Implementing and evaluating candidate-based invariant generation

The discovery of inductive invariants lies at the heart of static program verification. Presently, many automatic solutions to inductive invariant generation are inflexible, only applicable to certain classes of programs, or unpredictable. An automatic technique that circumvents these deficiencies to some extent is candidate-based invariant generation , whereby a large number of candidate invariants are guessed and then proven to be inductive or rejected using a sound program analyser. This paper describes our efforts to apply candidate-based invariant generation in GPUVerify, a static checker of programs that run on GPUs. We study a set of 383 GPU programs that contain loops, drawn from a number of open source suites and vendor SDKs. Among this set, 253 benchmarks require provision of loop invariants for verification to succeed. We describe the methodology we used to incrementally improve the invariant generation capabilities of GPUVerify to handle these benchmarks, through candidate-based invariant generation , whereby potential program invariants are speculated using cheap static analysis and subsequently either refuted or proven. We also describe a set of experiments that we used to examine the effectiveness of our rules for candidate generation, assessing rules based on their generality (the extent to which they generate candidate invariants), hit rate (the extent to which the generated candidates hold), effectiveness (the extent to which provable candidates actually help in allowing verification to succeed), and influence (the extent to which the success of one generation rule depends on candidates generated by another rule). We believe that our methodology for devising and evaluation candidate generation rules may serve as a useful framework for other researchers interested in candidate-based invariant generation. The candidates produced by GPUVerify help to verify 231 of these 253 programs. An increase in precision, however, has created sluggishness in GPUVerify because more candidates are generated and hence more time is spent on computing those which are inductive invariants. To speed up this process, we have investigated four under-approximating program analyses that aim to reject false candidates quickly and a framework whereby these analyses can run in sequence or in parallel. Across two platforms, running Windows and Linux, our results show that the best combination of these techniques running sequentially speeds up invariant generation across our benchmarks by 1 . 17 × (Windows) and 1 . 01 × (Linux), with per-benchmark best speedups of 93 . 58 × (Windows) and 48 . 34 × (Linux), and worst slowdowns of 10 . 24 × (Windows) and 43 . 31 × (Linux). We find that parallelising the strategies marginally improves overall invariant generation speedups to 1 . 27 × (Windows) and 1 . 11 × (Linux), maintains good best-case speedups of 91 . 18 × (Windows) and 44 . 60 × (Linux), and, importantly, dramatically reduces worst-case slowdowns to 3 . 15 × (Windows) and 3 . 17 × (Linux)

Tools and Algorithms for the Construction and Analysis of Systems

This open access book constitutes the proceedings of the 28th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2022, which was held during April 2-7, 2022, in Munich, Germany, as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2022. The 46 full papers and 4 short papers presented in this volume were carefully reviewed and selected from 159 submissions. The proceedings also contain 16 tool papers of the affiliated competition SV-Comp and 1 paper consisting of the competition report. TACAS is a forum for researchers, developers, and users interested in rigorously based tools and algorithms for the construction and analysis of systems. The conference aims to bridge the gaps between different communities with this common interest and to support them in their quest to improve the utility, reliability, exibility, and efficiency of tools and algorithms for building computer-controlled systems

Tools and Algorithms for the Construction and Analysis of Systems

This open access book constitutes the proceedings of the 28th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2022, which was held during April 2-7, 2022, in Munich, Germany, as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2022. The 46 full papers and 4 short papers presented in this volume were carefully reviewed and selected from 159 submissions. The proceedings also contain 16 tool papers of the affiliated competition SV-Comp and 1 paper consisting of the competition report. TACAS is a forum for researchers, developers, and users interested in rigorously based tools and algorithms for the construction and analysis of systems. The conference aims to bridge the gaps between different communities with this common interest and to support them in their quest to improve the utility, reliability, exibility, and efficiency of tools and algorithms for building computer-controlled systems

Tools and Algorithms for the Construction and Analysis of Systems

This open access two-volume set constitutes the proceedings of the 27th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2021, which was held during March 27 – April 1, 2021, as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2021. The conference was planned to take place in Luxembourg and changed to an online format due to the COVID-19 pandemic. The total of 41 full papers presented in the proceedings was carefully reviewed and selected from 141 submissions. The volume also contains 7 tool papers; 6 Tool Demo papers, 9 SV-Comp Competition Papers. The papers are organized in topical sections as follows: Part I: Game Theory; SMT Verification; Probabilities; Timed Systems; Neural Networks; Analysis of Network Communication. Part II: Verification Techniques (not SMT); Case Studies; Proof Generation/Validation; Tool Papers; Tool Demo Papers; SV-Comp Tool Competition Papers

High-Performance and Power-Aware Graph Processing on GPUs

Graphs are a common representation in many problem domains, including engineering, finance, medicine, and scientific applications. Different problems map to very large graphs, often involving millions of vertices. Even though very efficient sequential implementations of graph algorithms exist, they become impractical when applied on such actual very large graphs. On the other hand, graphics processing units (GPUs) have become widespread architectures as they provide massive parallelism at low cost. Parallel execution on GPUs may achieve speedup up to three orders of magnitude with respect to the sequential counterparts. Nevertheless, accelerating efficient and optimized sequential algorithms and porting (i.e., parallelizing) their implementation to such many-core architectures is a very challenging task. The task is made even harder since energy and power consumption are becoming constraints in addition, or in same case as an alternative, to performance. This work aims at developing a platform that provides (I) a library of parallel, efficient, and tunable implementations of the most important graph algorithms for GPUs, and (II) an advanced profiling model to analyze both performance and power consumption of the algorithm implementations. The platform goal is twofold. Through the library, it aims at saving developing effort in the parallelization task through a primitive-based approach. Through the profiling framework, it aims at customizing such primitives by considering both the architectural details and the target efficiency metrics (i.e., performance or power)

Formal methods for functional verification of cache-coherent systems-on-chip

State-of-the-art System-on-Chip (SoC) architectures integrate many different components, such as processors, accelerators, memories, and I/O blocks. Some of those components, but not all, may have caches. Because the effort of validation with simulation-based techniques, currently used in industry, grows exponentially with the complexity of the SoC, this thesis investigates the use of formal verification techniques in this context. More precisely, we use the CADP toolbox to develop and validate a generic formal model of a heterogeneous cache-coherent SoC compliant with the recent AMBA 4 ACE specification proposed by ARM. We use a constraint-oriented specification style to model the general requirements of the specification. We verify system properties on both the constrained and unconstrained model to detect the cache coherency corner cases. We take advantage of the parametrization of the proposed model to produce a comprehensive set of counterexamples of non-satisfied properties in the unconstrained model. The results of formal verification are then used to improve the industrial simulation-based verification techniques in two aspects. On the one hand, we suggest using the formal model to assess the sanity of an interface verification unit. On the other hand, in order to generate clever semi-directed test cases from temporal logic properties, we propose a two-step approach. One step consists in generating system-level abstract test cases using model-based testing tools of the CADP toolbox. The other step consists in refining those tests into interface-level concrete test cases that can be executed at RTL level with a commercial Coverage-Directed Test Generation tool. We found that our approach helps in the transition between interface-level and system-level verification, facilitates the validation of system-level properties, and enables early detection of bugs in both the SoC and the commercial test-bench.Les architectures des systèmes sur puce (System-on-Chip, SoC) actuelles intègrent de nombreux composants différents tels que les processeurs, les accélérateurs, les mémoires et les blocs d'entrée/sortie, certains pouvant contenir des caches. Vu que l'effort de validation basée sur la simulation, actuellement utilisée dans l'industrie, croît de façon exponentielle avec la complexité des SoCs, nous nous intéressons à des techniques de vérification formelle. Nous utilisons la boîte à outils CADP pour développer et valider un modèle formel d'un SoC générique conforme à la spécification AMBA 4 ACE récemment proposée par ARM dans le but de mettre en œuvre la cohérence de cache au niveau système. Nous utilisons une spécification orientée contraintes pour modéliser les exigences générales de cette spécification. Les propriétés du système sont vérifié à la fois sur le modèle avec contraintes et le modèle sans contraintes pour détecter les cas intéressants pour la cohérence de cache. La paramétrisation du modèle proposé a permis de produire l'ensemble complet des contre-exemples qui ne satisfont pas une certaine propriété dans le modèle non contraint. Notre approche améliore les techniques industrielles de vérification basées sur la simulation en deux aspects. D'une part, nous suggérons l'utilisation du modèle formel pour évaluer la bonne construction d'une unité de vérification d'interface. D'autre part, dans l'objectif de générer des cas de test semi-dirigés intelligents à partir des propriétés de logique temporelle, nous proposons une approche en deux étapes. La première étape consiste à générer des cas de tests abstraits au niveau système en utilisant des outils de test basé sur modèle de la boîte à outils CADP. La seconde étape consiste à affiner ces tests en cas de tests concrets au niveau de l'interface qui peuvent être exécutés en RTL grâce aux services d'un outil commercial de génération de tests dirigés par les mesures de couverture. Nous avons constaté que notre approche participe dans la transition entre la vérification du niveau interface, classiquement pratiquée dans l'industrie du matériel, et la vérification au niveau système. Notre approche facilite aussi la validation des propriétés globales du système, et permet une détection précoce des bugs, tant dans le SoC que dans les bancs de test commerciales

Computer Aided Verification

This open access two-volume set LNCS 11561 and 11562 constitutes the refereed proceedings of the 31st International Conference on Computer Aided Verification, CAV 2019, held in New York City, USA, in July 2019. The 52 full papers presented together with 13 tool papers and 2 case studies, were carefully reviewed and selected from 258 submissions. The papers were organized in the following topical sections: Part I: automata and timed systems; security and hyperproperties; synthesis; model checking; cyber-physical systems and machine learning; probabilistic systems, runtime techniques; dynamical, hybrid, and reactive systems; Part II: logics, decision procedures; and solvers; numerical programs; verification; distributed systems and networks; verification and invariants; and concurrency