ACM SIGSOFT SEN 实证软件工程：介绍我们的新定期专栏
ACM SIGSOFT SEN Empirical Software Engineering: Introducing Our New Regular Column
AI总结：
本研究介绍一个新专栏，旨在促进实证软件工程领域的讨论，涵盖研究方法、统计方法和跨学科研究等主题，鼓励反思和改进ESE研究。
摘要：
从20世纪70年代初的基础开始，实证软件工程（ESE）已经发展成为一个成熟的学科，涵盖了大量不同的主题、方法论和工业实践。尽管取得了显著进展，ESE研究领域仍然需要不断进化，因为新的障碍、不足和技术不断出现。研究可重复性、外部效度有限、评审的主观性以及将研究成果应用于工业实践都是推动ESE研究改进的因素。此外，ESE研究的某些方面并未被非常明确地记录，这使得新进入者难以掌握。通过这个新的定期ACM SIGSOFT SEN专栏（SEN-ESE），我们介绍了一个讨论ESE研究元方面的场所，从一般的主题如复制包的性质和最佳实践，到更细致的主题如统计方法、访谈转录工具和发表跨学科研究。本专栏的目标是成为定期激发讨论ESE话题的地方，这些话题可能不常被触及或被隐含。对本专栏的贡献将基于专家访谈、焦点小组、调查和立场文章，旨在鼓励我们如何进行、沟通、教学和最终改进ESE研究的反思和改进。最后，我们邀请ESE社区对具有挑战性、争议性或未充分研究的话题以及您希望听到的声音的建议进行反馈。虽然我们不能保证对每个想法做出回应，但我们的目标是围绕社区的兴趣来塑造这个专栏，并感谢所有贡献。
英文摘要：
From its early foundations in the 1970s, empirical software engineering (ESE) has evolved into a mature research discipline that embraces a plethora of different topics, methodologies, and industrial practices. Despite its remarkable progress, the ESE research field still needs to keep evolving, as new impediments, shortcoming, and technologies emerge. Research reproducibility, limited external validity, subjectivity of reviews, and porting research results to industrial practices are just some examples of the drivers for improvements to ESE research. Additionally, several facets of ESE research are not documented very explicitly, which makes it difficult for newcomers to pick them up. With this new regular ACM SIGSOFT SEN column (SEN-ESE), we introduce a venue for discussing meta-aspects of ESE research, ranging from general topics such as the nature and best practices for replication packages, to more nuanced themes such as statistical methods, interview transcription tools, and publishing interdisciplinary research. Our aim for the column is to be a place where we can regularly spark conversations on ESE topics that might not often be touched upon or are left implicit. Contributions to this column will be grounded in expert interviews, focus groups, surveys, and position pieces, with the goal of encouraging reflection and improvement in how we conduct, communicate, teach, and ultimately improve ESE research. Finally, we invite feedback from the ESE community on challenging, controversial, or underexplored topics, as well as suggestions for voices you would like to hear from. While we cannot promise to act on every idea, we aim to shape this column around the community interests and are grateful for all contributions.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
