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  1. Systems V & V, Quality and Standards Dr Sita Ramakrishnan School CSSE Monash University

  2. Test Coverage Criteriabased on Data Flow Mechanisms • Topics • Program Structure • Categories of Data Flow Coverage Criteria • Data Flow Testing References: • Peters J F and Pedrycz W,Software Engineering, An Engineering Approach, McGraW Hill, 2000, (Ch.12, Software Testing, pp.437-500) • Horgan J.R., London S., Lyu M.R. Achieving software quality with testing coverage measures. IEEE Computer, Sep. 1994: 60-69 • Other references (books included in the slides, conference & journal papers) given in the handout for the unit © S Ramakrishnan

  3. Program Structure • Program consists of blocks • Block consists of a sequence of statements • When a first statement is executed, the following statements are executed in the given order • Can be represented by a flow graph © S Ramakrishnan

  4. Testing Coverage • Have looked at testing techniques such as: • Black-box testing which includes categories such as: • Syntax-driven driven testing – where specification is described by a certain grammar. -> Generate test cases such that each production rule is applied/tested at least once • Decision-table based testing – may suit if requirements have been written as if-then rules • Cause-effect graphs in functional testing – addresses limitations of decision table where all inputs are treated separately although real world problem demand another approach. Boundary-value analysis & equivalence class partition also assume the independence of input • Structural testing – includes basic categories such as statement, branch & path coverage tests © S Ramakrishnan

  5. Testing Coverage • More on Black-box Testing with Cause-Effect Graphs: • Cause-effect graphs capture relationships between specific combination of inputs (causes) and outputs (effects). • Helps avoid combinatorial explosion associated with decision table approach • Causes and Effects represented as nodes of a cause-effect graph – includes intermediate nodes to link cause & effects in forming logical expressions © S Ramakrishnan

  6. Testing Coverage – Cause-Effect Graphs • Eg. of an ATM transaction system.Causes and Effected listed as: • Causes: C1 : Command is credit, C2: Command is Debit C3: Account No. is valid, C4: Trans. Amount is valid • Effects: E1: Print “invalid command”, E2: “invalid acct no” E3: “debit no. not valid”, E4 & E5: debit & credit a/c respectively or C1 E1 and C2 E2 and C3 E3 and C4 and E4 Cause-effect graph E5 © S Ramakrishnan

  7. Testing Coverage – Cause-Effect Graphs • 4 input (Cause) nodes & 5 output (Effect) nodes • the node in between input (C ) & output (E ) realise “and” or “or” operators • Processing node used in cause-effect graph – and, or, negation, and with processing node, • “and” - effect occurs if all inputs are true • “or” - effect occurs if at least one input is true • “negation” – effect occurs if inputs are false • Cause-Effect graph helps determine the corresponding test cases © S Ramakrishnan

  8. Testing Coverage – Cause-Effect Graphs • Eg. To determine test cases from C-E Graph • Want to find out the causes for E3 say given: C2 C3 C4 C1 C2 C3 C4 X 1 1 0 X= (don’t care condition) 1 = true, 0 = false E3 does not depend on Cause (C1) and E3 © S Ramakrishnan

  9. Test coverage based on Data Flow Coverage Criteria • Why data flow orientation in testing? • Data structures and their usage are essential elements of any code and hence need to be taken into account when looking at software testing • Main categories of data flow coverage criteria • basic block • all-use • c-use • d-use • du-path © S Ramakrishnan

  10. Test coverage based on Data Flow Coverage Criteria In a piece of Java code: Eg sum = 0; Definitions shown in blue prod = 0; i = 1; while (i <= n) { sum+ = i; basic block shown inpurple prod* = i; ->prod* = i an eg of “use” i++ -> i++ also an eg of “use” } if “use” appears in a computational if (k == 0) print_results1; expression, the pair is c-use, if in predicate, resulting pair is p-use if (k == 1) compute; © S Ramakrishnan

  11. Test coverage based on Data Flow Coverage Criteria • Definition – value stored in a memory location • Defined (d) – data structure is defined, created or initialized when it is given a valid state • Use – value fetched from a memory location • C-use – used in computation or output statement & - associated with each node • P-use – used in a predicate& associated with each edge C-uses Decision Basic Block All-uses P-uses Hierarchy of different dataflow coverage criteria © S Ramakrishnan

  12. Test coverage based on Data Flow Coverage Criteria • Def-use Graph • Obtained from the flow graph • Associate with each node the sets • C-use (i) - variables which have global c-uses in block i • Def (i) - variables with global definitions in block i • Associate with each edge (i,j) • P-use (i,j) – variables which have p-uses on edge (i,j) • Define sets of nodes • dpu(x,i) - edges (j,k) such that x Є p-use(j,k) and there is a def-clear path w.r.t. x from i to (j,k) • dcu(x,i) - nodes j such that x Є c-use(j) and there is a def-clear path w.r.t. x from i to j © S Ramakrishnan

  13. Test coverage based on Data Flow Coverage Criteria • Def-use Graph Paths – Definitions • Complete path – path from entry node to exit node • Def-clear path w.r.t. x from node i to node j and from node i to edge nm , j a path (i, n1,n2, …n , j) containing no definitions or undefinitions of x in nodes n1, n2, ….n m m © S Ramakrishnan

  14. Test coverage based on Data Flow Coverage Criteria • Data flow coverage criteria – • The family of data flow testing criteria is based on requiring that – • The test data execute definition-clear paths from each node containing a global definition of a variable to specified nodes containing global c-uses and edge containing p-uses of that variable • For each variable definition, data flow testing criteria require that • All/some definition-clear paths w.r.t. that variable from the node containing the definition to all/some of that uses/c-uses/p-uses reachable by some such paths be executed © S Ramakrishnan

  15. Test coverage based on Data Flow Coverage Criteria • All-def criterion • If variable x has a global definition in node i, the all-defs criterion requires the test data to exercise some path which goes from i to some node or edge at which the value assigned to x in node i is used • All-uses criterion • If variable x has a global definition in node i, the all-uses criterion requires the test data to exercise at least one path which goes from i to each node or edge at which the value assigned to x in node i is used © S Ramakrishnan

  16. Test coverage based on Data Flow Coverage Criteria • All-DU-paths criterion • If variable x has a global definition in node i, the all-DU-paths criterion requires the test data to exercise all paths which go from i to each node and edge at which the value assigned to x in node i is used • Other DF testing criteria • All-p-uses • All-c-uses • All-p-uses/some-c-uses • All-c-uses/some-p-uses © S Ramakrishnan

  17. Test coverage based on Data Flow Coverage Criteria Hierarchy of data flow coverage criteria all-paths all-du-paths all-uses all-c-uses-some-p-uses all-p-uses-some-c-uses all-c-uses all-defs all-p-uses all-edges all-nodes © S Ramakrishnan

  18. Test coverage based on Data Flow Coverage Criteria • Interprocedural Data Flow Testing • Most df testing methods deal with dependencies that exist within a procedure – intra procedural aspect • Data dependencies may also exist between procedures • Requires analysis of flow of data across these procedure/module boundaries © S Ramakrishnan

  19. Test coverage based on Data Flow Coverage Criteria • Homework: Closer look at Table 12.6 Coverage Criteria on P.479 in Peters & Pedrycz text (see slide 1 for Reference details) © S Ramakrishnan