Abstract
Code completion is a widely used productivity tool. It takes away the burden of remembering and typing the exact names of methods or classes: As a developer starts typing a name, it provides a progressively refined list of candidates matching the name. However, the candidate list usually comes in alphabetic order, i.e., the environment is only second-guessing the name based on pattern matching, relying on human intervention to pick the correct one. Finding the correct candidate can thus be cumbersome or slower than typing the full name.
We present an approach to improve code completion based on recorded program histories. We define a benchmarking procedure measuring the accuracy of a code completion engine and apply it to several completion algorithms on a dataset consisting of the history of several systems. Further, we use the change history data to improve the results offered by code completion tools. Finally, we propose an alternative interface for completion tools that we released to developers and evaluated.