静态测试中基于遗传算法的测试用例场景优先排序方法

2011 2nd International Conference on Computer and Communication Technology (ICCCT-2011) Pub Date : 2011-11-10 DOI:10.1109/ICCCT.2011.6075160

Sangeeta Sabharwal, R. Sibal, Chayanika Sharma

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引用次数: 27

摘要

白盒测试是一种考虑程序代码、代码结构和内部设计流程的测试技术。白盒测试主要有两种——静态测试和结构测试。静态测试只需要产品的源代码，而不需要二进制文件或可执行文件，而在结构测试中，测试实际上是由计算机在构建的产品上运行的。本文提出了一种利用遗传算法识别关键路径簇来优化静态测试效率的方法。通过对测试数据应用遗传算法优化测试效率。测试用例场景来源于源代码。本文采用信息流度量来计算由源代码生成的控制流图的每个节点所关联的信息流复杂度。这篇研究论文是我们之前的研究论文[18]的延伸。

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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A genetic algorithm based approach for prioritization of test case scenarios in static testing

White box testing is a test technique that takes into account program code, code structure and internal design flow. White box testing is primarily of two kinds-static and structural. Whereas static testing requires only the source code of the product, not the binaries or executables, in structural testing tests are actually run by the computer on built products. In this paper, we propose a technique for optimizing static testing efficiency by identifying the critical path clusters using genetic algorithm. The testing efficiency is optimized by applying the genetic algorithm on the test data. The test case scenarios are derived from the source code. The information flow metric is adopted in this work for calculating the information flow complexity associated with each node of the control flow graph generated from the source code. This research paper is an extension of our previous research paper [18].

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来源期刊

2011 2nd International Conference on Computer and Communication Technology (ICCCT-2011)

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