A software developer works on many tasks per day, frequently switching between these tasks back and forth. This constant churn of tasks makes it difficult for a developer to know the specifics of when they worked on what task, complicating task resumption, planning, retrospection, and reporting activities. We introduce a new approach to help identify the topic of work for a given time interval that is based on capturing the contents of the developer’s active window at regular intervals and creating a vector representation of key information the developer viewed. To evaluate our approach, we created a data set with multiple developers working on the same set of six information seeking tasks that we also make available for other researchers to investigate similar approaches. Our analysis shows that our approach enables: 1) segments of a developer’s work to be automatically associated with a task from a known set of tasks with average accuracy of 70.6%, and 2) a visual representation describing a segment of work that a developer can use to recognize a task with average accuracy of 67.9%.
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|Identifying and Describing Information Seeking Tasks|
|Predicting Code Context Models for Software Development Tasks|
Zhiyuan Wan Zhejiang University, Gail Murphy University of British Columbia, Xin Xia Monash UniversityPre-print
|Edge4Real: A Cost-Effective Edge Computing based Human Behaviour Recognition System for Human-Centric Software Engineering|
DI SHAO School of Information Technology, Deakin University, Xiao Liu School of Information Technology, Deakin University, Ben Cheng School of Information Technology, Deakin University, Yi Wang School of Information Technology, Deakin University, Thuong Hoang School of Information Technology, Deakin University