Software systems have not only become larger over time, but the amount of technical contributors and dependencies have also increased. With these expansions also comes the increasing risk of introducing a software failure into a pre-existing system. Software failures are a multi-billion dollar problem in the industry today and while integration and other forms of testing are helping to ensure a minimal number of failures, research to understand full impacts of code changes and their social implications is still a major concern. This paper describes how analysis of code changes and the technical relationships they infer can be used to detect pairs of developers whose technical dependencies may induce software failures. These developer pairs may also be used to predict future software failures as well as provide recommendations to contributors to solve these failures caused by source code changes.
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