A program slice consists of the parts of a program that (potentially) affect the values computed at some point of interest, referred to as a slicing criterion. The task of computing program slices is called program slicing. The original definition of a program slice was presented by Weiser in 1979. Since then, various slightly different notions of program slices have been proposed, as well as a number of methods to compute them. An important distinction is that between a static and a dynamic slice. The former notion is computed without making assumptions regarding a program's input, whereas the latter relies on some specific test case. Procedures, arbitrary control flow, composite datatypes and pointers, and interprocess communication each require a specific solution. We classify static and dynamic slicing methods for each of these features, and compare their accuracy and efficiency. Moreover, the possibilities for combining solutions for different features are investigated....

Abstract-Regression testing is a necessary but expensive maintenance activity aimed at showing that code has not been adversely affected by changes. Regression test selection techniques reuse tests from an existing test suite to test a modified program. Many regression test selection techniques have been proposed; however, it is difficult to compare and evaluate these techniques because they have different goals. This paper outlines the issues relevant to regression test selection techniques, and uses these issues as the basis for a framework within which to evaluate the techniques. We illustrate the application of our framework by using it to evaluate existing regression test selection techniques. The evaluation reveals the strengths and weaknesses of existing techniques, and highlights some problems that future work in this area should address. Index Terms-Software maintenance, regression testing, selective retest, regression test selection. 1

Regression testing is an expensive but necessary maintenance activity performed on modified software to provide confidence that changes are correct and do not adversely affect other portions of the software. A regression test selection technique chooses, from an existing test set, tests that are deemed necessary to validate modified software. We present a new technique for regression test selection. Our algorithms construct control flow graphs for a procedure or program and its modified version, and use these graphs to select tests that execute changed code from the original test suite. We prove that under certain conditions, the set of tests our technique selects includes every test from the original test suite that can expose faults in the modified procedure or program. Under these conditions our algorithms are safe. Moreover, although our algorithms may select some tests that cannot expose faults, they are at least as precise as other safe regression test selection algorith...

Program slicing is a decomposition technique that elides program components not relevant to a chosen computation, referred to as a slicing criterion. The remaining components form an executable program called a slice that computes a projection of the original program’s semantics. Using examples coupled with fundamental principles, a tutorial introduction to program slicing is presented. Then applications of program slicing are surveyed, ranging from its first use as a debugging technique to current applications in property verification using finite state models. Finally, a summary of research challenges for the slicing community is discussed.

This paper describes how a number of program-analysis problems can be solved by transforming them to graph-reachability problems. Some of the program-analysis problems that are amenable to this treatment include program slicing, certain dataflow-analysis problems, and the problem of approximating the possible "shapes" that heap-allocated structures in a program can take on. Relationships between graph reachability and other approaches to program analysis are described. Some techniques that go beyond pure graph reachability are also discussed.

Regression testing is an expensive testing procedure utilized to validate modified software. Regression test selection techniques attempt to reduce the cost of regression testing by selecting a subset of a program’s existing test suite. Safe regression test selection techniques select subsets that, under certain well-defined conditions, exclude no tests (from the original test suite) that if executed would reveal faults in the modified software. Many regression test selection techniques, including several safe techniques, have been proposed, but few have been subjected to empirical validation. This paper reports empirical studies on a particular safe regression test selection technique, in which the technique is compared to the alternative regression testing strategy of running all tests. The results indicate that safe regression test selection can be cost-effective, but that its costs and benefits vary widely based on a number of factors. In particular, test suite design can significantly affect the effectiveness of test selection, and coverage-based test suites may provide test selection results superior to those provided by test suites that are not coverage-based.

Applying finite-state verification techniques (e.g., model checking) to software requires that program source code be translated to a finite-state transition system that safely models program behavior. Automatically checking such a transition system for a correctness property is typically very costly, thus it is necessary to reduce the size of the transition system as much as possible. In fact, it is often the case that much of a program's source code is irrelevant for verifying a given correctness property. In this paper, we apply program slicing techniques to remove automatically such irrelevant code and thus reduce the size of the corresponding transition system models. We give a simple extension of the classical slicing definition, and prove its safety with respect to model checking of linear temporal logic (LTL) formulae. We discuss how this slicing strategy fits into a general methodology for deriving effective software models using abstraction-based program specializati...

After changes are made to a previously tested program, a goal of regression testing is to perform retesting based on the modifications while maintaining the same testing coverage as completely retesting the program. We present a novel approach to data flow based regression testing that uses slicing algorithms to explicitly detect definition-use associations that are affected by a program change. An important benefit of our slicing technique is that, unlike previous techniques, neither data flow history nor recomputation of data flow for the entire program is required to detect affected definition-use associations. The program changes drive the recomputation of the required partial data flow through slicing. Another advantage is that our technique achieves the same testing coverage with respect to the affected definition-use associations as a complete retest of the program without maintaining a test suite. Thus, the overhead of maintaining and updating a test suite is eliminated. 1. Int...

Program slicing is a fundamental operation for manysoftware engineering tools. Currently,the most efficient algorithm for interprocedural slicing is one that uses a program representation called the system dependence graph. This paper defines a newalgorithm for slicing with system dependence graphs that is asymptotically faster than the previous one. Apreliminary experimental study indicates that the newalgorithm is also significantly faster in practice, providing roughly a 6-fold speedup on examples of 348 to 757 lines. CR Categories and Subject Descriptors: D.2.2 [Software Engineering]: Tools and Techniques - programmer workbench; D.2.6 [SoftwareEngineering]: Programming Environments; D.2.7 [SoftwareEngineering]: Distribution and Maintenance - enhancement, restructuring;E.1 [Data Structures] graphs General Terms: Algorithms, Performance Additional Key Words and Phrases: dynamic programming, dynamic transitive closure, flow-sensitive summary information, program debugging, program ...

This paper reports on the design and implementation of Chianti, a change impact analysis tool for Java that is implemented in the context of the Eclipse environment. Chianti analyzes two versions of an application and decomposes their difference into a set of atomic changes. Change impact is then reported in terms of affected (regression or unit) tests whose execution behavior may have been modified by the applied changes. For each affected test, Chianti also determines a set of affecting changes that were responsible for the test’s modified behavior. This latter step of isolating the changes that induce the failure of one specific test from those changes that only affect other tests can be used as a debugging technique in situations where a test fails unexpectedly after a long editing session. We evaluated Chianti on a year (2002) of CVS data from M. Ernst’s Daikon system, and found that, on average, 52% of Daikon’s unit tests are affected. Furthermore, each affected unit test, on average, is affected by only 3.95 % of the atomic changes. These findings suggest that our change impact analysis is a promising technique for assisting developers with program understanding and debugging.