team of the items in the product backlog that he or she wants completed. The team then determines how much of this they can commit to complete during the next sprint, and records this in the sprint backlog. During a sprint, no one is allowed to change the sprint backlog, which means that the requirements are frozen for that sprint. Development is timeboxed such that the sprint must end on time; if requirements are not completed for any reason they are left out and returned to the product backlog. After a sprint is completed, the team demonstrates the use of the software.
Scrum enables the creation of self-organizing teams by encouraging co-location of all team members, and verbal communication between all team members and disciplines in the project.
A key principle of Scrum is its recognition that during a project the customers can change their minds about what they want and need (often called requirements churn), and that unpredicted challenges cannot be easily addressed in a traditional predictive or planned manner. As such, Scrum adopts an empirical approach—accepting that the problem cannot be fully understood or defined, focusing instead on maximizing the team’s ability to deliver quickly and respond to emerging requirements.
Daily Scrum is another key scrum practice. The description below was adapted from https://www.mountaingoatsoftware.com (emphasis added):
In Scrum, on each day of a sprint, the team holds a daily scrum meeting called the "daily scrum.” Meetings are typically held in the same location and at the same time each day. Ideally, a daily scrum meeting is held in the morning, as it helps set the context for the coming day's work. These scrum meetings are strictly time-boxed to 15 minutes. This keeps the discussion brisk but relevant.
...
During the daily scrum, each team member answers the following three questions:
...
The daily scrum meeting is not used as a problem-solving or issue resolution meeting. Issues that are raised are taken offline and usually dealt with by the relevant subgroup immediately after the meeting.
Intro to Scrum in Under 10 Minutes
(This is not an endorsement of the product mentioned in the video)
Can explain XP
The following description was adapted from the XP home page, emphasis added:
Extreme Programming (XP) stresses customer satisfaction. Instead of delivering everything you could possibly want on some date far in the future, this process delivers the software you need as you need it.
XP aims to empower developers to confidently respond to changing customer requirements, even late in the life cycle.
XP emphasizes teamwork. Managers, customers, and developers are all equal partners in a collaborative team. XP implements a simple, yet effective environment enabling teams to become highly productive. The team self-organizes around the problem to solve it as efficiently as possible.
XP aims to improve a software project in five essential ways: communication, simplicity, feedback, respect, and courage. Extreme Programmers constantly communicate with their customers and fellow programmers. They keep their design simple and clean. They get feedback by testing their software starting on day one. Every small success deepens their respect for the unique contributions of each and every team member. With this foundation, Extreme Programmers are able to courageously respond to changing requirements and technology.
XP has a set of simple rules. XP is a lot like a jig saw puzzle with many small pieces. Individually the pieces make no sense, but when combined together a complete picture can be seen. This flow chart shows how Extreme Programming's rules work together.
Pair programming, CRC cards, project velocity, and standup meetings are some interesting topics related to XP. Refer to extremeprogramming.org to find out more about XP.