There is a growing belief that understanding and addressing the human processes employed during software development is likely to provide substantially more value to industry than yet more recommendations for the implementation of various methods and tools. To this end, considerable research effort has been dedicated to studying human issues as represented in software artifacts, due to its relatively unobtrusive nature. We have followed this line of research and have conducted a preliminary study of team behaviors using data mining techniques and linguistic analysis. Our data source, the IBM Rational Jazz repository, was mined and data from three different project areas were extracted. Communications in these projects were then analyzed using the LIWC linguistic analysis tool. We found that although there are some variations in language use among teams working on project areas dedicated to different software outcomes, project type and the mix of (and number of) individuals involved did not affect team behaviors as evident in their communications. These assessments are initial conjectures, however; we plan further exploratory analysis to validate these results. We explain these findings and discuss their implications for software engineering practice.
翻译:人们日益相信,了解和处理软件开发过程中使用的人类过程可能会给工业带来更大的价值,而不是为采用各种方法和工具提出的更多建议。为此目的,由于软件文物相对不受侵扰的性质,大量研究工作致力于研究软件文物中所体现的人类问题。我们遵循了这一研究路线,对使用数据挖掘技术和语言分析的团队行为进行了初步研究。我们的数据源IBM irynal Jazz储存库被挖掘出来,从三个不同的项目领域提取了数据。然后,利用LIWC语言分析工具对这些项目中的通信进行了分析。我们发现,尽管在项目领域专门从事不同软件结果、项目类型和所涉人员组合(和人数)的小组在语言使用上存在一些差异,但没有影响其通信中显而易见的团队行为。这些评估是初步的推测;但我们计划进一步进行探索性分析,以证实这些结果。我们解释这些结论,并讨论其对软件工程实践的影响。