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The pervasive adoption of Continuous Integration practices -- both inindustry and open source projects -- has led software building to become adaily activity for thousands of developers around the world. Companies such asMicrosoft have invested in in-house infrastructures with the goal of optimizingthe build process. CloudBuild, a distributed and caching build servicedeveloped internally by Microsoft, runs the build process in parallel in thecloud and relies on caching to accelerate builds. This allows for agiledevelopment and rapid delivery of software even several times a day. However,moving towards faster builds requires not only improvements on theinfrastructure side, but also attention to developers' changes in the software.Surely, architectural decisions and software changes, such as addition ofdependencies, can lead to significant build time increase. Yet, estimating theimpact of such changes on build time can be challenging when dealing withcomplex, distributed, and cached build systems. In this paper, we envision apredictive model able to preemptively alert developers on the extent to whichtheir software changes may impact future building activities. In particular, wedescribe an approach that analyzes the developer's change and predicts (i)whether it impacts (any of) the Longest Critical Path; (ii) may lead to buildtime increase and its delta; and (iii) the percentage of future builds thatmight be affected by such change.

Towards Predicting the Impact of Software Changes on Building Activities