1. Software Testing Part III: Test Assessment and Improvement
Aditya P. Mathur
Purdue university
Last update: November 15, 2001

2. Test assessment and improvement
Learning Objectives
To understand the relevance and importance of test assessment.
To learn the fundamental principle underlying test assessment.
To learn various methods and tools for test assessment.
Test assessment and improvement

3. Test assessment and improvement
Learning objectives
To understand the relative strengths/weaknesses of test assessment methods.
To learn how to improve tests based on a test assessment procedure.
Test assessment and improvement

4. What is test assessment?
Once a test set T, a collection of test inputs, has been developed, we ask:
How good is T?
It is the measurement of the goodness of T which is known as test assessment.
Test assessment is carried out based on one or more criteria.
Test assessment and improvement

5. Test assessment-continued
These criteria are known as test adequacy criteria.
Test assessment is also known as test adequacy assessment.
Test assessment and improvement

6. Test assessment-continued
Test assessment provides the following information:
A metric, also known as the adequacy score or coverage, usually between 0 and 1.
A list of all the weaknesses found in T, which when removed, will raise the score to 1.
The weaknesses depend on the criteria used for assessment.
Test assessment and improvement

7. Test assessment-continued
Once the coverage has been computed, and the weaknesses identified, one can improve T.
Improvement of T is done by examining one or more weaknesses and constructing new test requirements designed to overcome the weakness(es).
The new test requirements lead to new test specifications and to further testing of the program.
Test assessment and improvement

8. Test assessment-continued
This is continued until all weaknesses are overcome, i.e. the adequacy criterion is satisfied (coverage=1).
In some instances it may not be possible to satisfy the adequacy criteria for one or more of the following reasons:
Lack of sufficient manpower
Weaknesses that cannot be removed because they are infeasible.
Test assessment and improvement

9. Test assessment-continued
The cost of removing the weaknesses is not justified.
While improving T by removing its weaknesses, one usually tests the program more thoroughly than it has been tested so far.
This additional testing is likely to result in the discovery of remaining errors.
Test assessment and improvement

10. Test assessment-continued
Hence we say that test assessment and improvement helps in the improvement of software reliability.
Test assessment and improvement is applicable throughout the testing process and during all stages of software development.
Test assessment and improvement

11. Test assessment-summary procedure
Develop T 1
Select an adequacy
criterion C. 2
Measure adequacy of T
w.r.t. C.
Yes 3
Is T adequate?
Yes No 4
Improve T 5
More testing is warranted ? No 6
Done
Test assessment and improvement

12. Principle underlying test assessment
There is a uniform principle that underlies test assessment throughout the testing process.
This principle is known as the coverage principle.
It has come about as a result of intensive research at Purdue and other research groups in software testing.
Test assessment and improvement

13. The coverage principle
To formulate and understand the coverage principle, we need to understand:
coverage domains
coverage elements
A coverage domain is a finite domain, related to the program under test, that we want to cover. Coverage elements are the individual elements of this domain
Test assessment and improvement

14. The coverage principle-continued
Requirements
Classes
Functions
Interface mutations
Exceptions
Coverage Domains
Coverage Elements
Test assessment and improvement

15. The coverage principle-continued
Measuring test adequacy and improving a test set against a sequence of well defined, increasingly strong, coverage domains leads to improved confidence in the reliability of the system under test.
Test assessment and improvement

16. The coverage principle-continued
Note the following properties of a coverage domain:
It is related to the program under test.
It is finite.
It may come from program requirements, related to the inputs and outputs.
Test assessment and improvement

17. The coverage principle-continued
It may come from program code. Can you think of a coverage domain that comes from the program code?
It aids in measuring test adequacy as well as the progress made in testing. How?
Test assessment and improvement

18. The coverage principle-continued
Example:
It is required to write a program that takes in the name of a person as a string and searches for the name in a file of names. The program must output the record ID which matches the given name. In case of no match a -1 is returned.
What coverage domains can be identified from this requirement?
Test assessment and improvement

19. The coverage principle-continued
As we learned earlier, improving coverage improves our confidence in the correct functioning of the program under test.
Given a program P and a test T suppose that T is adequate w.r.t. a coverage criterion C.
Does this mean that P is error free?
Obviously……???
Test assessment and improvement

20. Test assessment and improvement
Test effort
There are several measures of test effort.
One measure is the size of T. By this measure a test set with a larger number of test cases corresponds to higher effort than one with a lesser number of test cases.
Test assessment and improvement

21. Error detection effectiveness
Each coverage criterion has its error detection ability. This is also known as the error detection effectiveness or simply effectiveness of the criterion.
One measure of the effectiveness of criterion C is the fraction of faults guaranteed to be revealed by a test T that satisfies C.
Test assessment and improvement

22. Effectiveness-continued
Another measure is the probability that at least fraction f of the faults in P will be revealed by test T that satisfies C.
Unfortunately there is no absolute measure of the effectiveness of any given coverage criterion for a general class of programs and for arbitrary test sets.
Test assessment and improvement

23. Effectiveness-continued
One coverage criterion results in an exception to this rule: What is it?
Empirical studies conducted by researchers give us an idea of the relative goodness of various coverage criteria.
Thus, for a variety of criteria we can make a statement like: Criterion C1 is definitely better than criterion C2.
Test assessment and improvement

24. Effectiveness-continued
In some cases we may be able to say: Criterion C1 is probably better than criterion C2.
Such information allows us to construct a hierarchy of coverage criteria.
This hierarchy is helpful in organizing and managing testing. How?
Test assessment and improvement

25. Strength of a coverage criterion
The effectiveness of a coverage criterion is also referred to as its strength.
Strength is a measure of the criterion’s ability to reveal faults in a program.
Criterion C1 is considered stronger than criterion C2 if C1 is is capable of revealing more faults than C2.
Test assessment and improvement

26. Test assessment and improvement
The Saturation Effect
The rate at which new faults are discovered reduces as test adequacy with respect to a finite coverage domain increases; it reduces to zero when the coverage domain has been exhausted.
coverage 1
Test assessment and improvement

27. Saturation Effect: Fault View
Remaining
Faults M
tfs
tfe
tds
tdfe
tme
Functional
Testing Effort
Test assessment and improvement

28. Saturation Effect: Reliability View
R’m
R’d
R’df
R’f
Reliability Rm
Rdf
Mutation Rd
Dataflow Rf
Decision
Functional
tfs
tfe
tds
tde
tdfs
tdfe
tms
tfe
Testing Effort
True reliability (R)
Estimated reliability (R’)
Saturation region
FUNCTIONAL, DECISION, DATAFLOW
AND MUTATION COVERAGE PROVIDE
VARIOUS TEST EVALUATION CRITERIA.
Test assessment and improvement

29. Coverage principle-discussion
How you will use the knowledge of coverage principle and the saturation effect in organizing and managing testing?
Can you think of any other uses of the coverage principle and the saturation effect?
Test assessment and improvement

30. Test assessment and improvement
Control flow graph
Control flow graph (CFG) of a program is a representation of the flow of execution within the program.
It is useful in program analysis such as that required during test assessment and improvement.
More formally, a CFG G is:
Test assessment and improvement

31. Test assessment and improvement
Control flow graph
G=(N,A)
where N: set of nodes and A: set of arcs
There is a unique entry node en in N.
There is a unique exit node ex in N. A node represents a single statement or a block.
A block is a single-entry-single-exit sequence of instructions that are always executed in a sequence without any diversion of path except at the end of the block.
Test assessment and improvement

32. Control flow graph-continued
Every statement in a block, except possibly the first one, has exactly one predecessor.
Similarly, every statement in the block, except possibly the last one, has exactly one successor.
An arc a in A is a pair (n,m) of nodes from N which represent transfer of control from node n to node m.
A path of length k in G is an ordered sequence of arcs, from A such that:
Test assessment and improvement

33. Control flow graph-continued
The first node in is en
The last node in is ex
For any two adjacent arcs = (n,m) and = (p,q), m=p.
A path is considered executable or feasible if there exists a test case which causes this path to be traversed during program execution, otherwise the path is unexecutable or infeasible.
Test assessment and improvement

34. Control flow graph-example
Exercise:
Draw a CFG for the following program and identify all paths.:
1. scanf (x,y); if (y<0)
2. pow=0-y;
3. else pow=y;
4. z=1.0;
5. while (pow !=0)
6. {z=z*x; pow=pow-1;}
7. if (y<0)
8. z=1.0/z;
9. printf(z);
What does the above program compute?
Test assessment and improvement

35. Structure-based test adequacy
Based on the CFG of a program several test adequacy criteria can be defined.
Some are:
statement coverage criterion
branch coverage criterion
condition coverage criterion
path coverage criterion
Test assessment and improvement

36. Test assessment and improvement
Statement coverage
The coverage domain consists of all statements in the program. Restated, in terms of the control flow graph, it is the set of all nodes in G.
A test T satisfies the statement coverage criterion if upon execution of P on each element of T, each statement of P has been executed at least once.
Test assessment and improvement

37. Statement coverage-continued
Restated in terms of G, T is adequate w.r.t. the statement coverage criterion if each node in N is on at least one of the paths traversed when P is executed on each element of T.
Test assessment and improvement

38. Statement coverage-continued
Class exercise:
For the program for which you have drawn the control flow graph, develop a test set that satisfies the statement coverage criterion.
Follow the procedure for test assessment and improvement suggested earlier.
Test assessment and improvement

39. Statement coverage-weakness
Consider the following program:
int abs (x);
int x; {
if (x>=0) x=0-x;
return x; }
Test assessment and improvement

40. Statement coverage-weakness
Suppose that T= {(x=0)}.
Clearly, T satisfies the statement coverage criterion.
But is the program correct and is the error revealed by T which is adequate w.r.t. the statement coverage criterion?
What do you suggest we do to improve T?
Test assessment and improvement

41. Branch (or edge) coverage
In G there may be nodes which correspond to conditions in P. Such nodes, also called condition nodes, contain branches in P.
Each such node is considered covered if during some execution of P, the condition evaluates to true and false; these executions of P need not be the same.
Test assessment and improvement

42. Test assessment and improvement
Branch coverage
The coverage domain consists of all branches in G. Restated, in terms of the control flow graph, it is the set of all arcs exiting the condition nodes.
A test T satisfies the branch coverage criterion if upon execution of P on each element of T, each branch of P has been executed at least once.
Test assessment and improvement

43. Test assessment and improvement
Branch coverage
Class exercise:
Identify all condition nodes in the flow graph you have drawn earlier.
Does T= {(x=0)} satisfy the branch coverage criterion?
If not, then improve it so that it does.
Test assessment and improvement

44. Branch coverage-weakness
Consider the following program that is supposed to check if the input data item is in the range 0 to 100, inclusive:
int check(x);
int x; {
if ((x>=0 )&& (x<=200))
check=true;
else check=false; }
Test assessment and improvement

45. Branch coverage-weakness
Class exercise:
Do you notice the error in this program?
Find a test set T which is adequate w.r.t. statement coverage and does not reveal the error.
Improve T so that it is adequate w.r.t. branch coverage and does not reveal the error.
What do you conclude about the weakness of the branch coverage criterion?
Test assessment and improvement

46. Test assessment and improvement
Condition coverage
Condition nodes in G might have compound conditions.
For example, in the check program the condition node contains the condition:
This is a compound condition which consists of the elementary conditions x>=0 and x<=200.
((x>=0 ) && (x<=200))
Test assessment and improvement

47. Condition coverage-continued
A compound condition is considered covered if all of its constituent elementary conditions evaluate to true and false, respectively, during some execution of P.
A test set T is adequate w.r.t. condition coverage if all conditions in P are covered when P is executed on elements of T.
Test assessment and improvement

48. Condition coverage-continued
Class exercise:
Improve T from the previous exercise so that it is adequate w.r.t. the condition coverage criterion for the check function and does not reveal the error.
Do you find the above possible?
Test assessment and improvement

49. Branch coverage-weakness, continued
Consider the following program:
0. int set_z(x,y); {
1. int x,y;
2. if (x!=0)
3. y=5;
4. else z=z-x;
5. if (z>1)
6. z=z/x;
7. else
8. z=y; }
What might happen here?
Test assessment and improvement

50. Branch coverage-weakness
Class exercise:
Construct T for set_z such that (a) T is adequate w.r.t. the branch coverage criterion and (b) does not reveal the error.
What do you conclude about the effectiveness of the branch and condition coverage criteria?
Test assessment and improvement

51. Test assessment and improvement
Path coverage
As mentioned before, a path through a program is a sequence of statements such that the entry node of the program CFG is the first node on the path and the exit node is the last one on the path.
Is this definition equivalent to the one given earlier?
Test assessment and improvement

52. Path coverage-continued
A test set T is considered adequate w.r.t. the path coverage criterion if all paths in P are executed at least once upon execution on each element of T.
Class exercise:
Construct T for set_z such that T is adequate w.r.t. the path coverage criterion and does not reveal the error.
Is the above possible?
Test assessment and improvement

53. Path coverage-weakness
The number of paths in a program is usually very large.
How many paths in set_z?
How many paths in check?
How many in the program that computes
Test assessment and improvement

54. Path coverage-weaknesses
It is the infinite or a prohibitively large number of paths that prevent the use of this criterion in practice.
Suppose that a test set T covers all paths. Will it guarantee that all errors in P are revealed ?
Is obtaining 100% path coverage equivalent to exhaustive testing?
Test assessment and improvement

55. Variants of path coverage
As path coverage is usually impossible to attain, other heuristics have been proposed.
Loop coverage:
Make sure that each loop is executed 0, 1, and 2 times.
Try several combinations of if and switch statements. The combinations must come from requirements.
Test assessment and improvement

56. Hierarchy in Control flow criteria
Path coverage
Condition coverage
Branch coverage
Statement coverage X Y
X subsumes Y.
Test assessment and improvement

57. Test assessment and improvement
Exercise
Develop a test set T that is adequate w.r.t. the statement, condition, and the loop coverage criteria for the exponentiation program.
Test assessment and improvement

58. Testing technique or strategy
One can develop a testing strategy based on any of the criteria discussed.
Example:
A testing strategy based on the statement coverage criterion will begin by evaluating a test set T against this criterion. Then new tests will be added to T until all the statements are covered, i.e. T satisfies the criterion.
Test assessment and improvement

59. Test assessment and improvement
Definitions
Error-sensitive path: a path whose execution might lead to eventual detection of an error.
Error revealing path: a path whose execution will always cause the program to fail and the error to be detected.
Test assessment and improvement

60. Test assessment and improvement
Definitions
Reliable: A testing technique is reliable for an error if it guarantees that the error will always be detected.
This implies that a reliable testing technique must lead to the exercising of at least one error-revealing path.
Test assessment and improvement

61. Test assessment and improvement
Definitions
Weakly reliable: A testing technique is weakly reliable if it forces the execution of at least one error sensitive path.
Test assessment and improvement

62. Test assessment and improvement
Example: error detection [1] ([1]-[3] not covered during Fall 2001 in CS 406)
Let us go over the example in Korel and Laski’s paper.
It is a sorting program which uses the bubble sort algorithm.
It sorts an array a[0:N] in descending order.
There are two, nested, loops in the program.
The inner loop from i6-i10 finds the largest element of a[R1:N].
Test assessment and improvement

63. Example: error detection[2]
The largest element is saved in R0 and R3 points to the location of R0 in a.
The outer loop swaps a(R1) with a(R3).
The completion of one iteration of the outer loop ensures that the sub-array a[0:R1-1] has been sorted and that a[R1-1] is greater than or equal to any element of a[R1:N].
Test assessment and improvement

64. Example: error detection[3]
There is a missing re-initialization of R3 to R1 at the beginning of the inner loop.
In some cases this will cause the program to fail.
What are these cases?
We will get back to this error later!
Test assessment and improvement

65. Test assessment and improvement
Data flow graph
It represents the flow of data in a program.
The graph is constructed from the control flow graph (CFG) of the program.
A statement that occurs within a node of the CFG might contain variables occurrences.
Each variable occurrence is classified as a def or a use.
Test assessment and improvement

66. Test assessment and improvement
defs and uses
A def represents the definition of a variable. Here are some sample defs of variable x:
x=y*x;
scanf(&x,&y);
int x;
x[i-1]=y*x;
A use represents the use of a variable in a statement. Here a few examples of use of variable x:
All defs of x are italicized.
Test assessment and improvement

67. Test assessment and improvement
def-use-continued
x=x+1;
printf (“x is %d, y is %d”, x,y);
cout << x << endl << y
z=x[i+1]
if (x<y)…
Uses of a variable in input and assignments are classified as c-uses. Those in conditions are classified as p-uses.
All uses of x are italicized.
Test assessment and improvement

68. Test assessment and improvement
def-use-continued
c-use stands for computational use and p-use for predicate-use.
Both c- and p-uses affect the flow of control: p-uses directly as their values are used in evaluating conditions and c-uses indirectly as their values are used to compute other variables which in turn affect the outcome of condition evaluation.
Test assessment and improvement

69. Test assessment and improvement
def-use-continued
A path from node i to node j is said to be def-clear w.r.t. a variable x if there is no def of x in the nodes along the path from node i to node j. Nodes i and j may have a def of x.
A def-clear path from node i to edge (j,k) is one in which no node on the path has a def of x.
Test assessment and improvement

70. Test assessment and improvement
global-def
A def of a variable x is considered global to its block if it is the last def of x within that block.
A c-use of x in a block is considered global c-use if there is no def of x preceding this c-use within this block.
Test assessment and improvement

71. def-use graph: definitions
def(i): set of all variables for which there is a global definition at node i.
c-use(i): set of all variables that have a global c-use at node i.
p-use(i,j): set of all variables for which there is a p-use for the edge (i,j).
dcu(x,i): set of all nodes such that each node has x in its c-use and x is in def(i).
Test assessment and improvement

72. def-use graph: definitions
dpu(x,i): set of all edges such that each edge has x in its p-use , x is in def(i).
The def-use graph of program P is constructed by associating defs, c-use, and p-use sets with nodes of a flow graph.
Test assessment and improvement

73. def-use graph-continued
Sample program:
1. scanf (x,y); if (y<0)
2. pow=0-y;
3. else pow=y;
4. z=1.0;
5. while (pow !=0)
6. {z=z*x; pow=pow-1;}
7. if (y<0)
8. z=1.0/z;
9. printf(z);
Test assessment and improvement

74. def-use graph-continued
Unlabeled edges
imply empty p-use set.
def={x,y}
c-use= 1 y y
def={pow}
c-use={y}
def={pow}
c-use={y} 2 3 4
def={z}
c-use=
def=
c-use= 5
def=
c-use=
pow
pow
def={z,pow}
c-use={z,x,pow} 7 6 y y
def={z}
c-use={z}
def=
c-use={z} 8 9
Test assessment and improvement

75. def-use graph exercise
Draw a def-use graph for the following program.
0. int set_z(x,y); {
1. int x,y;
2. if (x!=0)
3. y=5;
4. else z=z-x;
5. if (z>1)
6. z=z/x;
7. else
8. z=y; }
Test assessment and improvement

76. def-use graph-continued
Traverse the graph to determine dcu and dpu sets.
(node, var) dcu dpu
(1,x) {6} 
(1,y) {2,3} {(1,2),(1,3),(7,8),(7,9)}
(2,pow) {6} {(5,6),(5,7)}
(3,pow) {6} {5,6),(5,7)}
(4,z) {6,8,9} 
(6,z) {6,8,9} 
(6,pow) {6} {(5,6),(5,7)}
(8,z) {9} 
Test assessment and improvement

77. Test assessment and improvement
Test generation
Exercises:
For the above graph generate a test set that satisfies
the branch coverage criterion
the all-defs criterion - for definitions of all variables at least one use (c- or p- use) must be exercised.
the all-uses criterion- all p-uses and all c-uses of all variable definitions be covered.
Develop the tests incrementally, i.e. by modifying the previous test set!
Test assessment and improvement

78. ATAC processing: phase I
P, Program under
test
Preprocess, compile
and instrument
Test set
generate
input
generate
.atac files
Instrumented version of P (executable)
upon execution
upon execution
.trace file
Program output
Test assessment and improvement

79. ATAC processing: phase II
.atac files
.trace file
coverage analyzer
control flow and data flow
coverage values
Test assessment and improvement

80. Test assessment and improvement
Mutation testing
What is mutation testing?
Mutation testing is a code-based test assessment and improvement technique.
It relies on the competent programmer hypothesis which is the following assumption:
Given a specification a programmer develops a program that is either correct or differs from the correct program by a combination of simple errors.
Test assessment and improvement

81. Mutation testing-continued
The process of program development is considered as iterative whereby an initial version of the program is refined by making simple, or a combination of simple changes, towards the final version.
Test assessment and improvement

82. Mutation testing-definitions
Given a program P, a mutant of P is obtained by making a simple change in P.
Program
Mutant
1. int x,y;
2. if (x!=0)
3. y=5;
4. else z=z-x;
5. if (z>1)
6. z=z/x;
7. else
8. z=y;
1. int x,y;
2. if (x!=0)
3. y=5;
4. else z=z-x;
5. if (z>1)
6. z=z/zpush(x);
7. else
8. z=y;
What is zpush?
Test assessment and improvement

83. Test assessment and improvement
Another mutant
Program
Mutant
1. int x,y;
2. if (x!=0)
3. y=5;
4. else z=z-x;
5. if (z>1)
6. z=z/x;
7. else
8. z=y;
1. int x,y;
2. if (x!=0)
3. y=5;
4. else z=z-x;
5. if (z<1)
6. z=z/x;
7. else
8. z=y;
Test assessment and improvement

84. Test assessment and improvement
Mutant
A mutant M is considered distinguished by a test case t T iff:
P(t)M(t)
where P(t) and M(t) denote, respectively, the observed behavior of P and M when executed on test input t.
A mutant M is considered equivalent to P iff:
P(t)M(t) t  T.
Test assessment and improvement

85. Test assessment and improvement
Mutation score
During testing a mutant is considered live if it has not been distinguished or proven equivalent.
Suppose that a total of #M mutants are generated for program P.
The mutation score of a test set T, designed to test P, is computed as:
number of live mutants/(#M-number of equivalent mutants)
Test assessment and improvement

86. Test adequacy criterion
A test T is considered adequate w.r.t. the mutation criterion if its mutation score is 1.
The number of mutants generated depends on P and the mutant operators applied on P.
A mutant operator is a rule that when applied to the program under test generates zero or more mutants.
Test assessment and improvement

87. Test assessment and improvement
Mutant operators
Consider the following program:
int abs (x);
int x; {
if (x>=0) x=0-x;
return x; }
Test assessment and improvement

88. Test assessment and improvement
Mutation operator
Consider the following rule:
Replace each relational operator in P by all possible relational operators excluding the one that is being replaced.
Assuming the set of relational operators to be: {<, >, <=, >=, ==, !=}, the above mutant operator will generate a total of 5 mutants of P.
Test assessment and improvement

89. Test assessment and improvement
Mutation operators
Mutation operators are language dependent.
For Fortran a total of 22 operators were proposed.
For C a total of 77 operators were proposed. None have been proposed for C++ though most of the operators for C are applicable to C++ programs.
Test assessment and improvement

90. Test assessment and improvement
Equivalent mutant
Consider the following program P:
int x,y,z;
scanf(&x,&y);
if (x>0)
x=x+1; z=x*(y-1);
else
x=x-1; z=x*(y-1);
Here z is considered the output of P.
Test assessment and improvement

91. Equivalent mutant-continued
Now suppose that a mutant of P is obtained by changing x=x+1 to x=abs(x)+1.
This mutant is equivalent to P as no test case can distinguish it from P.
Test assessment and improvement

92. Mutation testing procedure
Given P and a test set T:
1. Generate mutants
2. Compile P and the mutants
3. Execute P and the mutants on each test
case.
4. Determine equivalent mutants..
5. Determine mutation score.
6. If mutation score is not 1 then improve
the test set and repeat from step 3.
Test assessment and improvement

93. Mutation testing procedure
In practice the above procedure is implemented incrementally.
One applies a few selected mutant operators to P and computes the mutation score w.r.t. to the mutants generated.
Once these mutants have been distinguished or proven equivalent, another set of mutant operators is applied.
Test assessment and improvement

94. Mutation testing procedure
This procedure is repeated until either all the mutants have been exhausted or some external condition forces testing to stop.
We will not discuss the details of practical application of mutation testing.
Test assessment and improvement

95. Tools for mutation testing
Mothra: for Fortran, developed at Purdue, 1990
Proteum: for C, developed at the University of Saõ Paulo at Saõ Carlos in Brazil.
Test assessment and improvement

96. Uses of Mutation testing
Mutation testing is useful during integration testing to check for integration errors.
Only the variables that are in the interfaces of the components being integrated are mutated. This reduces the complexity of mutation testing.
Test assessment and improvement

97. Test assessment and improvement
Summary
Test adequacy criterion
Test improvement
Coverage principle
Saturation effect
Control flow criteria
Data flow criteria
def, use, p-use, c-use, all-uses
Test assessment and improvement

98. Test assessment and improvement
Summary continued
xSUDS, data flow testing tool.
Mutation testing
mutant, distinguishing a mutant, live mutant, mutant score, competent programmer hypothesis.
Test assessment and improvement