Abstract This tutorial provides an introduction toCPAcheckerfor users.CPAcheckeris a flexible and configurable framework for software verification and testing. The framework provides many abstract domains, such as BDDs, explicit values, intervals, memory graphs, and predicates, and many program-analysis and model-checking algorithms, such as abstract interpretation, bounded model checking,Impact, interpolation-based model checking,k-induction, PDR, predicate abstraction, and symbolic execution. This tutorial presents basic use cases forCPAcheckerin formal software verification, focusing on its main verification techniques with their strengths and weaknesses. An extended version also shows further use cases ofCPAcheckerfor test-case generation and witness-based result validation. The envisioned readers are assumed to possess a background in automatic formal verification and program analysis, but prior knowledge ofCPAcheckeris not required. This tutorial and user guide is based onCPAcheckerin version 3.0. This user guide’s latest version and other documentation are available at https://cpachecker.sosy-lab.org/doc.php .

Abstract CPAcheckeris a versatile framework for software verification, rooted in the established concept ofconfigurable program analysis. Compared to the last published system description at SV-COMP 2015, theCPAcheckersubmission to SV-COMP 2024 incorporates new analyses for reachability safety, memory safety, termination, overflows, and data races. To combine forces of the available analyses inCPAcheckerand cover the full spectrum of the diverse program characteristics and specifications in the competition, we usestrategy selectionto predict a sequential portfolio of analyses that is suitable for a given verification task. The prediction is guided by a set of carefully picked program features. The sequential portfolios are composed based on expert knowledge and consist of bit-precise analyses usingk-induction, data-flow analysis, SMT solving, Craig interpolation, lazy abstraction, and block-abstraction memoization. The synergy of various algorithms inCPAcheckerenables support for all properties and categories of C programs in SV-COMP 2024 and contributes to its success in many categories.CPAcheckeralso generates verification witnesses in the new YAML format.

Abstract Satisfiability Modulo Theories (SMT) is an enabling technology with many applications, especially in computer-aided verification. Due to advances in research and strong demand for solvers, there are many SMT solvers available. Since different implementations have different strengths, it is often desirable to be able to substitute one solver by another. Unfortunately, the solvers have vastly different APIs and it is not easy to switch to a different solver (lock-in effect). To tackle this problem, we developed JavaSMT, which is a solver-independent framework that unifies the API for using a set of SMT solvers. This paper describes version 3 of JavaSMT, which now supports eight SMT solvers and offers a simpler build and update process. Our feature comparisons and experiments show that different SMT solvers significantly differ in terms of feature support and performance characteristics. A unifying Java API for SMT solvers is important to make the SMT technology accessible for software developers. Similar APIs exist for other programming languages.