• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Software >An empirical evaluation of a three-tier conduit framework for multifaceted test case classification and selection using fuzzy-ant colony optimisation approach
【24h】

An empirical evaluation of a three-tier conduit framework for multifaceted test case classification and selection using fuzzy-ant colony optimisation approach

机译：基于多层次测试案例分类和选择的三层管道框架的模糊蚁群优化方法实证评估

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The test case optimisation is an NP-complete, knowledge-driven, data-driven, and multidimensional search space partitioning and dimension reduction problem. In the multifaceted test case classification, partitioning and reducing the multidimensional test case fitness search space is the critical problem. The vague nature of fitness parameters, conflicting nature objectives, and ambiguity in the test case fitness evaluation have created and increased the uncertainty, the imprecision, and the incompleteness in the test case classification and selection. Because of the increasing ambiguity, the complexity, and the cost of software testing, automated test case classification and selection has emerged as an appropriate tool to classify test cases into predefined categories using the multifaceted concept. Most of the test cases affecting the performance of the classifier are irrelevant and redundant. A strong need therefore exists to devise an intelligent technique to identify and remove test cases affecting the performance of the classifier. For increasing the performance of classifier, multifaceted test case selection is used to reduce fitness search space to be searched. In this paper, a three-tier sequential framework is proposed for a multifaceted test case classification and selection. The first stage of the proposed framework is the fuzzy synthesis-based filtration approach for multifaceted test case fitness evaluation and classification. The second stage of the proposed framework is the fuzzy entropy-based filtration technique with a backward search strategy, used for estimating and reducing the ambiguity in test case fitness evaluation, classification, and selection. The third stage of the proposed framework is the ant colony optimisation-based wrapper technique with a forward search strategy, employed to select test cases from the output (reduced) test suite by the second stage. The proposed framework is tested on artefacts of benchmark applications. The results of the empirical study clearly show that the third stage of our proposed method outperforms the second and first stages, and the performance of the algorithms used in all three stages increases on average as the stages are escalating. The classification accuracy is enhanced by reducing the ambiguity in fitness and the classification of test cases, increasing the number of test cases accurately classified, and reducing the number in the test case pool to be exercised. Copyright (c) 2014 John Wiley & Sons, Ltd.
机译：测试用例优化是一个NP完全，知识驱动，数据驱动以及多维搜索空间划分和降维问题。在多维测试用例分类中，划分和减少多维测试用例适应性搜索空间是关键问题。适应度参数的模糊性质，冲突的自然目标以及测试用例适应性评估中的歧义性造成并增加了测试用例分类和选择的不确定性，不精确性和不完整性。由于歧义性的增加，软件测试的复杂性和成本的增加，自动测试用例的分类和选择已成为一种使用多面概念将测试用例分类为预定义类别的合适工具。影响分类器性能的大多数测试用例都是无关紧要的。因此，强烈需要设计一种智能技术来识别和删除影响分类器性能的测试用例。为了提高分类器的性能，使用了多方面的测试用例选择来减少要搜索的适应性搜索空间。本文提出了一种三层顺序框架，用于多方面的测试案例分类和选择。所提出框架的第一阶段是用于多方面测试用例适应性评估和分类的基于模糊综合的过滤方法。所提出框架的第二阶段是基于模糊熵的过滤技术，其具有向后搜索策略，用于估计和减少测试用例适应性评估，分类和选择中的歧义。拟议框架的第三阶段是基于蚁群优化的包装技术，该技术具有正向搜索策略，第二阶段用于从输出（精简）测试套件中选择测试案例。所提出的框架已在基准应用程序的伪像上进行了测试。实证研究的结果清楚地表明，我们提出的方法的第三阶段优于第二阶段和第一阶段，并且随着这三个阶段的逐步升级，所有这三个阶段使用的算法的性能平均都会提高。通过降低适应度的歧义性和测试用例的分类，增加准确分类的测试用例的数量，并减少要执行的测试用例池的数量，可以提高分类的准确性。版权所有（c）2014 John Wiley＆Sons，Ltd.

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号