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Logic Coverage in Software Integrating PDF-417 2d barcode in Software Logic Coverage




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Logic Coverage generate, create barcode pdf417 none with software projects GS1 DataBar bar codes GACC is satis ed but pred PDF-417 2d barcode for None icate coverage is not, when the predicates are very small (one or two terms), but dif cult with three or more terms, since for one of the clauses, it is likely that the chosen GACC tests will also be CACC tests. The restrictive nature of RACC, on the other hand, can sometimes make it hard to satisfy the criterion. This is particularly true when some combinations of clause values are infeasible.

Assume that in the predicate used above, the semantics of the program effectively eliminate rows 2, 3, and 6 from the truth table. Then RACC cannot be satis ed with respect to clause list.contains(str) (that is, we have infeasible test requirements), but CACC can.

The wise reader, (that is, if still awake) will by now realize that Correlated Active Clause Coverage is often the most practical avor of ACC.. EXERCISES Section 3.2. Use predicates (1) throug Software PDF417 h (10) to answer the following questions. 1. 2.

3. 4. 5.

6. 7. 8.

9. 10. p = a ( b c) p = a (b c) p=a b p = a (b c) p=a b p = a (b c) p = (a b) (c d) p = ( a b) (a c) ( a c) p = a b (c d) p = (a b) (b c) (a c) (a) Identify the clauses that go with predicate p.

(b) Compute (and simplify) the conditions under which each of the clauses determines predicate p. (c) Write the complete truth table for all clauses. Label your rows starting from 1.

Use the format in the example underneath the de nition of combinatorial coverage in Section 3.2. That is, row 1 should be all clauses true.

You should include columns for the conditions under which each clause determines the predicate, and also a column for the predicate itself. (d) Identify all pairs of rows from your table that satisfy general active clause coverage (GACC) with respect to each clause. (e) Identify all pairs of rows from your table that satisfy correlated active clause coverage (CACC) with respect to each clause.

(f) Identify all pairs of rows from your table that satisfy restricted active clause coverage (RACC) with respect to each clause. (g) Identify all 4-tuples of rows from your table that satisfy general inactive clause coverage (GICC) with respect to each clause. Identify any infeasible GICC test requirements.

(h) Identify all 4-tuples of rows from your table that satisfy restricted inactive clause coverage (RICC) with respect to each clause. Identify any infeasible RICC test requirements..

Coverage Criteria 11. Re ne the GACC, CACC, PDF417 for None RACC, GICC, and RICC coverage criteria so that the constraints on the minor clauses are made more formal. 12.

(Challenging!) Find a predicate and a set of additional constraints so that CACC is infeasible with respect to some clause, but GACC is feasible.. 3.3 STRUCTURAL LOGIC COVERAGE OF PROGRAMS As with graph coverage cr Software PDF-417 2d barcode iteria, the logic coverage criteria apply to programs in a straightforward way. Predicates are derived directly from decision points in the programs (if, case, and loop statements). Although these criteria are dif cult to apply when predicates have a large number of clauses, this is often not a problem with programs.

The vast majority of predicates in programs have only one clause, and programmers tend to write predicates with a maximum of two or three clauses. It should be clear that when a predicate only has one clause, all of the logic coverage criteria collapse into the same criterion predicate coverage. The primary complexity of applying logic coverage to programs has more to do with reachability than with the criteria.

That is, a logic coverage criterion imposes test requirements that are related to speci c decision points (statements) in the program. Getting values that satisfy those requirements is only part of the problem; getting to the statement is sometimes more dif cult. Two issues are associated with getting there.

The rst is simply that of reachability from 1; the test case must include values to reach the statement. In small programs (that is, most methods) this problem is not hard, but when applied within the context of an entire arbitrarily large program, satisfying reachability can be enormously complex. The values that satisfy reachability are pre x values in the test case.

The other part of getting there can be even harder. The test requirements are expressed in terms of program variables that may be de ned locally to the unit or even the statement block being tested. Our test cases, on the other hand, can include values only for inputs to the program that we are testing.

Therefore these internal variables have to be resolved to be in terms of the input variables. Although the values for the variables in the test requirements should ultimately be a function of the values of the input variables, this relationship may be arbitrarily complex. In fact, this internal variable problem is formally undecidable.

Consider an internal variable X that is derived from a table lookup, where the index to the table is determined by a complex function whose inputs are program inputs. To choose a particular value for X, the tester has to work backward from the statement where the decision appears, to the table where X was chosen, to the function, and nally to an input that would cause the function to compute the desired value. If the function includes randomness or is time sensitive, or if the input cannot be controlled by the tester, it may be impossible to satisfy the test requirement with certainty.

This controllability problem has been explored in depth in the automatic test data generation literature and will not be discussed in detail here, except to note that this problem is a major reason why the use of program-level logic coverage criteria is usually limited to unit and module testing activities. The example program in Figures 3.2 and 3.

3 is used to illustrate logic coverage on programs.2 The program is a simple triangle classi cation program called TriTyp. This program (or more accurately, the algorithm) has been used as an example in.

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