Software analytics as a learning case in practice: approaches and experiences

  • Authors:

  • Dongmei Zhang;Yingnong Dang;Jian-Guang Lou;Shi Han;Haidong Zhang;Tao Xie

  • Affiliations:

  • Microsoft Research Asia, Beijing, China;Microsoft Research Asia, Beijing, China;Microsoft Research Asia, Beijing, China;Microsoft Research Asia, Beijing, China;Microsoft Research Asia, Beijing, China;North Carolina State University, Raleigh, NC

  • Venue:
  • Proceedings of the International Workshop on Machine Learning Technologies in Software Engineering
  • Year:
  • 2011

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Abstract

Software analytics is to enable software practitioners to perform data exploration and analysis in order to obtain insightful and actionable information for data-driven tasks around software and services. In this position paper, we advocate that when applying analytic technologies in practice of software analytics, one should (1) incorporate a broad spectrum of domain knowledge and expertise, e.g., management, machine learning, large-scale data processing and computing, and information visualization; and (2) investigate how practitioners take actions on the produced information, and provide effective support for such information-based action taking. Our position is based on our experiences of successful technology transfer on software analytics at Microsoft Research Asia.