Program synthesis has been long studied with recent approaches focused on directly using
the power of Large Language Models (LLMs) to generate code. Programming benchmarks …

Context: One of the critical phases in the software development life cycle is software testing.
Testing helps with identifying potential bugs and reducing maintenance costs. The goal of …

Automated Program Repair (APR) aims to automatically generate patches for rectifying
software bugs. Recent strides in Large Language Models (LLM), such as ChatGPT, have …

Mutation testing, a mainstream fault-based software testing technique, can mimic a wide
variety of software faults by seeding them into the target program and resulting in the so …

The uninterpretability of DNNs hinders their deployment to safety-critical applications.
Recent works have shown that Abstract-Interpretation-based formal certification techniques …

Context: Deep neural networks (DNN) have been widely deployed in safety-critical domains,
such as autonomous cars and healthcare, where error behaviors can lead to serious …

Concolic execution is a powerful program analysis technique for code path exploration.
Despite recent advances that greatly improved the efficiency of concolic execution engines …

Modern web applications use databases to store their data. When processing user requests,
these applications retrieve and store data in the database server, which incurs network …

Generating test cases is essential for discovering software bugs. However, finding bugs in
multi-path loops is challenging, especially when bugs can only be exposed after a specific …

Symbolic execution is a well-known software testing technique that evaluates how a
program runs when considering a symbolic input, ie, an input that can initially assume any …