An empirical study of Linespots: A novel past-fault algorithm
This is an incremental improvement for software developers and engineers needing more accurate fault prediction tools.
The paper tackles fault prediction in software by proposing Linespots, a novel algorithm based on Bugspots, and finds that it consistently improves predictive performance over Bugspots across all seven evaluation metrics.
This paper proposes the novel past-faults fault prediction algorithm Linespots, based on the Bugspots algorithm. We analyze the predictive performance and runtime of Linespots compared to Bugspots with an empirical study using the most significant self-built dataset as of now, including high-quality samples for validation. As a novelty in fault prediction, we use Bayesian data analysis and Directed Acyclic Graphs to model the effects. We found consistent improvements in the predictive performance of Linespots over Bugspots for all seven evaluation metrics. We conclude that Linespots should be used over Bugspots in all cases where no real-time performance is necessary.