Fuzz testing (fuzzing) has witnessed its prosperity in detecting security flaws recently. It
generates a large number of test cases and monitors the executions for defects. Fuzzing has …

Pre-trained large language models (LLMs) have recently emerged as a breakthrough
technology in natural language processing and artificial intelligence, with the ability to …

The task of generating code solutions for a given programming problem can benefit from the
use of pre-trained language models such as Codex, which can produce multiple diverse …

Search-based software testing (SBST) generates high-coverage test cases for programs
under test with a combination of test case generation and mutation. SBST's performance …

Identifying invariants is an important program analysis task with applications towards
program understanding, bug finding, vulnerability analysis, and formal verification. Existing …

Among the many software testing techniques available today, fuzzing has remained highly
popular due to its conceptual simplicity, its low barrier to deployment, and its vast amount of …

This paper reviews the 2nd NTIRE challenge on single image super-resolution (restoration
of rich details in a low resolution image) with focus on proposed solutions and results. The …

Ethereum smart contracts---autonomous programs that run on a blockchain---often control
transactions of financial and intellectual property. Because of the critical role they play, smart …

This paper defines software fairness and discrimination and develops a testing-based
method for measuring if and how much software discriminates, focusing on causality in …

A good test suite is one that detects real faults. Because the set of faults in a program is
usually unknowable, this definition is not useful to practitioners who are creating test suites …