Compilation error repair

Abstract

Compile-time errors pose a major learning hurdle for students of introductory programming courses. Compiler error messages, while accurate, are targeted at seasoned programmers, and seem cryptic to beginners. In this work, we address this problem of pedagogically-inspired program repair and report TRACER (Targeted RepAir of Compilation ERrors), a system for performing repairs on compilation errors, aimed at introductory programmers. TRACER invokes a novel combination of tools from programming language theory and deep learning and offers repairs that not only enable successful compilation, but repairs that are very close to those actually performed by students on similar errors. The ability to offer such targeted corrections, rather than just code that compiles, makes TRACER more relevant in offering real-time feedback to students in lab or tutorial sessions, as compared to existing works that merely offer a certain compilation success rate. In an evaluation on 4500 erroneous C programs written by students of a freshman year programming course, TRACER recommends a repair exactly matching the one expected by the student for 68% of the cases, and in 79.27% of the cases, produces a compilable repair. On a further set of 6971 programs that require errors to be fixed on multiple lines, TRACER enjoyed a success rate of 44% compared to the 27% success rate offered by the state-of-the-art technique DeepFix.