Shrikanth N. C.

Shrikanth N. C., Tim Menzies

It can be insightful to extend qualitative studies with a secondary quantitative analysis (where the former suggests insightful questions that the latter can answer). Documenting developer beliefs should be the start, not the end, of Software Engineering research. Once prevalent beliefs are found, they should be checked against real-world data. For example, this paper finds several notable discrepancies between empirical evidence and the developer beliefs documented in Wan et al.'s recent TSE paper "Perceptions, expectations, and challenges in defect prediction". By reporting these discrepancies we can stop developers (a) wasting time on inconsequential matters or (b) ignoring important effects. For the future, we would encourage more "extension studies" of prior qualitative results with quantitative empirical evidence.

Anurag Dwarakanath, Shrikanth N. C., Kumar Abhinav et al.

In this paper we study the trustworthiness of the crowd for crowdsourced software development. Through the study of literature from various domains, we present the risks that impact the trustworthiness in an enterprise context. We survey known techniques to mitigate these risks. We also analyze key metrics from multiple years of empirical data of actual crowdsourced software development tasks from two leading vendors. We present the metrics around untrustworthy behavior and the performance of certain mitigation techniques. Our study and results can serve as guidelines for crowdsourced enterprise software development.