软件开发全球团队中预测任务内聚的通信内容和时间分析

2016 IEEE 11th International Conference on Global Software Engineering Workshops (ICGSEW) Pub Date : 2016-09-29 DOI:10.1109/ICGSEW.2016.24

Alberto Castro-Hernández

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引用次数: 1

摘要

本论文提案描述了基于交互的度量及其在全球软件开发项目中预测内聚性的能力的研究。这些信息是从六个软件开发项目中收集来的，这些项目涉及来自不同国家的学生。这些相互作用的相似性和数量将被计算和分析。测试的措施将在个人和团体层面进行分析。同样，在虚拟学习团队中发现的基于交流类别的内容特征将用于提高任务凝聚力水平的识别。最后，将计算时间交互相似性度量，以评估其在全局设置中的预测能力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Content and Temporal Analysis of Communications to Predict Task Cohesion in Software Development Global Teams

This dissertation proposal describes a study of interaction-based measures and their ability to predict cohesion within global software development projects. Messages were collected from six software development projects that involved students from different countries. The similarities and quantities of such interactions will be computed and analyzed. The tested measures will be analyzed at individual and group level. Similarly, content features based on communication categories, found in virtual learning teams, will be used to improve the identification of task cohesion level. Finally, temporal interaction similarity measures will be calculated to assess its prediction capabilities in a global setting.

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来源期刊

2016 IEEE 11th International Conference on Global Software Engineering Workshops (ICGSEW)

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