一句话：提出 Pytest-Smell 工具，自动检测 Python 单元测试中的坏味，以改善测试代码与软件质量。
论文关注单元测试代码的质量问题。正如源代码一样，单元测试也可能包含不良编程实践，即缺陷或坏味，它们会降低软件系统的可理解性与可维护性，并增加问题与 bug 出现的风险。为应对这一问题，作者提出 Pytest-Smell，一个面向 Python 单元测试的坏味检测工具，旨在自动化发现此类坏味，从而辅助开发者提升测试代码质量。摘要主要阐述动机与工具目标，未给出具体检测规则、实现技术、实验设计、精度或性能等评估结果，因此无法从摘要判断其实际效果。
Code quality and design are key factors in building a successful software application. It is known that a good internal structure assures a good external quality. To improve code quality, several guidelines and best practices are defined. Along with these, a key contribution is brought by unit testing. Just like the source code, unit test code is subject to bad programming practices, known as defects or smells, that have a negative impact on the quality of the software system. As a consequence, the system becomes harder to understand, maintain, and more prone to issues and bugs. In this respect, methods and tools that automate the detection of the aforementioned unit test smells are of the utmost importance.
DOI 原文 ·
@inproceedings{paperbot7397,
title = {Pytest-Smell: a smell detection tool for Python unit tests},
author = {Alexandru Bodea},
booktitle = {ISSTA},
year = {2022},
doi = {10.1145/3533767.3543290}
}