Using acceptance tests to predict files changed by programming tasks

Abstract In a collaborative development context, conflicting code changes might compromise software quality and developers productivity. To reduce conflicts, one could avoid the parallel execution of potentially conflicting tasks. Although hopeful, this strategy is challenging because it relies on the prediction of the required file changes to complete a task. As predicting such file changes is hard, we investigate its feasibility for BDD (Behaviour-Driven Development) projects, which write automated acceptance tests before implementing features. We develop a tool that, for a given task, statically analyzes Cucumber tests and infers test-based interfaces (files that could be executed by the tests), approximating files that would be changed by the task. To assess the accuracy of this approximation, we measure precision and recall of test-based interfaces of 513 tasks from 18 Rails projects on GitHub. We also compare such interfaces with randomly defined interfaces, interfaces obtained by textual similarity of test specifications with past tasks, and interfaces computed by executing tests. Our results give evidence that, in the specific context of BDD, Cucumber tests might help to predict files changed by tasks. We find that the better the test coverage, the better the predictive power. A hybrid approach for computing test-based interfaces is promising.