增强GUI测试案例生成与多目标准对立遗传子
1Department of Computer Applications, PSNA College of Engineering and Technology, Dindigul, 624622, India. jayalakshmi908765@gmail.com.
Scientific reports
|December 5, 2025
概括
本研究介绍了准对立性遗传搜索算法 (OOGSSA),用于高效的图形用户界面 (GUI) 测试案例生成. OOGSSA增强了测试覆盖范围和故障检测,提高了软件的可靠性.
科学领域:
- 软件工程 软件工程 软件工程
- 人工智能的人工智能
- 计算智能是一种计算智能.
背景情况:
- 确保图形用户界面 (GUI) 质量对于强大且易于使用的软件至关重要.
- 传统的自动化测试方法往往在复杂的GUI交互和实现全面覆盖方面扎.
研究的目的:
- 通过使用先进的优化算法,提出一种新的,高效的GUI测试案例生成方法.
- 通过最大限度地提高测试覆盖范围,最大限度地减少冗余,并改进故障检测能力来增强GUI测试.
主要方法:
- 开发了近对立的遗传子搜索算法 (OOGSSA),这是对子搜索算法的增强.
- 集成基于精英反对派的学习和遗传进化,以促进人口多样性和融合速度.
- 自动检查GUI事件交互和适应性学习,以改进测试套件.
主要成果:
- 实验评估表明,高老鼠事件覆盖率 (95%) 测试套件大小为75.
- 在测试案例生成中,获得了高相似度得分 (雅卡德指数:0.75-0.82) 和低不相似度得分 (迪斯杰罗温克勒:0.18-0.31).
- 与传统的自动化和动态测试生成工具相比,OOGSSA表现出卓越的适应性和智能.
结论:
- OOGSSA为GUI测试提供了可扩展和智能化的方法,显著提高了软件的可靠性和效率.
- 该方法有效地解决了GUI测试生成中的多目标优化目标.
- 对高度复杂的GUI的潜在计算成本是一个考虑因素,但总的来说,OOGSSA提供了显著的进步.
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