Putting It All Together: Using Socio-technical Networks to Predict Failures

Studies have shown that social factors in development organizations have adramatic effect on software quality. Separately, program dependencyinformation has also been used successfully to predict which software componentsare more fault prone. Interestingly, the influence of these two phenomena haveonly been studied separately. Intuition and practical experience suggests,however, that task assignment (i.e. who worked on which components and howmuch) and dependency structure (which components have dependencies on others)together interact to influence the quality of the resulting software. Westudy the influence of combined socio-technical software networks onthe fault-proneness of individual software components within a system. Thenetwork properties of a software component in this combined network are ableto predict if an entity is failure prone with greater accuracy than priormethods which use dependency or contribution information in isolation. Weevaluate our approach in different settings by using it on Windows Vista andacross six releases of the Eclipse development environment including usingmodels built from one release to predict failure prone components in the nextrelease. We compare this to previous work. In every case, our method performsas well or better and is able to more accurately identify those softwarecomponents that have more post-release failures, with precision and recallrates as high as 85%.

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