一句话：针对演化软件中组合测试模型与测试计划的维护问题，提出修改、增强、选择的协同演化思路。
软件演化使测试维护困难，测试库容易膨胀并偏离当前版本的最优测试计划。组合测试（CT）通过手工定义组合模型并自动生成测试计划，能以较少测试获得较高覆盖，被视为最佳实践；但其在演化软件中的适用性尚未被充分探索。本文以“修改、增强、选择”为主题，研究组合模型与测试计划的协同演化：随着软件版本变化，模型需要被修改和增强，测试计划需要被选择或调整，以在演化过程中持续获得有效且精简的测试计划。摘要未给出具体算法与实验评估，需阅读正文了解其协同演化机制、工具支持及实证结果。
The evolution of software introduces many challenges to its testing. Considerable test maintenance efforts are dedicated to the adaptation of the tests to the changing software. As a result, over time, the test repository may inflate and drift away from an optimal test plan for the software version at hand. Combinatorial Testing (CT) is a well-known test design technique to achieve a small and effective test plan. It requires a manual definition of the test space in the form of a combinatorial model, and then automatically generates a test plan design, which maximizes the added value of each of the tests. CT is considered a best practice, however its applicability to evolving software is hardly explored.
DOI 原文 ·
@inproceedings{paperbot4613,
title = {Modify, enhance, select: co-evolution of combinatorial models and test plans},
author = {Rachel Tzoref-Brill and Shahar Maoz},
booktitle = {FSE},
year = {2018},
doi = {10.1145/3236024.3236067}
}