Page 182 - 《软件学报》2026年第5期

钱忠胜 等: 面向两阶段分组的测试用例优先级排序方法 2061

在 TETC 指标上分别最少提升 96.84%、99.29% 和 84.23%. 可见, 本文方法的设计思路是合理而有意义的.

4 总结与下一步工作

本文提出一种面向两阶段分组的测试用例优先级排序方法 TPG-TCP. 第 1 阶段进行粗粒度测试用例分组, 第
2 阶段进行细粒度测试用例分组排序, 不仅提高了排序的效率, 也提升了有效性.
1) 为减少在覆盖信息和排序处理上的时间消耗, 提出粗粒度用例分组. 利用测试用例间的隐藏关系, 将待测用
例集分为关键用例组与普通用例组, 减少对覆盖信息的冗余访问, 降低排序时间成本, 提高排序效率, 并为下一阶
段采用多样性策略排序做准备.
2) 为同时提高排序效率与有效性, 采用细粒度用例分组排序. 为减少 Additional 策略中随机因素的干扰, 通过
划定迭代次数将关键用例分组, 并提出基于用例潜力度的 TP-Additional 策略对一部分关键用例排序, 同时采用简
单高效的 Total 策略对普通用例与另一部分关键用例排序. 这在提高方法排序效率的同时也提升了有效性.
3) 为验证所提方法效果, 展开综合实验分析. 所提方法 TPG-TCP 无论是与经典方法还是最新方法对比, 在 2
个常用 TCP 指标上均有明显提升. 同时通过消融实验, 验证了方法各构件的必要性.
虽然本文所提方法 TPG-TCP 较优, 但依旧存在一些待完善之处, 其中关键用例组的划分条件较为宽松, 未深
入考虑用例间覆盖信息的相似程度. 在后续研究中, 我们会尝试探索合适的机器学习方法, 试图在捕获用例覆盖信
息相似性的同时, 也能保证方法的高效性.

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