An empirical study on constraint optimization techniques for test generation

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• 作者：Zhiyi Zhang ; Zhenyu Chen ; Ruizhi Gao ; Eric Wong…
• 关键词：test generation ; symbolic execution ; constraint solving ; constraint optimization ; static metric
• 刊名：SCIENCE CHINA Information Sciences
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：60
• 期：1
• 全文大小：478 KB
• 刊物类别：Computer Science
• 刊物主题：Chinese Library of Science
  Information Systems and Communication Service
  
• 出版者：Science China Press, co-published with Springer
• ISSN：1869-1919
• 卷排序：60

文摘

Constraint solving is a frequent, but expensive operation with symbolic execution to generate tests for a program. To improve the efficiency of test generation using constraint solving, four optimization techniques are usually applied to existing constraint solvers, which are constraint independence, constraint set simplification, constraint caching, and expression rewriting. In this paper, we conducted an empirical study, using these four constraint optimization techniques in a well known test generation tool KLEE with 77 GNU Coreutils applications, to systematically investigate how these optimization techniques affect the efficiency of test generation. The experimental results show that these constraint optimization techniques as well as their combinations cannot improve the efficiency of test generation significantly for ALL-SIZED programs. Moreover, we studied the constraint optimization techniques with respect to two static metrics, lines of code (LOC) and cyclomatic complexity (CC), of programs. The experimental results show that the “constraint set simplification” technique can improve the efficiency of test generation significantly for the programs with high LOC and CC values. The “constraint caching” optimization technique can improve the efficiency of test generation significantly for the programs with low LOC and CC values. Finally, we propose four hybrid optimization strategies and practical guidelines based on different static metrics.