3,544 research outputs found

    An overview of the ciao multiparadigm language and program development environment and its design philosophy

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    We describe some of the novel aspects and motivations behind the design and implementation of the Ciao multiparadigm programming system. An important aspect of Ciao is that it provides the programmer with a large number of useful features from different programming paradigms and styles, and that the use of each of these features can be turned on and off at will for each program module. Thus, a given module may be using e.g. higher order functions and constraints, while another module may be using objects, predicates, and concurrency. Furthermore, the language is designed to be extensible in a simple and modular way. Another important aspect of Ciao is its programming environment, which provides a powerful preprocessor (with an associated assertion language) capable of statically finding non-trivial bugs, verifying that programs comply with specifications, and performing many types of program optimizations. Such optimizations produce code that is highly competitive with other dynamic languages or, when the highest levéis of optimization are used, even that of static languages, all while retaining the interactive development environment of a dynamic language. The environment also includes a powerful auto-documenter. The paper provides an informal overview of the language and program development environment. It aims at illustrating the design philosophy rather than at being exhaustive, which would be impossible in the format of a paper, pointing instead to the existing literature on the system

    Program development using abstract interpretation (and the ciao system preprocessor)

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    The technique of Abstract Interpretation has allowed the development of very sophisticated global program analyses which are at the same time provably correct and practical. We present in a tutorial fashion a novel program development framework which uses abstract interpretation as a fundamental tool. The framework uses modular, incremental abstract interpretation to obtain information about the program. This information is used to validate programs, to detect bugs with respect to partial specifications written using assertions (in the program itself and/or in system librarles), to genérate and simplify run-time tests, and to perform high-level program transformations such as múltiple abstract specialization, parallelization, and resource usage control, all in a provably correct way. In the case of validation and debugging, the assertions can refer to a variety of program points such as procedure entry, procedure exit, points within procedures, or global computations. The system can reason with much richer information than, for example, traditional types. This includes data structure shape (including pointer sharing), bounds on data structure sizes, and other operational variable instantiation properties, as well as procedure-level properties such as determinacy, termination, non-failure, and bounds on resource consumption (time or space cost). CiaoPP, the preprocessor of the Ciao multi-paradigm programming system, which implements the described functionality, will be used to illustrate the fundamental ideas

    Interactive Simplifier Tracing and Debugging in Isabelle

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    The Isabelle proof assistant comes equipped with a very powerful tactic for term simplification. While tremendously useful, the results of simplifying a term do not always match the user's expectation: sometimes, the resulting term is not in the form the user expected, or the simplifier fails to apply a rule. We describe a new, interactive tracing facility which offers insight into the hierarchical structure of the simplification with user-defined filtering, memoization and search. The new simplifier trace is integrated into the Isabelle/jEdit Prover IDE.Comment: Conferences on Intelligent Computer Mathematics, 201

    Applying Formal Methods to Networking: Theory, Techniques and Applications

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    Despite its great importance, modern network infrastructure is remarkable for the lack of rigor in its engineering. The Internet which began as a research experiment was never designed to handle the users and applications it hosts today. The lack of formalization of the Internet architecture meant limited abstractions and modularity, especially for the control and management planes, thus requiring for every new need a new protocol built from scratch. This led to an unwieldy ossified Internet architecture resistant to any attempts at formal verification, and an Internet culture where expediency and pragmatism are favored over formal correctness. Fortunately, recent work in the space of clean slate Internet design---especially, the software defined networking (SDN) paradigm---offers the Internet community another chance to develop the right kind of architecture and abstractions. This has also led to a great resurgence in interest of applying formal methods to specification, verification, and synthesis of networking protocols and applications. In this paper, we present a self-contained tutorial of the formidable amount of work that has been done in formal methods, and present a survey of its applications to networking.Comment: 30 pages, submitted to IEEE Communications Surveys and Tutorial

    PerfXplain: Debugging MapReduce Job Performance

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    While users today have access to many tools that assist in performing large scale data analysis tasks, understanding the performance characteristics of their parallel computations, such as MapReduce jobs, remains difficult. We present PerfXplain, a system that enables users to ask questions about the relative performances (i.e., runtimes) of pairs of MapReduce jobs. PerfXplain provides a new query language for articulating performance queries and an algorithm for generating explanations from a log of past MapReduce job executions. We formally define the notion of an explanation together with three metrics, relevance, precision, and generality, that measure explanation quality. We present the explanation-generation algorithm based on techniques related to decision-tree building. We evaluate the approach on a log of past executions on Amazon EC2, and show that our approach can generate quality explanations, outperforming two naive explanation-generation methods.Comment: VLDB201

    Tools for Search Tree Visualization: The APT Tool

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    The control part of the execution of a constraint logic program can be conceptually shown as a search-tree, where nodes correspond to calis, and whose branches represent conjunctions and disjunctions. This tree represents the search space traversed by the program, and has also a direct relationship with the amount of work performed by the program. The nodes of the tree can be used to display information regarding the state and origin of instantiation of the variables involved in each cali. This depiction can also be used for the enumeration process. These are the features implemented in APT, a tool which runs constraint logic programs while depicting a (modified) search-tree, keeping at the same time information about the state of the variables at every moment in the execution. This information can be used to replay the execution at will, both forwards and backwards in time. These views can be abstracted when the size of the execution requires it. The search-tree view is used as a framework onto which constraint-level visualizations (such as those presented in the following chapter) can be attached
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