基于搜索的压力测试多目标元启发式方法

N. Gois, Pedro Porfírio Muniz de Farias, André L. V. Coelho
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引用次数: 0

摘要

现在的应用程序需要处理大量的并发请求。这些系统必须进行压力测试,以确保它们能够在负载下正常工作。在这种背景下,一个叫做基于搜索的软件测试的研究领域变得越来越重要。大多数基于搜索的测试方法都是基于单目标优化。在测试的多目标优化中,研究者通常对不同的目标赋予不同的权重值,并将它们合并为一个单一的目标。本文验证了多目标算法在基于搜索的压力测试中的应用。NSGA-II算法在IAdapter工具中使用jMetal框架实现。IAdapter是一个JMeter插件,用于执行基于搜索的压力测试。jMetal是一个基于java的面向对象框架,用于使用元启发式进行多目标优化。通过一个实验验证了所提出的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Multi-objective Metaheuristic Approach to Search-Based Stress Testing
Nowadays applications need to deal with a large number of concurrent requests. These systems must be stress tested to ensure that they can function correctly under a load. In this context, a research field called Search-based Software Testing has become increasingly important. Most of the search-based test methods are based on single objective optimization. In the case of multi-objective optimization of tests, usually researchers assign different weight values to different objectives and combine them as a single objective. This research paper verifies the use of a multi-objective algorithm in search-based stress testing. The NSGA-II algorithm was implemented in the IAdapter tool using the jMetal framework. IAdapter is a JMeter plugin used for performing search-based stress tests. jMetal is an object-oriented Java-based framework for multi-objective optimization with metaheuristics. One experiment was conducted to validate the proposed approach.
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