Multi-core on-the-fly SCC decomposition

Bloemen, Vincent; Laarman, Alfons; Pol, Jaco van de

doi:10.1145/2851141.2851161

Cited by 21 publications

(33 citation statements)

References 55 publications

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“…The results of ESF, EWF, PWF and PSF checking is shown in Table III. We can see that our approach for fairness checking can gain significant speedup for most models 3 . The performance improvement is more visible when the state space consists of a lot of SCCs and the average SCC size is large.…”

Section: B Performance Of On-the-fly Parallel Fairness Verificationmentioning

confidence: 85%

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Concurrent On-the-Fly SCC Detection for Automata-Based Model Checking with Fairness Assumption

Günay

et al. 2016

2016 21st International Conference on Engineering of Complex Computer Systems (ICECCS)

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Abstract-Model checking is an automated technique for verifying temporal logic properties of finite state systems. Tarjan's algorithm for detecting Strongly Connected Components (SCCs) is a widely used depth-first search procedure for Automatabased (LTL) model checking. It works on the SCC detection on-the-fly with the composition of transition systems and Büchi Automaton (state space generation), which has been deployed as sequential implementations in many tools. However, these implementations suffer from heavy time cost for systems which involve a large number of SCC explorations. To address this issue, in this paper, we develop a concurrent SCC detection approach for the on-the-fly generated state space in LTL model checking by expanding the existing concurrent Tarjan's algorithm. Besides, we involve fairness checking. Different that the previous work, which performs fairness checking after the generation of a complete SCC, in our approach we perform fairness checking during SCC generation to improve efficiency. We implement our approach in PAT model checker. Our experimental results show that our approach achieves up to 2X speedup for the complete SCC detection in large-scale system models compared to the sequential on-the-fly model checking in PAT. Besides, our parallel on-the-fly fairness checking approach speedups fairness checking around 2X∼45X.

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Section: B Performance Of On-the-fly Parallel Fairness Verificationmentioning

confidence: 85%

“…It builds a state space exploration algorithm based on the shared memory multicore architecture. [3] presents a novel emptiness checking approach for LTL model checking, which is based on SCC enumeration and support TGBA. Its key feature it the usage of a global union-find data structure.…”

Section: Related Workmentioning

confidence: 99%

Concurrent On-the-Fly SCC Detection for Automata-Based Model Checking with Fairness Assumption

Günay

et al. 2016

2016 21st International Conference on Engineering of Complex Computer Systems (ICECCS)

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“…As it is presented, UPDATE Dijkstra calls unite only when a potential root is discovered not to be a root (lines [10][11][12][13][14]. In the particular case where a closing edge does not invalidate any potential root, no unite operation is performed; still, the acceptance marks on this closing edge are updated locally (line 15).…”

Section: The Dijkstra Strategymentioning

confidence: 99%

“…× cndfs [21] O(P × |T |) × × Lowe [28] O(|T | 2 ) × Bloemen [10,11] O(P × |T | × |Q|) × this paper Sections 3-4 O(P × |T | × α(|Q|))…”

Section: Algorithm Referencementioning

confidence: 99%

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Variations on parallel explicit emptiness checks for generalized Büchi automata

Renault

Duret-Lutz

Kordon

et al. 2016

Int J Softw Tools Technol Transfer

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We present new parallel explicit emptiness checks for LTL model checking. Unlike existing parallel emptiness checks, these are based on a Strongly Connected Component (SCC) enumeration, support generalized Büchi acceptance, and require no synchronization points nor recomputing procedures. A salient feature of our algorithms is the use of a global unionfind data structure in which multiple threads share structural information about the automaton checked.Besides these basic algorithms, we present one architectural variant isolating threads that write to the union-find, and one extension that decomposes the automaton based on the strength of its SCCs to use more optimized emptiness checks.The results from an extensive experimentation of our algorithms and their variations show encouraging performances, especially when the decomposition technique is used.

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Automated Verification of Parallel Nested DFS

Oortwijn

Huisman

Joosten

et al. 2020

Tools and Algorithms for the Construction and Analysis of Systems

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Model checking algorithms are typically complex graph algorithms, whose correctness is crucial for the usability of a model checker. However, establishing the correctness of such algorithms can be challenging and is often done manually. Mechanising the verification process is crucially important, because model checking algorithms are often parallelised for efficiency reasons, which makes them even more error-prone. This paper shows how the VerCors concurrency verifier is used to mechanically verify the parallel nested depth-first search (NDFS) graph algorithm of Laarman et al. [25]. We also demonstrate how having a mechanised proof supports the easy verification of various optimisations of parallel NDFS. As far as we are aware, this is the first automated deductive verification of a multi-core model checking algorithm. This research has been performed while working at the University of Twente.

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Multi-core on-the-fly SCC decomposition

Cited by 21 publications

References 55 publications

Concurrent On-the-Fly SCC Detection for Automata-Based Model Checking with Fairness Assumption

Concurrent On-the-Fly SCC Detection for Automata-Based Model Checking with Fairness Assumption

Variations on parallel explicit emptiness checks for generalized Büchi automata

Automated Verification of Parallel Nested DFS

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