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The inference problem: a survey
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On the difficulty of replicating human subjects studies in software engineering
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Predicting build failures using social network analysis on developer communication
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A few billion lines of code later: using static analysis to find bugs in the real world
Communications of the ACM
The inductive software engineering manifesto: principles for industrial data mining
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Science rests on peer review and the wide-spread dissemination of knowledge. Software engineering research will advance further and faster if the sharing of data and tools were easier and more wide- spread. Pragmatic concerns hinder the realization of this ideal: the time and effort required and the risk of being scooped. We examine the costs and benefits of facilitating sharing in our field in an effort to help the community understand what problems exist and find a solution. We examine how other fields, such as medicine and physics, handle sharing, describe the value of sharing for replication and innovation, and address practical concerns such as standards and warehousing. To launch what we hope will become an ongoing discussion of solutions in our community, we present some ways forward that mitigate the risk of sharing --- partial sharing, registry, escrow, and market.