SUMMARY Maintenance of aging legacy COBOL systems is labor‐intensive and is becoming a more and more difficult problem. Program slicing is a potentially useful analysis for aiding different maintenance activities, including program comprehension, reverse engineering, debugging, and testing. Numerous techniques have been proposed in the past decades; however, in interactive contexts, we found none of them suitable for slicing industrial‐scale COBOL systems due to their large space or preprocessing requirements. This paper proposes a novel static program slicing approach, which is based on context‐sensitive token propagation over control flow graphs (CFGs). CFGs require less space compared with program dependence graphs (PDGs) used by other techniques, and the token propagation method computes the necessary information only, on demand. Algorithms are presented for data flow and full slicing to calculate precise program slices. Preliminary application experiences on industrial‐scale COBOL systems are also summarized. Copyright © 2011 John Wiley & Sons, Ltd.

Abstract A large number of path‐oriented testing criteria have been proposed in the last twenty years. Surprisingly, almost all of them suffer from a serious weakness, which is called the untestedness syndrome: even though a criterion is satisfied, some statements of the program under test may remain ‘untested’, i.e., the observed test output does not depend on them. A new data‐flow based testing criterion is introduced which does not suffer from untestedness, called the All Program Function (APF) criterion. Intuitively, it requires that each possible computation to every output statement in a program be covered by some test; but for lots of programs APF would require an infinite number of tests. A second, applicable criterion is thus introduced, derived from APF and called the Basic Program Function (BPF) criterion. BPF leaves no statement untested and yields finite test suites. Some examples show the application of BPF and investigate the failure‐detection capability of the proposed criterion. Copyright © 2001 John Wiley & Sons, Ltd.

We introduce an improved software regression testing method that determines the test cases that must be rerun to fulfil a given testing criterion. The key part of our method is regression slicing. A regression slice contains the statements whose state may be changed in the modified program with respect to the original for a given test case.

An integrated testing criterion is proposed that extends traditional criteria to be effective to reveal domain errors. The method requires many fewer test cases and is applicable for any kind of predicates. An automated test data generation algorithm is developed to satisfy the criterion. This is the first integrated algorithm that unites path selection and test data generation. The method is based on function minimization and is extended to find required test cases corresponding to ON-OFF points very quickly. In this way the algorithm is dynamic and thus can be used in practice.

No abstract available.

Compiler optimization, parallel processing, data flow testing, and symbolic debugging can benefit from interprocedural data flow analysis. However, the live, reaching definition, and most summary data flow problems are theoretically intractable in the interprocedural case. A method is presented that reduces the exponential time bound with the help of an algorithm that solves the problem in polynomial time. Either the resulting sets contain precise results or the missing (or additional) results do not cause any problems during their use. We also introduce the double iterative framework, where one procedure is processed at a time. The results of the intraprocedural analysis of procedures then propagates along the edges of the call multi-graph. In this way the intra and interprocedural analyses are executed alternately until there is no change in any result set. This method can be applied to any known interprocedural data flow problem. Here the algorithms for the kill, live variables, and reaching definitions problems are presented. Besides for precision, the algorithms can be used for very large programs, and since inter and intraprocedural analyses can be optimized separately, the method is fast as well.