Automated Program Repair (APR) helps improve the efficiency of software development and
maintenance. Recent APR techniques use deep learning, particularly the encoder-decoder …

Automated program repair is an emerging technology that seeks to automatically rectify
program errors and vulnerabilities. Repair techniques are driven by a correctness criterion …

Automated program repair is an emerging technology which consists of a suite of techniques
to automatically fix bugs or vulnerabilities in programs. In this paper, we present a …

Automated program repair (APR) aims to reduce the effort of software development. With the
development of deep learning, lots of DL-based APR approaches have been proposed …

We consider the problem of establishing that a program-synthesis problem is unrealizable
(ie, has no solution in a given search space of programs). Prior work on unrealizability has …

Interactive program synthesis aims to solve the ambiguity in specifications, and selecting the
proper question to minimize the rounds of interactions is critical to the performance of …

The goal of programmatic Learning from Demonstration (LfD) is to learn a policy in a
programming language that can be used to control a robot's behavior from a set of user …

Automated program repair relying on static analysis complements test-driven repair, since it
does not require failing tests to repair a bug, and it avoids test-overfitting by considering …

Symbolic execution of Android applications is challenging as it involves either building a
customized VM for Android or modeling the Android libraries. Since the Android Runtime …

We consider the problem of automatically establishing that a given syntax-guided-synthesis
(SyGuS) problem is unrealizable (ie, has no solution). We formulate the problem of proving …