A high-level view of Java applications
OOPSLA '03 Companion of the 18th annual ACM SIGPLAN conference on Object-oriented programming, systems, languages, and applications
MSR '05 Proceedings of the 2005 international workshop on Mining software repositories
Automatic Identification of Bug-Introducing Changes
ASE '06 Proceedings of the 21st IEEE/ACM International Conference on Automated Software Engineering
Predicting defects using network analysis on dependency graphs
Proceedings of the 30th international conference on Software engineering
Can developer-module networks predict failures?
Proceedings of the 16th ACM SIGSOFT International Symposium on Foundations of software engineering
Practical change impact analysis based on static program slicing for industrial software systems
Proceedings of the 33rd International Conference on Software Engineering
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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.