The recent extensive availability of "big data" platforms calls for a widespread adoption by the formal verification community. Cloud computing platforms represent a great opportunity to run massively parallel jobs, yet classical formal verification tools techniques must undergo a deep technological transformation in order to exploit the new available architectures. This has raised an increasing interest in deploying verification techniques on parallel distributed frameworks. In this paper we introduce a framework to ease the adoption of a distributed approach to verification of Computation Tree Logic (CTL) formulas on very large state spaces. The approach exploits integrates a recently developed, parametric state-space builder. The whole framework adopts M AP R EDUCE as core computational model, and can be tailored to different modelling formalisms. The outcomes of several tests performed on (Petri-nets based) benchmark specifications are presented, thus showing the convenience of the proposed approach.
@cite_29 @cite_1 @cite_17 @cite_32 @cite_0 discuss parallel distributed verification of (LTL) formulas. They aim at increasing the memory available and reducing the overall time required by LTL formulas verification by employing distributed techniques for searching accepting cycles in B "ichi automata. Distributed and parallel model checking of CTL logic was also proposed. @cite_18 introduced a CTL model checking technique which works by splitting the given state space into several partial state spaces''. Each computer involved in the distributed computation owns a partial state space and performs a model checking algorithm on this incomplete structure. To be able to proceed, the border states are augmented by assumptions about truth values of formulas and the computers exchange assumptions about relevant states to compute more precise information. Other approaches were introduced in @cite_27 @cite_13 .
@cite_18 @cite_29 @cite_1 @cite_32 @cite_0 @cite_27 @cite_13 @cite_17
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In this paper we discuss the problem of performing distributed CTL model checking by splitting the given state space into several "partial state spaces." The partial state space is modelled as a Kripke structure with border states. Each computer involved in the distributed computation owns a partial state space and performs a model-checking algorithm on this incomplete structure. To be able to proceed, the border states are augmented by assumptions about truth values of formulas and the computers exchange assumptions about relevant states to compute more precise information. In this paper, we propose a distributed algorithm for CTL model-checking and a counterexample search whenever the CTL formula is not satisfied. The distributed approach is used in order to cope with the state space explosion problem. A cluster of workstations performs collaborative verification over a partitioned state space. Thus, every process involved in the distributed verification performs the labelling procedure on its own partial state space, and uses the parse tree of the CTL formula to evaluate sub-formulas and delay the synchronisations so as to minimise idle time. A counterexample search consists in a distributed construction of the tree-like corresponding to the failure executions. Some experiments have been carried out to evaluate the efficiency of this approach. In modular verification the specification of a module consists of two parts. One hart describes the guaranteed behavior of the module. The other part describes the assumed behavior of the system iii which the module is interacting. This is called the assume-guarantee paradigm. In this paper we consider assume-guarantee specifications in which the guarantee is specified by branching temporal formulas. We distinguish between two approaches. In the first approach, the assumption is specified by branching temporal formulas. In the second approach, the assumption is specified by linear temporal logic. We consider guarantees in CTL and CTL * , the universal fragments of CTL and CTL * , and assumptions in LTL. CTL, and CTL * . We describe a reduction of modular model checking to standard model checking. Using the reduction, we show that modular model checking is PSPACE-complete for CTL and is EXPSPACE-complete for CTL * . We then show that the case of LTL assumption is a special case of the case of CTL * assumption, but that the EXPSPACE-hardness result apply already to assumptions in LTL. Abstract Documents in computer-readable form can be used to provide information about other documents, i.e. those they cite. To do this efficiently requires procedures for computer recognition of citing statements. This is not easy, especially for multi-sentence citing statements. Computer recognition procedures have been developed which are accurate to the following extent: 73 of the words in statements selected by computer procedures as being citing statements are words which are correctly attributable to the corresponding documents. The retrieval effectiveness of computer-recognized citing statements was tested in the following way. First, for eight retrieval requests in inorganiic chemistry, average recall by search of Chemical Abstracts Service indexing and Chemical Abstracts abstract text words was found to be 50 . Words from citing statements referring to the papers to be retrieved were then added to the index terms and abstract words as additional access points, and searching was repeated. Average recall increased to 70 . Only words from citing statements published within a year of the cited papers were used. The retrieval effect of citing statement words alone (published within a year) without index or abstract terms was the following: average recall was 40 . When just the words of the titles of the cited papers were added to those citing statement words, average recall increased to 50 . A citing sentence is one that appears in a scientific article and cites previous work. Citing sentences have been studied and used in many applications. For example, they have been used in scientific paper summarization, automatic survey generation, paraphrase identification, and citation function classification. Citing sentences that cite multiple papers are common in scientific writing. This observation should be taken into consideration when using citing sentences in applications. For instance, when a citing sentence is used in a summary of a scientific paper, only the fragments of the sentence that are relevant to the summarized paper should be included in the summary. In this paper, we present and compare three different approaches for identifying the fragments of a citing sentence that are related to a given target reference. Our methods are: word classification, sequence labeling, and segment classification. Our experiments show that segment classification achieves the best results. Model checking became a standard method of analyzing complex systems in many application domains. No doubt, a number of applications is placing great demands on model checking tools. The process of analysis of complex and real-life systems often requires vast computation resources, memory in particular. This phenomenon, referred to as the state space explosion problem, has been tackled by many researchers during the past two decades. A plethora of more or less successful techniques to fight the problem have been introduced, including parallel and distributed-memory processing. DiVinE is a tool for LTL model checking and reach ability analysis of discrete distributed systems. The tool is able to efficiently exploit the aggregate computing power of multiple network-interconnected multi-cored workstations in order to deal with extremely large verification tasks. As such it allows to analyze systems whose size is far beyond the size of systems that can be handled with regular sequential tools. While the main focus of the tool is on high-performance explicit state model checking, an emphasis is also put on ease of deployment and usage. Additionally, the component architecture and publicly available source code of Divine allow for its usage as a platform for research on parallel and distributed-memory model checking techniques. Regular model checking is a form of symbolic model checking for parameterized and infinite-state systems whose states can be represented as words of arbitrary length over a finite alphabet, in which regular sets of words are used to represent sets of states. We present LTL(MSO), a combination of the logics monadic second-order logic (MSO) and LTL as a natural logic for expressing the temporal properties to be verified in regular model checking. In other words, LTL(MSO) is a natural specification language for both the system and the property under consideration. LTL(MSO) is a two-dimensional modal logic, where MSO is used for specifying properties of system states and transitions, and LTL is used for specifying temporal properties. In addition, the first-order quantification in MSO can be used to express properties parameterized on a position or process. We give a technique for model checking LTL(MSO), which is adapted from the automata-theoretic approach: a formula is translated to a buchi regular transition system with a regular set of accepting states, and regular model checking techniques are used to search for models. We have implemented the technique, and show its application to a number of parameterized algorithms from the literature. Citation relationship between scientific publications has been successfully used for scholarly bibliometrics, information retrieval and data mining tasks, and citation-based recommendation algorithms are well documented. While previous studies investigated citation relations from various viewpoints, most of them share the same assumption that, if paper1 cites paper2 (or author1 cites author2), they are connected, regardless of citation importance, sentiment, reason, topic, or motivation. However, this assumption is oversimplified. In this study, we employ an innovative "context-rich heterogeneous network" approach, which paves a new way for citation recommendation task. In the network, we characterize 1) the importance of citation relationships between citing and cited papers, and 2) the topical citation motivation. Unlike earlier studies, the citation information, in this paper, is characterized by citation textual contexts extracted from the full-text citing paper. We also propose algorithm to cope with the situation when large portion of full-text missing information exists in the bibliographic repository. Evaluation results show that, context-rich heterogeneous network can significantly enhance the citation recommendation performance.