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Test Coverage
CS-300 Fall 2005
Supreeth Venkataraman
CS-300 Fall 2005 Supreeth Venkataraman 2
Test Coverage
Coverage is a measure of how much testing can be done given a set of test cases.
Given a set of test cases, how much of the code in the program being tested is covered?
Or.. Given a set of test cases how many functionalities as listed in the requirements can be tested?
Coverage in most cases is a term associated with white-box testing or structural testing.
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Black Box Testing
Black-box testing involves deriving test cases based on the functional requirements of the program being tested.
“Does the software exhibit the intended behavior for each of its functionalities?”
Black-box testing can be used to detect improper functionality, errors of interface, errors in data structures, and initialization and termination errors with little regard for the logical structure of the program. [Pressman 97]
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Black Box Testing
We have already seen many types of blackbox testing
Fault-Based testing, boundary-value testing, etc.
Functional testing is thought of as being superior to structural testing in most cases
However, it is acknowledged that code based testing does uncover a lot of defects.
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Equivalence Partitioning
A good test case is one that has a good likelihood of uncovering a fault.
Exhaustive testing is impossible due to the infinite domain of inputs.
We must choose a suitable subset of inputs so that “it covers a large part of other possible test cases” – Myers, p.45
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Equivalence Partitioning
Partition the input domain into equivalence classes
The goal here is to partition the inputs in such a way that if one test case in an equivalence class is capable of detecting some fault, then all test cases in that class are capable of detecting the same fault.
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Equivalence Partitioning
An example of an equivalence class for E-LIB. A set of strings that obey the rules of structure
of the SSN. While checking for the structure of the SSN, if
one test case from our class does not uncover a fault, it is reasonable to assume that none of the strings in the class will reveal a fault.
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White Box Testing
White-box testing is also known as structural testing or code-based testing.
The test cases to be used to test the program are derived from the program structure, and not from functional specifications.
Many many variations of white-box testing exist.
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White Box Testing – and criticisms
A lot of research has been undertaken to discover the best kind of code coverage.
“All testing that does not derive from functions is fundamentally misguided”
“People do not use software in order to execute its statements; rather they invoke its functionality”
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White box or Black box? Achieving code coverage does not imply that
good functional coverage is achieved as well. A good mix of functional and structural testing
is desirable as both functional as well as code coverage are important.
Structural test cases must wait to be derived until the code is written, but functional tests can be derived from requirements.
Weyuker proposed that structural testing be used as a way of evaluating functional test quality.
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White box or Black Box?
In many cases, structural coverage is done after adequate functional coverage is achieved.
Structural testing is used to back up functional testing
If structural testing is inadequate, create additional functional test cases.
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Test Adequacy
The term “adequacy” can be thought of as asking oneself the question “How many test cases do I need in order to completely cover the entire program based on the technique that I have chosen for testing?
Or….When do I stop testing?
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Control Flow Testing
Control-flow testing is based on the flow of control in a program.
There are many variations of control-flow testing. Statement coverage, branch coverage, path coverage etc.
We will examine statement coverage and branch coverage in some detail.
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The Program Flowgraph
A program flowgraph graphically represents the potential control flow of a program.
Program flowgraphs are made up of nodes and directed edges
Each node represents a basic block, which can be defined as a collection of statements that are always executed together.
Each directed edge between two nodes A and B in a control flow graph represents a potential control path from A to B
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Example Programvoid myflow(int x,int y) { int a; if (y == 0) { a = 1; } else { a = y; } y = y – 1; if (a > 0) { a = x; } else { a = x + 1; } printf(“%d\n”, a);}
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2
3
4 6
7
8
911
12
y == 0 y != 0
a > 0 a ≤ 0
1. void myflow(int x, int y) {2. int a;3. if (y == 0) {4. a = 1;5. } else {6. a = y; }7. y = y – 1;8. if (a > 0) {9. a = x;10. } else {11. a = x + 1; }12. printf(“%d\n”, a); }
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Statement Coverage
Achieving statement coverage means that all statements in the program have to be executed at least once by a set of test cases
Having complete statement coverage does not necessarily mean that the program cannot fail
Think about the input space.... Statement coverage is also called all-nodes
testing.
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Statement Coverage Test Cases
Test case1: input = {x = 7, y = 0}
expected output = {a = 7}
Test case2: input = {x = 7, y = -1}
expected output = {a = 8}
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Branch Coverage
Achieving branch coverage means that there must be enough test cases so that every path for a conditional transfer of control is exercised
Or... Every true and false branch have to be exercised by some test case
Complete coverage means that the test cases should be sufficient to traverse all the edges in the program graph.
This form of testing is also known as all-edges testing .
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Branch Coverage
The fact that there is complete branch coverage does not mean that all errors will be found. Branch testing does not necessarily check all combinations of control transfers.
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Branch Coverage Test Cases
Test case1: input = {x = 7, y = 0}
expected output = {a = 7}
Test case2: input = {x = 7, y = -1}
expected output = {a = 8}
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Path Coverage
Path coverage means that all possible execution paths in the program must be executed.
This is a very strong coverage criterion, but impractical.
Programs with loops have an infinite number of execution paths, and thus would need an infinite number of test cases
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Data Flow Testing
Data flow testing is based on the definition and use of variables in a program.
Deals with flow of data rather than flow of control.
There are many data-flow testing methods All-definitions coverage, all-uses coverage, all-
du-paths coverage etc. We will look at all-uses testing in some detail
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Terminology (Beizer)
Definition – a variable is said to be defined when it is initialized with a value as part of a declaration, or when it appears on the left hand side of an assignment statement .
eg: x = 4;
int y = 0;
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Terminology
Use – The value of a variable is said to be used either when the variable appears on the right hand side of an assignment statement or when it appears in a predicate statement like if (x > y) (Beizer)
Eg: y = x;
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Terminology
Definition-clear path - This is a set of connected nodes in the flowgraph where some variable x is defined in the first node, and is not subsequently redefined in any other node in the path.
For example, the path 2-3-4-7-8-9-12 is a definition-clear path with respect to variable “x” in figure 2.2.
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2
3
4 6
7
8
911
12
y == 0 y != 0
a > 0 a ≤ 0
1. void myflow(int x, int y) {2. int a;3. if (y == 0) {4. a = 1;5. } else {6. a = y; }7. y = y – 1;8. if (a > 0) {9. a = x;10. } else {11. a = x + 1; }12. printf(“%d\n”, a); }
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All-Uses Testing
The all-uses treatment states that there must be at least one definition-clear path exercised by some test case from every definition of a variable x to all of its uses.
All-uses testing is a powerful test coverage criterion.
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All-Uses test cases Test case1: input = {x = 7, y = 0} expected output = {a = 7} Path = {2-3-4-7-8-9} Test case2: input = {x = 7, y = -1} expected output = {a = 8} Path = {2-3-6-7-8-9} Test case3: input = {x = 7, y = 4} expected output = {a = 7} Path = {2-3-6-7-8-11}
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The Subsumes Relationship
The subsumption relationship means that satisfying one test coverage criterion may implicitly force another test coverage criterion to be satisfied as well
Eg: Branch coverage forces statement coverage to be attained as well (This is strict subsumption)
“Subsumes” does not necessarily mean “better”
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Subsumption Hierarchy (Rapps and Weyuker)
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Mutation Testing
Mutation testing involves changing (mutating) the program source statement(s)
If the actual output from a test case is different from the expected output (hopefully it will be), the test case is said to kill the mutant.
Mutation coverage requires that all mutants be killed
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Some Mutation Examples
Operator mutation – change the operator in the mutated version.• Eg: change x + y to x – y or x * y …
• Change x < y to x <=y or x >=y …
If all the mutants are killed we are satisfied that no wrong operator has been mistakenly used.
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Choosing a Testing Method
The process• If the development process is not well defined
without a proper test plan one does not really know what type of testing to apply.
• If the project starts getting delayed, then testing time is extremely limited.
Resources available• testing time, testing experience, budget ...
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Choosing a Testing Method
Feasibility Issues• Structural testing may not achieve complete
code coverage because of dead code
• Dead code is code that never gets executed.
• There could be dead statements, dead paths etc.
• The tester must devote time to identifying infeasible code.
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Conclusions
In practice, there is no agreement as to what the payoffs are for each form of structural testing
Functional testing has advantages over structural testing because functional tests capture the expected actions of users.