ControlFlag: A Self-supervised Idiosyncratic Pattern Detection System for Software Control Structures

Software debugging has been shown to utilize upwards of 50% of developers' time. Machine programming, the field concerned with the automation of software (and hardware) development, has recently made progress in both research and production-quality automated debugging systems. In this paper, we present ControlFlag, a system that detects possible idiosyncratic violations in software control structures. ControlFlag also suggests possible corrections in the event a true error is detected. A novelty of ControlFlag is that it is entirely self-supervised; that is, it requires no labels to learn about the potential idiosyncratic programming pattern violations. In addition to presenting ControlFlag's design, we also provide an abbreviated experimental evaluation.