Starts with a brief review of the history and the application areas considered in the literature. The author then proceeds with introductory modeling examples, behavioral and structural properties, three methods of analysis, subclasses of Petri nets and their analysis. In particular, one section is devoted to marked graphs, the concurrent system model most amenable to analysis. Introductory discussions on stochastic nets with their application to performance modeling, and on high-level nets with their application to logic programming, are provided. Also included are recent results on reachability criteria. Suggestions are provided for further reading on many subject areas of Petri nets. >

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Petri nets: Properties, analysis and applications

ing WS1S Systems to Verify Parameterized Networks . . . . . . . . . . . . 188 Kai Baukus, Saddek Bensalem, Yassine Lakhnech and Karsten Stahl FMona: A Tool for Expressing Validation Techniques over Infinite State Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204 J.-P. Bodeveix and M. Filali Transitive Closures of Regular Relations for Verifying Infinite-State Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 220 Bengt Jonsson and Marcus Nilsson Diagnostic and Test Generation Using Static Analysis to Improve Automatic Test Generation . . . . . . . . . . . . . 235 Marius Bozga, Jean-Claude Fernandez and Lucian Ghirvu Efficient Diagnostic Generation for Boolean Equation Systems . . . . . . . . . . . . 251 Radu Mateescu Efficient Model-Checking Compositional State Space Generation with Partial Order Reductions for Asynchronous Communicating Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 266 Jean-Pierre Krimm and Laurent Mounier Checking for CFFD-Preorder with Tester Processes . . . . . . . . . . . . . . . . . . . . . . . 283 Juhana Helovuo and Antti Valmari Fair Bisimulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 299 Thomas A. Henzinger and Sriram K. Rajamani Integrating Low Level Symmetries into Reachability Analysis . . . . . . . . . . . . . 315 Karsten Schmidt Model-Checking Tools Model Checking Support for the ASM High-Level Language . . . . . . . . . . . . . . 331 Giuseppe Del Castillo and Kirsten Winter Table of

Tools and Algorithms for the Construction and Analysis of Systems. Proc. TACAS 2009

tions. Bootstrap has found many applications in engineering field, including artificial neural networks, biomedical engineering, environmental engineering, image processing, and radar and sonar signal processing. Basic concepts of the bootstrap are summarized in each section as a step-by-step algorithm for ease of implementation. Most of the applications are taken from the signal processing literature. The principles of the bootstrap are introduced in Chapter 2. Both the nonparametric and parametric bootstrap procedures are explained. Babu and Singh (1984) have demonstrated that in general, these two procedures behave similarly for pivotal (Studentized) statistics. The fact that the bootstrap is not the solution for all of the problems has been known to statistics community for a long time; however, this fact is rarely touched on in the manuscripts meant for practitioners. It was first observed by Babu (1984) that the bootstrap does not work in the infinite variance case. Bootstrap Techniques for Signal Processing explains the limitations of bootstrap method with an example. I especially liked the presentation style. The basic results are stated without proofs; however, the application of each result is presented as a simple step-by-step process, easy for nonstatisticians to follow. The bootstrap procedures, such as moving block bootstrap for dependent data, along with applications to autoregressive models and for estimation of power spectral density, are also presented in Chapter 2. Signal detection in the presence of noise is generally formulated as a testing of hypothesis problem. Chapter 3 introduces principles of bootstrap hypothesis testing. The topics are introduced with interesting real life examples. Flow charts, typical in engineering literature, are used to aid explanations of the bootstrap hypothesis testing procedures. The bootstrap leads to second-order correction due to pivoting; this improvement in the results due to pivoting is also explained. In the second part of Chapter 3, signal processing is treated as a regression problem. The performance of the bootstrap for matched filters as well as constant false-alarm rate matched filters is also illustrated. Chapters 2 and 3 focus on estimation problems. Chapter 4 introduces bootstrap methods used in model selection. Due to the inherent structure of the subject matter, this chapter may be difficult for nonstatisticians to follow. Chapter 5 is the most impressive chapter in the book, especially from the standpoint of statisticians. It provides real data bootstrap applications to illustrate the theory covered in the earlier chapters. These include applications to optimal sensor placement for knock detection and land-mine detection. The authors also provide a MATLAB toolbox comprising frequently used routines. Overall, this is a very useful handbook for engineers, especially those working in signal processing.

Probability and Random Processes

A large number of problems in AI and other areas of computer science can be viewed as special cases of the constraint-satisfaction problem. Some examples are machine vision, belief maintenance, scheduling, temporal reasoning, graph problems, floor plan design, the planning of genetic experiments, and the satisfiability problem. A number of different approaches have been developed for solving these problems. Some of them use constraint propagation to simplify the original problem. Others use backtracking to directly search for possible solutions. Some are a combination of these two techniques. This article overviews many of these approaches in a tutorial fashion.

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Algorithms for constraint-satisfaction problems: a survey

SPARQL is the standard language for querying RDF data. In this article, we address systematically the formal study of the database aspects of SPARQL, concentrating in its graph pattern matching facility. We provide a compositional semantics for the core part of SPARQL, and study the complexity of the evaluation of several fragments of the language. Among other complexity results, we show that the evaluation of general SPARQL patterns is PSPACE-complete. We identify a large class of SPARQL patterns, defined by imposing a simple and natural syntactic restriction, where the query evaluation problem can be solved more efficiently. This restriction gives rise to the class of well-designed patterns. We show that the evaluation problem is coNP-complete for well-designed patterns. Moreover, we provide several rewriting rules for well-designed patterns whose application may have a considerable impact in the cost of evaluating SPARQL queries.

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Semantics and complexity of SPARQL

Petri nets have been extensively studied because of their suitability as models for asynchronous computing Despite this effort, the mathematical properties of Petrl nets are not very well understood In this paper we investigate two unportant special types of Petn nets, the conflict-free nets and the persistent nets, the former being a proper subset of the latter. Our results completely characterize the sets of reachable markings attainable by such nets Reachabihty sets of persistent nets are shown to be semllmear A stronger result is obtamed for conflict-free nets which results m an exponential time algorithm for deciding boundedness of such nets The best known upper bound for deciding boundedness of arbitrary nets is exponential space We conclude with a proof that all reachablhty sets of Petri nets may be realized with a "small amount" of nonperslstence

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Properties of Conflict-Free and Persistent Petri Nets

The problem of discovering functional dependencies (FDs) from an existing relation instance has received considerable attention in the database research community. To date, even the most efficient solutions have exponential complexity in the number of attributes of the instance. We develop an algorithm, FastFDs, for solving this problem based on a depth-first, heuristic-driven (DFHD) search for finding minimal covers of hypergraphs. The technique of reducing the FD discovery problem to the problem of finding minimal covers of hypergraphs was applied previously by Lopes et al. in the algorithm Dep-Miner. Dep-Miner employs a levelwise search for minimal covers, whereas FastFDs uses DFHD search. We report several tests on distinct benchmark relation instances involving Dep-Miner, FastFDs, and TANE. Our experimental results indicate that DFHD search is more efficient than Dep-Miner's levelwise search or TANE's partitioning approach for many of these benchmark instances.

FastFDs: A Heuristic-Driven, Depth-First Algorithm for Mining Functional Dependencies from Relation Instances - Extended Abstract

On the structure of sets in NP and other complexity classes

We examine the issue of how to measure the degree to which a functional dependency (FD) is approximate. The primary motivation lies in the fact that approximate FDs represent potentially interesting patterns existent in a table. Their discovery is a valuable data mining problem. However, before algorithms can be developed, a measure must be defined quantifying their approximation degree.First we develop an approximation measure by axiomatizing the following intuition: the degree to which X → Y is approximate in a table T is the degree to which T determines a function from ΠX(T) to ΠY(T). We prove that a unique unnormalized measure satisfies these axioms up to a multiplicative constant. Next we compare the measure developed with two other measures from the literature. In all but one case, we show that the measures can be made to differ as much as possible within normalization. We examine these measure on several real datasets and observe that many of the theoretically possible extreme differences do not bear themselves out. We offer some conclusions as to particular situations where certain measures are more appropriate than others.

On approximation measures for functional dependencies

In this article, we develop a relational algebra for metadata integration, Federated Interoperable Relational Algebra (FIRA). FIRA has many desirable properties such as compositionality, closure, a deterministic semantics, a modest complexity, support for nested queries, a subalgebra equivalent to canonical Relational Algebra (RA), and robustness under certain classes of schema evolution. Beyond this, FIRA queries are capable of producing fully dynamic output schemas, where the number of relations and/or the number of columns in relations of the output varies dynamically with the input instance. Among existing query languages for relational metadata integration, only FIRA provides generalized dynamic output schemas, where the values in any (fixed) number of input columns can determine output schemas.Further contributions of this article include development of an extended relational model for metadata integration, the Federated Relational Data Model, which is strictly downward compatible with the relational model. Additionally, we define the notion of Transformational Completeness for relational query languages and postulate FIRA as a canonical transformationally complete language. We also give a declarative, SQL-like query language that is equivalent to FIRA, called Federated Interoperable Structured Query Language (FISQL).While our main contributions are conceptual, the federated model, FISQL/FIRA, and the notion of transformational completeness nevertheless have important applications to data integration and OLAP. In addition to summarizing these applications, we illustrate the use of FIRA to optimize FISQL queries using rule-based transformations that directly parallel their canonical relational counterparts. We conclude the article with an extended discussion of related work as well as an indication of current and future work on FISQL/FIRA.

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Edward L. Robertson

Papers

Properties of Conflict-Free and Persistent Petri Nets

FastFDs: A Heuristic-Driven, Depth-First Algorithm for Mining Functional Dependencies from Relation Instances - Extended Abstract

On the structure of sets in NP and other complexity classes

On approximation measures for functional dependencies

Relational languages for metadata integration