Abstract Whenever automatic software verifiers determine that a program fulfills or violates its specification, they are expected to produce also a witness that justifies the verdict. This allows a third party to independently validate the verdict and the arguments from which it was derived, increasing trust in the results. The current standard exchange format for witnesses in software verification does not support program termination. To fill this gap, we propose an extension of the witness format that is based on transition invariants as a general and effective formalism. We justify this by (a) proving that transition invariants can encode other popular termination arguments, such as ranking functions, and (b) providing three different validation approaches for transition invariants, which together can validate most of the produced witnesses. Our approach based on transition invariants was integrated into version 2.1 of the exchange format for verification witnesses, our experiments show that the new witnesses can be effectively validated and that validation is often more efficient than verification, and the software-verification community has adopted the format already for SV-COMP 2026.

Abstract SvLibChecker is a small tool for software model checking. Its goal is to provide a light-weight framework that makes it easy to implement and explore algorithms for software verification. The input to SvLibChecker is an SV-LIB program. SV-LIB is an intermediate language that relieves the developers from dealing with sophisticated language features and their semantics. Software verifiers are usually complex software systems with hundreds of thousands of lines of code. Due to the simple input, algorithms in SvLibChecker can be written in a succinct way. SvLibChecker 1.0 provides nine different model-checking algorithms. Each algorithm consists of about 100 lines of Python code. The full project has 3 849LOC in total, which are well-documented and have a good code coverage (> 90 %). The simplicity, lean architecture, and modular design of SvLibChecker lends itself to education. It is much easier to understand the implementation of an algorithm implemented in SvLibChecker , compared to complex verifiers for languages like C. SvLibChecker ’s implementations of the algorithms show performance characteristics similar to CPAchecker , a mature state-of-the-art tool for software verification. The combination of simplicity and performance makes SvLibChecker a suitable tool for verification researchers and educators, for rapidly experimenting with new verification approaches, and for learning and understanding how model-checking algorithms work.

Abstract Software model checking and deductive software verification have complementary strengths and weaknesses: software model checkers are more straight-forward to use, as they analyze the program without user input; but they do not yet support complicated data structures and expressive specifications. In contrast, deductive verifiers can verify expressive specifications and complex data structures modularly, but they require the user to specify the program behavior in detail, which is a time-consuming process. Due to their differing nature, the two approaches usually remain separate. However, for industrial usage, one requires both: ease of use as well as expressiveness. Therefore, we present AutoSV-Annotator , a toolchain that integrates the two approaches for C programs. The toolchain allows a user to iteratively refine the deductive annotations in a C program, calling a model checker to supplement the annotations at each iteration, guided by the already existing annotations. We show that our tool is able to annotate and prove many tasks from the SV-Benchmarks set. Our results show that the two strategies can indeed benefit from each other.

Designing algorithms for complex problems as certifying algorithms is an important approach to ensure correctness of computational results. Instead of producing an output y for an input x, a certifying algorithm produces as output for x not only y but also a witness w. The witness w (also called certificate) can now be used to check that y is indeed the correct output for input x. Witnesses and their validation also exist in the area of automatic software verification, and a large number of tools support verification witnesses. SV-COMP 2025 reports 62 verifiers producing witnesses and 18 tools for witness validation. In 2023, a new version 2.0 of the witness format for software verification was introduced to overcome several problems with the previous format, and this new format is now widely supported. However, there is no format with a clear definition and semantics for witnesses of non-termination. This paper closes this gap by presenting an extension of the witness format 2.0 to support program non-termination. Besides explaining the design of this extension, we describe various approaches to generate and validate non-termination witnesses. We also give an overview of current tool support of the extended format, i.e., the verifiers that can generate non-termination witnesses and the witness validators able to analyze these witnesses. Finally, we present an experimental evaluation showing the performance of these tools on program-termination tasks of SV-COMP 2025.

Abstract Software verification is a complex problem, and verification tools need significant tuning to achieve high performance. Due to this, many verifiers choose to specialize on basic reachability properties. Instead of implementing algorithms for each possible specification, some verifiers implement known transformations from the given specification to reachability on their internal representations. Unfortunately, those internal transformations are not reusable by others. To improve this situation, we propose TransVer , a tool which offers transformations as modular stand-alone component, modifying the input program instead of the internal representation, enabling their usage as a preprocessing step by other verifiers. This way, we separate two concerns: improving the performance of reachability analyses and implementing efficient transformations of arbitrary specifications to reachability. We implement the transformations in a framework that is based on instrumentation automata , inspired by the BLAST query language. In our initial study, we support three important concrete specifications for C programs: termination , no-overflow , and memory cleanup . We conduct experiments with ten different verifiers. The experiments evaluate the efficiency and effectiveness of our transformations. The results are promising: Our transformations can extend existing verifiers to be effective on specifications for which they have no integrated support, and the efficiency is often similar or better to state-of-the-art verifiers that have integrated support for the considered specifications.

Abstract CPAchecker is a tool for software verification, witness validation, and test-case generation, based on the concept of configurable program analysis. One of its main applications is to validate correctness and violation witnesses in versions 1.0 and 2.0. The witness validation is achieved by strengthening a selection of verification algorithms using the information from the witness. Due to the modular approach of CPAchecker, extending its verification analyses for witness validation can be easily done. Similar to CPAchecker ’s verification approach, witness validation uses a selection of analyses dependent on the witness type, the specification, and program features. To validate correctness witnesses, CPAchecker uses k-induction and predicate abstraction to verify that the invariants from the witness hold and the correctness of the program can be proven. To validate violation witnesses, CPAchecker uses predicate abstraction, value analysis, SMGs, and BDDs. CPAchecker ’s many verification algorithms make it a versatile and successful tool for witness validation.

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 .

Identifying and fixing bugs in programs remains a challenge and is one of the most time-consuming tasks in software development. But even after a bug is identified, and a fix has been proposed by a developer or tool, it is not uncommon that the fix is incomplete and does not cover all possible inputs that trigger the bug. This can happen quite often and leads to re-opened issues and inefficiencies. In this paper, we introduce P3, a curated dataset composed of incomplete fixes. Each entry in the set contains a series of commits fixing the same underlying issue, where multiple of the intermediate commits are incomplete fixes. These are sourced from real-world open-source C projects. The selection process involves both automated and manual stages. Initially, we employ heuristics to identify potential partial fixes from repositories, subsequently we validate them through meticulous manual inspection. This process ensures the accuracy and reliability of our curated dataset. We envision that the dataset will support researchers while investigating partial fixes in more detail, allowing them to develop new techniques to detect and fix them. We make our dataset publicly available at https://gitlab.com/sosy-lab/research/data/partial-fix-dataset.

Abstract Verification witnesses are now widely accepted objects used not only to confirm or refute verification results, but also for general exchange of information among various tools for program verification. The original format for witnesses is based on GraphML, and it has some known issues including a semantics based on control-flow automata, limited tool support of some format features, and a large size of witness files. This paper presents version 2.0 of the witness format, which is based on YAML and overcomes the above-mentioned issues. We describe the new format, provide an experimental comparison of various aspects of the original and the new witness format showing that both witness formats perform similarly, and report on its adoption in the community.

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.

Abstraction is an important approach for proving the correctness of computer programs. There are many implementations of this approach available, but unfortunately, the various implementations are difficult to reuse and combine, and the successful techniques have to be re-implemented in new tools again and again. We address this problem by contributing the tool cegar-pt, which views abstraction as program transformation and integrates different verification components off-the-shelf. The idea is to use existing components without having to change their implementation, while still adjusting the precision of the abstraction using the successful CEGAR approach. The approach of cegar-pt is largely general: It only restricts the abstraction to transform, given a precision that defines the level of abstraction, one program into another program. The abstraction by program transformation can over-approximate the data flow (e.g., havoc some variables, use more abstract types) or the control flow (e.g., loop abstraction, slicing). To illustrate our tool, we provide a demonstration video, accessible at https://youtu.be/ASZ6hoq8asE.

Dynamic reconfiguration is one of the key challenges in adaptive systems. As many tasks of adaptive systems are carried out by software and flexible machines, adaptation can be mainly defined by reconfiguration. The Real-Time Container Architecture provides a novel framework for these updates by running distributed embedded software in containers and enabling real-time reconfiguration of these software components following a reconfiguration plan. Yet, it limits I/O access of the containerized software components to GPIO, besides UDP-based communication. We extend the platform with new I/O methods and evaluated the extension with the smart factory showcase system Cube Bot. The extensions enable access to a camera and a robot from within the containers in compliance to the platform concepts. Within the application containers, different languages, state-of-the-art AI technology and the serial interface of the robot can be used. This will show the usefulness of the Real-Time Container Architecture in an even broader industrial context and its capability for extension to other use cases.

Abstract Loop abstraction is a central technique for program analysis, because loops can cause large state-space representations if they are unfolded. In many cases, simple tricks can accelerate the program analysis significantly. There are several successful techniques for loop abstraction, but they are hard-wired into different tools and therefore difficult to compare and experiment with. We present a framework that allows us to implement different loop abstractions in one common environment, where each technique can be freely switched on and off on-the-fly during the analysis. We treat loops as part of the abstract model of the program, and use counterexample-guided abstraction refinement to increase the precision of the analysis by dynamically activating particular techniques for loop abstraction. The framework is independent from the underlying abstract domain of the program analysis, and can therefore be used for several different program analyses. Furthermore, our framework offers a sound transformation of the input program to a modified, more abstract output program, which is unsafe if the input program is unsafe. This allows loop abstraction to be used by other verifiers and our improvements are not ‘locked in’ to our verifier. We implemented several existing approaches and evaluate their effects on the program analysis.

Quadratic unconstrained binary optimization (QUBO) has become the standard format for optimization using quantum computers, i.e., for both the quantum approximate optimization algorithm (QAOA) and quantum annealing (QA). We present a toolkit of methods to transform almost arbitrary problems to QUBO by (i) approximating them as a polynomial and then (ii) translating any polynomial to QUBO. We showcase the usage of our approaches on two example problems (ratio cut and logistic regression).