Program analysis can assist software development but its use is limited by a number of usability issues, including false positives and integration issues. Previous systems have show significant progress addressing these by using a data-driven approach to track the 'not useful' results, and integrating the results into code review. However, these systems were very context dependent. In this paper, we motivate the application of the same data-driven principles and code-review based integration to the design of the MEAN system, an analysis infrastructure running on an open tools stack. We then evaluate its implementation within a local software company, and present implications for the design of future program analysis systems.
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