9 resultados para Program Compilation

em Universidad Politécnica de Madrid


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The technique of Abstract Interpretation [11] has allowed the development of sophisticated program analyses which are provably correct and practical. The semantic approximations produced by such analyses have been traditionally applied to optimization during program compilation. However, recently, novel and promising applications of semantic approximations have been proposed in the more general context of program validation and debugging [3,9,7].

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This paper addresses the issue of the practicality of global flow analysis in logic program compilation, in terms of speed of the analysis, precisión, and usefulness of the information obtained. To this end, design and implementation aspects are discussed for two practical abstract interpretation-based flow analysis systems: MA , the MCC And-parallel Analyzer and Annotator; and Ms, an experimental mode inference system developed for SB-Prolog. The paper also provides performance data obtained (rom these implementations and, as an example of an application, a study of the usefulness of the mode information obtained in reducing run-time checks in independent and-parallelism.Based on the results obtained, it is concluded that the overhead of global flow analysis is not prohibitive, while the results of analysis can be quite precise and useful.

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This paper addresses the issue of the practicality of global flow analysis in logic program compilation, in terms of both speed and precision of analysis. It discusses design and implementation aspects of two practical abstract interpretation-based flow analysis systems: MA3, the MOO Andparallel Analyzer and Annotator; and Ms, an experimental mode inference system developed for SB-Prolog. The paper also provides performance data obtained from these implementations. Based on these results, it is concluded that the overhead of global flow analysis is not prohibitive, while the results of analysis can be quite precise and useful.

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CiaoPP is the abstract interpretation-based preprocessor of the Ciao multi-paradigm (Constraint) Logic Programming system. It uses modular, incremental abstract interpretation as a fundamental tool to obtain information about programs. In CiaoPP, the semantic approximations thus produced have been applied to perform high- and low-level optimizations during program compilation, including transformations such as múltiple abstract specialization, parallelization, partial evaluation, resource usage control, and program verification. More recently, novel and promising applications of such semantic approximations are being applied in the more general context of program development such as program verification. In this work, we describe our extensión of the system to incorpórate Abstraction-Carrying Code (ACC), a novel approach to mobile code safety. ACC follows the standard strategy of associating safety certificates to programs, originally proposed in Proof Carrying- Code. A distinguishing feature of ACC is that we use an abstraction (or abstract model) of the program computed by standard static analyzers as a certifícate. The validity of the abstraction on the consumer side is checked in a single-pass by a very efficient and specialized abstractinterpreter. We have implemented and benchmarked ACC within CiaoPP. The experimental results show that the checking phase is indeed faster than the proof generation phase, and that the sizes of certificates are reasonable. Moreover, the preprocessor is based on compile-time (and run-time) tools for the certification of CLP programs with resource consumption assurances.

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The technique of Abstract Interpretation [13] has allowed the development of sophisticated program analyses which are provably correct and practical. The semantic approximations produced by such analyses have been traditionally applied to optimization during program compilation. However, recently, novel and promising applications of semantic approximations have been proposed in the more general context of program verification and debugging [3],[10],[7].

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We describe the current status of and provide performance results for a prototype compiler of Prolog to C, ciaocc. ciaocc is novel in that it is designed to accept different kinds of high-level information, typically obtained via an automatic analysis of the initial Prolog program and expressed in a standardized language of assertions. This information is used to optimize the resulting C code, which is then processed by an off-the-shelf C compiler. The basic translation process essentially mimics the unfolding of a bytecode emulator with respect to the particular bytecode corresponding to the Prolog program. This is facilitated by a flexible design of the instructions and their lower-level components. This approach allows reusing a sizable amount of the machinery of the bytecode emulator: predicates already written in C, data definitions, memory management routines and áreas, etc., as well as mixing emulated bytecode with native code in a relatively straightforward way. We report on the performance of programs compiled by the current versión of the system, both with and without analysis information.

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Recent research into the implementation of logic programming languages has demonstrated that global program analysis can be used to speed up execution by an order of magnitude. However, currently such global program analysis requires the program to be analysed as a whole: sepárate compilation of modules is not supported. We describe and empirically evalúate a simple model for extending global program analysis to support sepárate compilation of modules. Importantly, our model supports context-sensitive program analysis and multi-variant specialization of procedures in the modules.

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We describe the current status of and provide preliminary performance results for a compiler of Prolog to C. The compiler is novel in that it is designed to accept different kinds of high-level information (typically obtained via an analysis of the initial Prolog program and expressed in a standardized language of assertions) and use this information to optimize the resulting C code, which is then further processed by an off-the-shelf C compiler. The basic translation process used essentially mimics an unfolding of a C-coded bytecode emúlator with respect to the particular bytecode corresponding to the Prolog program. Optimizations are then applied to this unfolded program. This is facilitated by a more flexible design of the bytecode instructions and their lower-level components. This approach allows reusing a sizable amount of the machinery of the bytecode emulator: ancillary pieces of C code, data definitions, memory management routines and áreas, etc., as well as mixing bytecode emulated code with natively compiled code in a relatively straightforward way We report on the performance of programs compiled by the current versión of the system, both with and without analysis information.

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Ciao Prolog incorporates a module system which allows sepárate compilation and sensible creation of standalone executables. We describe some of the main aspects of the Ciao modular compiler, ciaoc, which takes advantage of the characteristics of the Ciao Prolog module system to automatically perform sepárate and incremental compilation and efficiently build small, standalone executables with competitive run-time performance, ciaoc can also detect statically a larger number of programming errors. We also present a generic code processing library for handling modular programs, which provides an important part of the functionality of ciaoc. This library allows the development of program analysis and transformation tools in a way that is to some extent orthogonal to the details of module system design, and has been used in the implementation of ciaoc and other Ciao system tools. We also describe the different types of executables which can be generated by the Ciao compiler, which offer different tradeoffs between executable size, startup time, and portability, depending, among other factors, on the linking regime used (static, dynamic, lazy, etc.). Finally, we provide experimental data which illustrate these tradeoffs.