基于代码覆盖率的测试套件分析和操作的工具集和程序存储库

Dávid Tengeri, Árpád Beszédes, David Havas, T. Gyimóthy
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引用次数: 15

摘要

代码覆盖通常用于学术界和工业界的白盒软件测试实践中。各种测试优化方法,例如测试选择和优先级排序,依赖于代码覆盖信息,但是其他相关领域也从中受益,例如故障定位。这些方法需要访问覆盖信息的精细细节和处理这些数据的有效方法。(免费的)SoDA库和工具集的目的是提供一组有效的数据结构和算法,可用于以各种方式准备、存储和分析与代码覆盖率相关的数据。SoDA的重点不在于覆盖率数据的计算(如仪器和测试执行),而在于基于这些信息的测试套件的分析和操作。该库的一个重要设计目标是可用于工业规模的程序和测试套件。此外,在编程语言、分析粒度和覆盖标准上没有限制。在本文中,我们演示了库的目的和好处,相关的工具集,它还包括一个图形用户界面,以及可能的使用场景。SoDA还包括一个准备好的程序存储库,这些程序大小不等,可以用于实验,也可以作为代码覆盖率相关研究的基准。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Toolset and Program Repository for Code Coverage-Based Test Suite Analysis and Manipulation
Code coverage is often used in academic and industrial practice of white-box software testing. Various test optimization methods, e.g. Test selection and prioritization, rely on code coverage information, but other related fields benefit from it as well, such as fault localization. These methods require access to the fine details of coverage information and efficient ways of processing this data. The purpose of the (free) SoDA library and toolset is to provide an efficient set of data structures and algorithms which can be used to prepare, store and analyze in various ways data related to code coverage. The focus of SoDA is not on the calculation of coverage data (such as instrumentation and test execution) but on the analysis and manipulation of test suites based on such information. An important design goal of the library was to be usable on industrial-size programs and test suites. Furthermore, there is no limitation on programming language, analysis granularity and coverage criteria. In this paper, we demonstrate the purpose and benefits of the library, the associated toolset, which also includes a graphical user interface, as well as possible usage scenarios. SoDA also includes a repository of prepared programs, which are from small to large sizes and can be used for experimentation and as a benchmark for code coverage related research.
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