Data Mining - Concepts and Techniques.

Our growing dependence on increasingly complex computer and software systems necessitates the development of formalisms, techniques, and tools for assessing functional properties of these systems. One such technique that has emerged in the last twenty years is model checking, which systematically (and automatically) checks whether a model of a given system satisfies a desired property such as deadlock freedom, invariants, and request-response properties. This automated technique for verification and debugging has developed into a mature and widely used approach with many applications. Principles of Model Checking offers a comprehensive introduction to model checking that is not only a text suitable for classroom use but also a valuable reference for researchers and practitioners in the field. The book begins with the basic principles for modeling concurrent and communicating systems, introduces different classes of properties (including safety and liveness), presents the notion of fairness, and provides automata-based algorithms for these properties. It introduces the temporal logics LTL and CTL, compares them, and covers algorithms for verifying these logics, discussing real-time systems as well as systems subject to random phenomena. Separate chapters treat such efficiency-improving techniques as abstraction and symbolic manipulation. The book includes an extensive set of examples (most of which run through several chapters) and a complete set of basic results accompanied by detailed proofs. Each chapter concludes with a summary, bibliographic notes, and an extensive list of exercises of both practical and theoretical nature.

/pdf/principles-of-model-checking-249iimickz.pdf

Principles of Model Checking

Model Checking

SPIN is an efficient verification system for models of distributed software systems. It has been used to detect design errors in applications ranging from high-level descriptions of distributed algorithms to detailed code for controlling telephone exchanges. The paper gives an overview of the design and structure of the verifier, reviews its theoretical foundation, and gives an overview of significant practical applications.

/pdf/the-model-checker-spin-1bgo4jtefp.pdf

The model checker SPIN

Symbolic model checking is a powerful formal specification and verification method that has been applied successfully in several industrial designs. Using symbolic model checking techniques it is possible to verify industrial-size finite state systems. State spaces with up to 1030 states can be exhaustively searched in minutes. Models with more than 10120 states have been verified using special techniques.

/pdf/symbolic-model-checking-pxw1i9acib.pdf

Symbolic Model Checking

The main problem in model checking that prevents it from being used for verification of large systems is the state explosion problem. This problem often arises from combining parallel processes together, Many techniques have been proposed to overcome this difficulty and, thus, increase the size of the systems that model checkers can handle. We describe several compositional model checking techniques used in practice and show a few examples demonstrating their performance.

Compositional reasoning in model checking

: The BDD-based symbolic model checking algorithm given in (4.10) is extended to handle real-time properties using the bounded until operator (9). We believe that this algorithm which is based on discrete time is able to handle many real-time properties that arise in practical problems. One example of such a property is priority increasing. This is a serious problem that can make real- time systems unpredictable in subtle ways. Our work discusses this problem and presents one possible solution. The solution is formalized and verified using the modified algorithm. We also propose another extension to the model checking algorithm. Timed transition graphs are transition graphs in which events may take non-unit time to occur. The time it takes for a transition in a TTG to happen is determined by a time interval. This allows the construction of smaller and more realistic models. A symbolic model checking algorithm is given for formulas using the bounded until operator in TTG models.

Real-time symbolic model checking for discrete time models

Recently, a number of scalable stream sharing protocols have been proposed with the promise of great reductions in the server and network bandwidth required for delivering popular media content. Although the scalability of these protocols has been evaluated mostly for sequential user accesses, a high degree of interactivity has been observed in the accesses to several real media servers. Moreover, some studies have indicated that user interactivity can severely penalize the scalability of stream sharing protocols.This paper investigates alternative mechanisms for scalable streaming to interactive users. We first identify a set of workload aspects that are determinant to the scalability of classes of streaming protocols. Using real workloads and a new interactive media workload generator, we build a rich set of realistic synthetic workloads. We evaluate Bandwidth Skimming and Patching, two state-of-the-art streaming protocols, covering, with our workloads, a larger region of the design space than previous work. Finally, we propose and evaluate five optimizations to Bandwidth Skimming, the most scalable of the two protocols. Our best optimization reduces the average server bandwidth required for interactive workloads in up to 54%, for unlimited client buffers, and 29%, if buffers are constrained to 25% of media size.

https://homepages.dcc.ufmg.br/~cunha/papers/rocha05mm-interactive.pdf

Scalable media streaming to interactive users

Symbolic model checking is a technique for verifying finite-state concurrent systems. Models with up to 1030 states can often be verified in minutes. In this paper, we present a new tool to analyze real-time systems, based on this technique. We have designed a language, called Verus, for the description of real-time systems. Such a description is compiled into a state-transition graph and represented symbolically using binary decision diagrams. We have developed new algorithms for exploring the state space and computing quantitative information about the system. In addition to determining the exact bounds on the length of the time interval between two specified events, we compute the number of occurrences of an event in such an interval. This technique allows us to determine performance measures such as schedulability, response time, and system load. Our algorithms produce more detailed information than traditional methods. This information leads to a better understanding of the behavior of the system, in addition to verifying if its timing requirements are satisfied. We integrate these ideas into the Verus tool, currently under development. To demonstrate how our technique works, we have verified a robotics control system. The results obtained demonstrate that our method can be successfully applied in the analysis of real-time system designs.

/pdf/verus-a-tool-for-quantitative-analysis-of-finite-state-real-3l06ld9e3k.pdf

Sérgio Campos

Papers

Symbolic Model Checking

Compositional reasoning in model checking

Real-time symbolic model checking for discrete time models

Scalable media streaming to interactive users

Verus: a tool for quantitative analysis of finite-state real-time systems