An orchestrated survey of methodologies for automated software test case generation
An orchestrated survey of methodologies for automated software test case generation
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DOI：
10.1016/j.jss.2013.02.061
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发表时间：
2013-08-01
影响因子：
3.5
通讯作者：
Zhu, Hong
中科院分区：
文献类型：
--
作者：
Anand, Saswat;Burke, Edmund K.;Zhu, Hong
测试案例生成是软件测试中劳动力最密集的任务之一。它对软件测试的有效性和效率也有很大的影响。由于这些原因，数十年来，它一直是软件测试中最活跃的研究主题之一，从而带来了许多不同的方法和工具。本文介绍了对自动生成软件测试用例最突出的技术的精心策划调查，该技术在自动阶段中进行了审查。介绍的技术包括：（a）使用符号执行，（b）基于模型的测试，（c）组合测试，（d）随机测试及其自适应随机测试的变体以及（e）基于搜索的测试的变体。每个部分均由世界知名的积极研究人员就该技术做出了贡献，并简要介绍了方法，当前的艺术状态，对开放研究问题的讨论以及该方法未来发展的观点。总体而言，本文旨在提供自动测试案例生成研究的介绍性，最新和（相对）的简短概述，同时确保全面和权威的治疗方法。 （c）2013 Elsevier Inc.保留所有权利。
Test case generation is among the most labour-intensive tasks in software testing. It also has a strong impact on the effectiveness and efficiency of software testing. For these reasons, it has been one of the most active research topics in software testing for several decades, resulting in many different approaches and tools. This paper presents an orchestrated survey of the most prominent techniques for automatic generation of software test cases, reviewed in self-standing sections. The techniques presented include: (a) structural testing using symbolic execution, (b) model-based testing, (c) combinatorial testing, (d) random testing and its variant of adaptive random testing, and (e) search-based testing. Each section is contributed by world-renowned active researchers on the technique, and briefly covers the basic ideas underlying the method, the current state of the art, a discussion of the open research problems, and a perspective of the future development of the approach. As a whole, the paper aims at giving an introductory, up-to-date and (relatively) short overview of research in automatic test case generation, while ensuring a comprehensive and authoritative treatment. (c) 2013 Elsevier Inc. All rights reserved.