DySy: dynamic symbolic execution for invariant inference

Dynamically discovering likely program invariants from concrete test executions has emerged as a highly promising software engineering technique. Dynamic invariant inference has the advantage of succinctly summarizing both 'expected' program inputs and the subset of program behaviors that...

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Vydané v:International Conference on Software Engineering 2008 Ročník 2008; číslo 24
Hlavní autori: Csallner, Christoph, Tillmann, Nikolai, Smaragdakis, Yannis
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: 01.01.2008
ISBN:1605580791, 9781605580791
ISSN:0270-5257
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Abstract Dynamically discovering likely program invariants from concrete test executions has emerged as a highly promising software engineering technique. Dynamic invariant inference has the advantage of succinctly summarizing both 'expected' program inputs and the subset of program behaviors that is normal under those inputs. In this paper, we introduce a technique that can drastically increase the relevance of inferred invariants, or reduce the size of the test suite required to obtain good invariants. Instead of falsifying invariants produced by pre-set patterns, we determine likely program invariants by combining the concrete execution of actual test cases with a simultaneous symbolic execution of the same tests. The symbolic execution produces abstract conditions over program variables that the concrete tests satisfy during their execution. In this way, we obtain the benefits of dynamic inference tools like Daikon: the inferred invariants correspond to the observed program behaviors. At the same time, however, our inferred invariants are much more suited to the program at hand than Daikon's hard-coded invariant patterns. The symbolic invariants are literally derived from the program text itself, with appropriate value substitutions as dictated by symbolic execution.
AbstractList Dynamically discovering likely program invariants from concrete test executions has emerged as a highly promising software engineering technique. Dynamic invariant inference has the advantage of succinctly summarizing both 'expected' program inputs and the subset of program behaviors that is normal under those inputs. In this paper, we introduce a technique that can drastically increase the relevance of inferred invariants, or reduce the size of the test suite required to obtain good invariants. Instead of falsifying invariants produced by pre-set patterns, we determine likely program invariants by combining the concrete execution of actual test cases with a simultaneous symbolic execution of the same tests. The symbolic execution produces abstract conditions over program variables that the concrete tests satisfy during their execution. In this way, we obtain the benefits of dynamic inference tools like Daikon: the inferred invariants correspond to the observed program behaviors. At the same time, however, our inferred invariants are much more suited to the program at hand than Daikon's hard-coded invariant patterns. The symbolic invariants are literally derived from the program text itself, with appropriate value substitutions as dictated by symbolic execution.
Author Smaragdakis, Yannis
Csallner, Christoph
Tillmann, Nikolai
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