A program slice consists of the parts of a program that (potentially) affect the values computed at some point of interest Such a point of interest is referred to as a slicing criterion, and is typically specified by a location in the program in combination with a subset of the program’s variables 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 Static slices are computed without making assumptions regarding a program’s input, whereas the computation of dynamic slices relies on a specific test case This survey presents an overview of program slicing, including the various general approaches used to compute slices, as well as the specific techniques used to address a variety of language features such as procedures, unstructured control flow, composite data types and pointers, and concurrency Static and dynamic slicing methods for each of these features are compared and classified in terms of their accuracy and efficiency Moreover, the possibilities for combining solutions for different features are investigated Recent work on the use of compiler-optimization and symbolic execution techniques for obtaining more accurate slices is discussed The paper concludes with an overview of the applications of program slicing, which include debugging, program integration, dataflow testing, and software maintenance

/pdf/a-survey-of-program-slicing-techniques-1u546ok1jr.pdf

A Survey of Program Slicing Techniques.

Software vulnerabilities have had a devastating effect on the Internet. Worms such as CodeRed and Slammer can compromise hundreds of thousands of hosts within hours or even minutes, and cause millions of dollars of damage [26, 43]. To successfully combat these fast automatic Internet attacks, we need fast automatic attack detection and filtering mechanisms. In this paper we propose dynamic taint analysis for automatic detection of overwrite attacks, which include most types of exploits. This approach does not need source code or special compilation for the monitored program, and hence works on commodity software. To demonstrate this idea, we have implemented TaintCheck, a mechanism that can perform dynamic taint analysis by performing binary rewriting at run time. We show that TaintCheck reliably detects most types of exploits. We found that TaintCheck produced no false positives for any of the many different programs that we tested. Further, we describe how TaintCheck could improve automatic signature generation in

/pdf/dynamic-taint-analysis-for-automatic-detection-analysis-and-2bodbjb0mi.pdf

Dynamic Taint Analysis for Automatic Detection, Analysis, and Signature Generation of Exploits on Commodity Software

The use of metaheuristic search techniques for the automatic generation of test data has been a burgeoning interest for many researchers in recent years. Previous attempts to automate the test generation process have been limited, having been constrained by the size and complexity of software, and the basic fact that in general, test data generation is an undecidable problem. Metaheuristic search techniques oer much promise in regard to these problems. Metaheuristic search techniques are highlevel frameworks, which utilise heuristics to seek solutions for combinatorial problems at a reasonable computational cost. To date, metaheuristic search techniques have been applied to automate test data generation for structural and functional testing; the testing of grey-box properties, for example safety constraints; and also non-functional properties, such as worst-case execution time. This paper surveys some of the work undertaken in this eld, discussing possible new future directions of research for each of its dieren t individual areas.

https://www.inf.utfsm.cl/~mcriff/Tesistas/Testing/sbs-survey.pdf

Search‐based software test data generation: a survey

Objective measurement of test quality is one of the key issues in software testing. It has been a major research focus for the last two decades. Many test criteria have been proposed and studied for this purpose. Various kinds of rationales have been presented in support of one criterion or another. We survey the research work in this area. The notion of adequacy criteria is examined together with its role in software dynamic testing. A review of criteria classification is followed by a summary of the methods for comparison and assessment of criteria.

/pdf/software-unit-test-coverage-and-adequacy-43qk91tobg.pdf

Software unit test coverage and adequacy

Extensively class tested, this text takes an innovative approach to explaining the process of software testing: it defines testing as the process of applying a few well-defined, general-purpose test criteria to a structure or model of the software. The structure of the text directly reflects the pedagogical approach and incorporates the latest innovations in testing, including techniques to test modern types of software such as OO, web applications, and embedded software.

Introduction to Software Testing: List of Figures

Dynamic program slicing

Dynamic slicing of computer programs

A dynamic program slice is an executable part of the program whose behavior is identical, for the same program input, to that of the original program with respect to a variable(s) of interest at some execution position. It has been shown that dynamic slicing is useful for the purpose of debugging, testing and software maintenance. The existing methods of dynamic slice computation are based on “backward” analysis, i.e., after the execution trace of the program is first recorded, the dynamic slice algorithm traces backwards the execution trace to derive dynamic dependence relations that are then used to compute dynamic slices. For many programs, during their execution extremely high volume of information may be recorded that may prevent accurate dynamic slice computation. In this paper we present a novel approach of dynamic slice computation, referred to as forward approach of dynamic slice computation. In this method, dynamic slices are computed during program execution without major recording of the execution trace. The major advantage of the forward approach is that space complexity is bounded as opposed to the backward methods of slice computation.

Forward computation of dynamic program slices

Test data generation in program testing is the process of identifying a set of test data which satisfies a given testing criterion. Existing pathwise test data generators proceed by selecting program paths that satisfy the selected criterion and then generating program inputs for these paths. One of the problems with this approach is that unfeasible paths are often selected; as a result, significant computational effort can be wasted in analysing those paths. In this paper, an approach to test data generation, referred to as a dynamic approach for test data generation, is presented. In this approach, the path selection stage is eliminated. Test data are derived based on the actual execution of the program under test and function minimization methods. The approach starts by executing a program for an arbitrary program input. During program execution for each executed branch, a search procedure decides whether the execution should continue through the current branch or an alternative branch should be taken. If an undesirable execution flow is observed at the current branch, then a real-valued function is associated with this branch, and function minimization search algorithms are used to locate values of input variables automatically, which will change the flow of execution at this branch.

Dynamic method for software test data generation

Debugging tools offer a rich set of breakpoint and displaying facilities. Those do not involve, however, a means for automatic identification of potentially faulty parts of the programs being debugged. Although that goal might be unrealistic in general, even partial solution to the problem, for a restricted classes of faults, might be useful. Towards that goal the authors present a novel fault localization algorithm that is capable of identifying a restricted class of programming faults for Pascal-like languages. The algorithm uses the following principle for fault localization: if a program component produces an incorrect result, while its input is correct, then the program component is faulty. The algorithm uses the computation trajectory-based influence relations to formulate hypotheses about the nature of the fault. User input is needed to assess correctness of intermediate situations on the trajectory. The set of potentially faulty statements generated by the algorithm is closely related to the concept of dynamic slice (B. Korel et al., 1988). The algorithm has been implemented in the System for Testing and Debugging (B. Korel et al., 1988). Early experiments indicate that the approach can be quite useful, particularly for inexperienced programmers. >

Algorithmic software fault localization

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