Diagnostic messages generated by compilers and interpreters such as syntax error
messages have been researched for over half of a century. Unfortunately, these messages …

Researchers have recently achieved significant advances in deep learning techniques,
which in turn has substantially advanced other research disciplines, such as natural …

A key part of learning to program is learning to understand programming error messages.
They can be hard to interpret and identifying the cause of errors can be time-consuming …

Automated program repair (APR) aims to fix software bugs automatically and plays a crucial
role in software development and maintenance. With the recent advances in deep learning …

Most programmers make mistakes when writing code. Some of these mistakes are small and
require few edits to the original program–a class of errors recently termed last mile mistakes …

In this paper, we address the problem of automatic repair of software vulnerabilities with
deep learning. The major problem with data-driven vulnerability repair is that the few …

This paper presents a novel end-to-end approach to program repair based on sequence-to-
sequence learning. We devise, implement, and evaluate a technique, called SequenceR, for …

We consider repair tasks: given a critic (eg, compiler) that assesses the quality of an input,
the goal is to train a fixer that converts a bad example (eg, code with syntax errors) into a …

We consider the problem of learning to repair programs from diagnostic feedback (eg,
compiler error messages). Program repair is challenging for two reasons: First, it requires …

Software debugging, and program repair are among the most time-consuming and labor-
intensive tasks in software engineering that would benefit a lot from automation. In this …