Unfair behaviors of Machine Learning (ML) software have garnered increasing attention and
concern among software engineers. To tackle this issue, extensive research has been …

Uniform or near-uniform generation of solutions for large satisfiability formulas is a problem
of theoretical and practical interest for the testing community. Recent works proposed two …

Toward verified artificial intelligence Page 1 46 COMMUNICATIONS OF THE ACM | JULY
2022 | VOL. 65 | NO. 7 contributed articles ILL US TRA TION B Y PETER CRO W THER A …

Almost every software system provides configuration options to tailor the system to the target
platform and application scenario. Often, this configurability renders the analysis of every …

Many analyses on configurable software systems are intractable when confronted with
colossal and highly-constrained configuration spaces. These analyses could instead use …

Probabilistic inference via model counting has emerged as a scalable technique with strong
formal guarantees, thanks to recent advances in hashing-based approximate counting. State …

Given a Boolean formula, the problem of counting seeks to estimate the number of solutions
of F while the problem of uniform sampling seeks to sample solutions uniformly at random …

In software and hardware testing, generating multiple inputs which satisfy a given set of
constraints is an important problem with applications in fuzz testing and stimulus generation …

Numerous software systems are highly configurable and provide a myriad of configuration
options that users can tune to fit their functional and performance requirements (eg …

Analyses of Software Product Lines (SPLs) rely on automated solvers to navigate complex
dependencies among features and find legal configurations. Often these analyses do not …