Software Batch Testing to Reduce Build Test Executions

Testing is expensive and batching tests have the potential to reduce test costs. The continuous integration strategy of testing each commit or change individually helps to quickly identify faults but leads to a maximum number of test executions. Large companies that have a large number of commits, e.g. Google and Facebook, or have expensive test infrastructure, e.g. Ericsson, must batch changes together to reduce the number of total test runs. For example, if eight builds are batched together and there is no failure, then we have tested eight builds with one execution saving seven executions. However, when a failure occurs it is not immediately clear which build is the cause of the failure. A bisection is run to isolate the failing build, i.e. the culprit build. In our eight builds example, a failure will require an additional 6 executions, resulting in a saving of one execution. \n \nThe goal of this work is to improve the efficiency of the batch testing. We evaluate six approaches. The first is the baseline approach that tests each build individually. The second, is the existing bisection approach. The third uses a batch size of four, which we show mathematically reduces the number of execution without requiring bisection. The fourth combines the two prior techniques introducing a stopping condition to the bisection. The final two approaches use models \nof build change risk to isolate risky changes and test them in smaller batches. \n \nWe evaluate the approaches on nine open source projects that use Travis CI. Compared to the TestAll baseline, on average, the approaches reduce the number of build test executions across projects by 46%, 48%, 50%, 44%, and 49% for BatchBisect, Batch4, BatchStop4, RiskTopN, and RiskBatch, respectively. The greatest reduction is BatchStop4 at 50%. However, the simple approach of Batch4 does not require bisection and achieves a reduction of 48%. We recommend that \nall CI pipelines use a batch size of at least four. We release our scripts and data for replication. \n \nRegardless of the approach, on average, we save around half the build test executions compared to testing each change individually. We release the BatchBuilder tool that automatically batches submitted changes on GitHub for testing on Travis CI. Since the tool reports individual results for each pull-request or pushed commit, the batching happens in the background and the development process is unchanged.

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