Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Data Mining Techniques: For Marketing, Sales, and Customer Support
Data Mining Techniques: For Marketing, Sales, and Customer Support
Mining Version Histories to Guide Software Changes
Proceedings of the 26th International Conference on Software Engineering
Integrating in-process software defect prediction with association mining to discover defect pattern
Information and Software Technology
The secret life of bugs: Going past the errors and omissions in software repositories
ICSE '09 Proceedings of the 31st International Conference on Software Engineering
Proceedings of the 2010 ACM conference on Computer supported cooperative work
Customized awareness: recommending relevant external change events
Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 1
Summarizing software artifacts: a case study of bug reports
Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 1
Keeping up with your friends: function Foo, library Bar.DLL, and work item 24
Proceedings of the 1st Workshop on Web 2.0 for Software Engineering
CodeTimeline: storytelling with versioning data
Proceedings of the 34th International Conference on Software Engineering
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Software teams record their work progress in task repositories which often require them to encode their activities in a set of edits to field values in a form-based user interface. When others read the tasks, they must decode the schema used to write the activities down. We interviewed four software teams and found out how they used the task repository fields to record their work activities. However, we also found that they had trouble interpreting task revisions that encoded for multiple activities at the same time. To assist engineers in decoding tasks, we developed a scalable method based on frequent pattern mining to identify patterns of frequently co-edited fields that each represent a conceptual work activity. We applied our method to our two years of our interviewee's task repositories and were able to abstract 83,000 field changes into just 27 patterns that cover 95% of the task revisions. We used the 27 patterns to render the teams' tasks in web-based English newsfeeds and evaluated them with the product teams. The team agreed with most of our patterns and English interpretations, but outlined a number of improvements that we will incorporate into future work.