Scaling regression testing to large software systems

A. Orso, N. Shi, M. J. Harrold
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引用次数: 261

Abstract

When software is modified, during development and maintenance, it is regression tested to provide confidence that the changes did not introduce unexpected errors and that new features behave as expected. One important problem in regression testing is how to select a subset of test cases, from the test suite used for the original version of the software, when testing a modified version of the software. Regression-test-selection techniques address this problem. Safe regression-test-selection techniques select every test case in the test suite that may behave differently in the original and modified versions of the software. Among existing safe regression testing techniques, efficient techniques are often too imprecise and achieve little savings in testing effort, whereas precise techniques are too expensive when used on large systems. This paper presents a new regression-test-selection technique for Java programs that is safe, precise, and yet scales to large systems. It also presents a tool that implements the technique and studies performed on a set of subjects ranging from 70 to over 500 KLOC. The studies show that our technique can efficiently reduce the regression testing effort and, thus, achieve considerable savings.
将回归测试扩展到大型软件系统
当软件在开发和维护期间被修改时,将对其进行回归测试,以确保更改没有引入意外错误,并且新特性的行为符合预期。回归测试中的一个重要问题是,当测试软件的修改版本时,如何从用于软件原始版本的测试套件中选择测试用例的子集。回归测试选择技术解决了这个问题。安全回归测试选择技术选择测试套件中的每个测试用例,这些测试用例在软件的原始版本和修改版本中可能表现不同。在现有的安全回归测试技术中,高效的技术通常过于不精确,并且在测试工作中节省的工作量很少,而精确的技术在大型系统上使用时过于昂贵。本文提出了一种新的Java程序回归测试选择技术,该技术安全、精确,并且可扩展到大型系统。它还提供了一个工具,该工具实现了对一组从70到500多KLOC的主题进行的技术和研究。研究表明,我们的技术可以有效地减少回归测试的工作量,从而实现可观的节省。
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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