PredSym:为一个没有bug的版本估算软件测试预算

Proceedings of the 7th International Workshop on Automating Test Case Design, Selection, and Evaluation Pub Date : 2016-11-18 DOI:10.1145/2994291.2994294

Arnamoy Bhattacharyya, Timur Malgazhdarov

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引用次数: 3

摘要

符号执行工具在软件测试阶段被广泛用于发现隐藏的错误和软件漏洞。准确地预测符号执行工具探索选定的代码覆盖率所需的时间，有助于规划测试阶段所需的预算。在这项工作中，我们提出了一个自动工具PredSym，它使用静态程序特征来预测符号执行工具(KLEE)在给定时间预算下探索的覆盖范围，并预测探索给定覆盖范围所需的时间。PredSym使用LASSO回归来建立一个模型，该模型不会受到过拟合的影响，并且可以在未见过的数据点上以10%的最大误差预测覆盖率和时间。PredSym还提供了基于启发式方法的代码改进建议，以改进由KLEE生成的覆盖率。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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PredSym: estimating software testing budget for a bug-free release

Symbolic execution tools are widely used during a software testing phase for finding hidden bugs and software vulnerabilities. Accurately predicting the time required by a symbolic execution tool to explore a chosen code coverage helps in planning the budget required in the testing phase. In this work, we present an automatic tool, PredSym, that uses static program features to predict the coverage explored by a symbolic execution tool - KLEE, for a given time budget and to predict the time required to explore a given coverage. PredSym uses LASSO regression to build a model that does not suffer from overfitting and can predict both the coverage and the time with a worst error of 10% on unseen datapoints. PredSym also gives code improvement suggestions based on a heuristic for improving the coverage generated by KLEE.

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Proceedings of the 7th International Workshop on Automating Test Case Design, Selection, and Evaluation

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