Parallel Recursive State Compression for Free

This paper focuses on reducing memory usage in enumerative model checking, while maintaining the multi-core scalability obtained in earlier work. We present a tree-based multi-core compression method, which works by leveraging sharing among sub-vectors of state vectors. An algorithmic analysis of both worst-case and optimal compression ratios shows the potential to compress even large states to a small constant on average (8 bytes). Our experiments demonstrate that this holds up in practice: the median compression ratio of 279 measured experiments is within 17% of the optimum for tree compression, and five times better than the median compression ratio of SPIN's COLLAPSE compression. Our algorithms are implemented in the LTSmin tool, and our experiments show that for model checking, multi-core tree compression pays its own way: it comes virtually without overhead compared to the fastest hash table-based methods.Comment: 19 page

Adaptive Forgetting Curves for Spaced Repetition Language Learning

The forgetting curve has been extensively explored by psychologists, educationalists and cognitive scientists alike. In the context of Intelligent Tutoring Systems, modelling the forgetting curve for each user and knowledge component (e.g. vocabulary word) should enable us to develop optimal revision strategies that counteract memory decay and ensure long-term retention. In this study we explore a variety of forgetting curve models incorporating psychological and linguistic features, and we use these models to predict the probability of word recall by learners of English as a second language. We evaluate the impact of the models and their features using data from an online vocabulary teaching platform and find that word complexity is a highly informative feature which may be successfully learned by a neural network model.Cambridge Assessmen

ASAP: An Extensible Platform for State Space Analysis

Abstract. The ASCoVeCo State space Analysis Platform (ASAP) is a tool for performing explicit state space analysis of coloured Petri nets (CPNs) and other formalisms. ASAP supports a wide range of state space reduction techniques and is intended to be easy to extend and to use, making it a suitable tool for students, researchers, and industrial users that would like to analyze protocols and/or experiment with different algorithms. This paper presents ASAP from these two perspectives.

Checking bounded reachability in asynchronous systems by symbolic event tracing

This report presents a new symbolic technique for checking reachability properties of asynchronous systems by reducing the problem to satisfiability in restrained difference logic. The analysis is bounded by fixing a finite set of potential events, each of which may occur at most once in any order. The events are specified using high-level Petri nets. The logic encoding describes the space of possible causal links between events rather than possible sequences of states as in Bounded Model Checking. Independence between events is exploited intrinsically without partial order reductions, and the handling of data is symbolic. On a family of benchmarks, the proposed approach is consistently faster than Bounded Model Checking. In addition, this report presents a compact encoding of the restrained subset of difference logic in propositional logic

Is there a best Büchi automaton for explicit model checking?

LTL to Büchi automata (BA) translators are traditionally optimized to produce automata with a small number of states or a small number of non-deterministic states. In this paper, we search for properties of Büchi automata that really influence the performance of explicit model checkers. We do that by manual analysis of several automata and by experiments with common LTL-to-BA translators and realistic verification tasks. As a result of these experiences, we gain a better insight into the characteristics of automata that work well with Spin.Překladače LTL na Büchiho automaty jsou obvykle optimalizovány tak, aby produkovaly automaty s co nejmenším počtem stavů, či s co nejmenším počtem nedeterministických stavů. V této publikaci hledáme vlastnosti Büchiho automatů, které skutečně ovlivňují výkon nástrojů pro explicitní metodu ověřování modelu (model checking). A to pomocí manuální analýzy několika automatů a experimenty s běžnými překladače LTL na automaty a realistickými verifikačními úlohami. Výsledkem těchto experimentů je lepší porozumění charakteristik automatů, které jsou dobré pro model checker Spin

Simulation Subsumption in Ramsey-Based Büchi Automata Universality and Inclusion Testing

International audienc

Variations on Multi-Core Nested Depth-First Search

Recently, two new parallel algorithms for on-the-fly model checking of LTL properties were presented at the same conference: Automated Technology for Verification and Analysis, 2011. Both approaches extend Swarmed NDFS, which runs several sequential NDFS instances in parallel. While parallel random search already speeds up detection of bugs, the workers must share some global information in order to speed up full verification of correct models. The two algorithms differ considerably in the global information shared between workers, and in the way they synchronize. Here, we provide a thorough experimental comparison between the two algorithms, by measuring the runtime of their implementations on a multi-core machine. Both algorithms were implemented in the same framework of the model checker LTSmin, using similar optimizations, and have been subjected to the full BEEM model database. Because both algorithms have complementary advantages, we constructed an algorithm that combines both ideas. This combination clearly has an improved speedup. We also compare the results with the alternative parallel algorithm for accepting cycle detection OWCTY-MAP. Finally, we study a simple statistical model for input models that do contain accepting cycles. The goal is to distinguish the speedup due to parallel random search from the speedup that can be attributed to clever work sharing schemes.Comment: In Proceedings PDMC 2011, arXiv:1111.006

Advanced Ramsey-Based Büchi Automata Inclusion Testing

International audienceChecking language inclusion between two nondeterministic B ̈ chi au- u tomata A and B is computationally hard (PSPACE-complete). However, several approaches which are efficient in many practical cases have been proposed. We build on one of these, which is known as the Ramsey-based approach. It has recently been shown that the basic Ramsey-based approach can be drastically optimized by using powerful subsumption techniques, which allow one to prune the search-space when looking for counterexamples to inclusion. While previous works only used subsumption based on set inclusion or forward simulation on A and B , we propose the following new techniques: (1) A larger subsumption rela- tion based on a combination of backward and forward simulations on A and B . (2) A method to additionally use forward simulation between A and B . (3) Ab- straction techniques that can speed up the computation and lead to early detection of counterexamples. The new algorithm was implemented and tested on automata derived from real-world model checking benchmarks, and on the Tabakov-Vardi random model, thus showing the usefulness of the proposed techniques