Differential symbolic execution

Person, Suzette; Dwyer, Matthew B.; Elbaum, Sebastian; Păsăreanu, Corina S.

doi:10.1145/1453101.1453131

Cited by 216 publications

(197 citation statements)

References 18 publications

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“…For example, the research community has invested a lot of effort in designing techniques for improving the testing of software patches, ranging from test suite prioritisation and selection algorithms [11,30,35] to program analysis techniques for test case generation and bug finding [1,2,20,21,27,28,36,40] to methods for surviving errors introduced by patches at runtime [14]. Many of these techniques depend on the existence of a manual test suite, sometimes requiring the availability of a test exercising the patch [24,37], sometimes making assumptions about the stability of program coverage or external behaviour over time [14,29], other times using it as a starting point for exploration [10,16,22,39], and often times employing it as a baseline for comparison [3,6,9,26].…”

Section: Introductionmentioning

confidence: 99%

Covrig: a framework for the analysis of code, test, and coverage evolution in real software

Marinescu

Hošek

Cadar

2014

Proceedings of the 2014 International Symposium on Software Testing and Analysis

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Software repositories provide rich information about the construction and evolution of software systems. While static data that can be mined directly from version control systems has been extensively studied, dynamic metrics concerning the execution of the software have received much less attention, due to the inherent difficulty of running and monitoring a large number of software versions.In this paper, we present Covrig, a flexible infrastructure that can be used to run each version of a system in isolation and collect static and dynamic software metrics, using a lightweight virtual machine environment that can be deployed on a cluster of local or cloud machines.We use Covrig to conduct an empirical study examining how code and tests co-evolve in six popular open-source systems. We report the main characteristics of software patches, analyse the evolution of program and patch coverage, assess the impact of nondeterminism on the execution of test suites, and investigate whether the coverage of code containing bugs and bug fixes is higher than average.

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Section: Introductionmentioning

confidence: 99%

Covrig: a framework for the analysis of code, test, and coverage evolution in real software

Marinescu

Hošek

Cadar

2014

Proceedings of the 2014 International Symposium on Software Testing and Analysis

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“…There are also approaches that attempt to show equivalence of the original and the upgraded software [14,10,7]. The SymDiff tool [10] decides conditional partial equivalence, i.e., equivalence under certain input constraints.…”

Section: Related Workmentioning

confidence: 99%

“…Moreover, SymDiff also allows automated extraction of the constraints and reports them to the user. The goal of differential symbolic execution [14] is to show equivalence of the two versions using symbolic execution. If the versions are not equivalent, a behavioral delta is constructed as a feedback for the user.…”

Section: Related Workmentioning

confidence: 99%

eVolCheck: Incremental Upgrade Checker for C

Fedyukovich

Šerý

Sharygina

2013

Tools and Algorithms for the Construction and Analysis of Systems

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Software is not created at once. Rather, it grows incrementally version by version and evolves long after being first released. To be practical for software developers, the software verification tools should be able to cope with changes. In this paper, we present a tool, eVolCheck, that focuses on incremental verification of software as it evolves. During the software evolution the tool maintains abstractions of program functions, function summaries, derived using Craig interpolation. In each check, the function summaries are used to localize verification of an upgrade to analysis of the modified functions. Experimental evaluation on a range of various benchmarks shows substantial speedup of incremental upgrade checking of eVolCheck in contrast to checking each version from scratch.

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“…software patches. In particular, differential symbolic execution [23] for using symbolic execution to compute the behavioral characterization of a program change, and discusses several applications, including regression test generation. Xu and Rothermel [30] introduced directed test suite augmentation, in which existing test suites are combined with dynamic symbolic execution to execute uncovered branches in a patch.…”

Section: Related Workmentioning

confidence: 99%

High-Coverage Symbolic Patch Testing

Marinescu

Cadar

2012

Model Checking Software

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Abstract. Software patches are often poorly tested, with many of them containing faults that affect the correct operation of the software. In this paper, we propose an automatic technique based on symbolic execution, that aims to increase the quality of patches by providing developers with an automated mechanism for generating a set of comprehensive test cases covering all or most of the statements in a software patch. Our preliminary evaluation of this technique has shown promising results on several real patches from the lighttpd web server.

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Differential symbolic execution

Cited by 216 publications

References 18 publications

Covrig: a framework for the analysis of code, test, and coverage evolution in real software

Covrig: a framework for the analysis of code, test, and coverage evolution in real software

eVolCheck: Incremental Upgrade Checker for C

High-Coverage Symbolic Patch Testing

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