35 resultados para program development

em Universidad Politécnica de Madrid


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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.

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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.

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We present in a tutorial fashion CiaoPP, the preprocessor of the Ciao multi-paradigm programming system, which implements 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 libraries), to generate and simplify run-time tests, and to perform high-level program transformations such as multiple 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).

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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 libraries), to generate and simplify run-time tests, and to perform high-level program transformations such as multiple 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, nonfailure, 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.

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We discuss a framework for the application of abstract interpretation as an aid during program development, rather than in the more traditional application of program optimization. Program validation and detection of errors is first performed statically by comparing (partial) specifications written in terms of assertions against information obtained from (global) static analysis of the program. The results of this process are expressed in the user assertion language. Assertions (or parts of assertions) which cannot be checked statically are translated into run-time tests. The framework allows the use of assertions to be optional. It also allows using very general properties in assertions, beyond the predefined set understandable by the static analyzer and including properties defined by user programs. We also report briefly on an implementation of the framework. The resulting tool generates and checks assertions for Prolog, CLP(R), and CHIP/CLP(fd) programs, and integrates compile-time and run-time checking in a uniform way. The tool allows using properties such as types, modes, non-failure, determinacy, and computational cost, and can treat modules separately, performing incremental analysis.

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We present a framework for the application of abstract interpretation as an aid during program development, rather than in the more traditional application of program optimization. Program validation and detection of errors is first performed statically by comparing (partial) specifications written in terms of assertions against information obtained from static analysis of the program. The results of this process are expressed in the user assertion language. Assertions (or parts of assertions) which cannot be verified statically are translated into run-time tests. The framework allows the use of assertions to be optional. It also allows using very general properties in assertions, beyond the predefined set understandable by the static analyzer and including properties defined by means of user programs. We also report briefly on an implementation of the framework. The resulting tool generates and checks assertions for Prolog, CLP(R), and CHIP/CLP(fd) programs, and integrates compile-time and run-time checking in a uniform way. The tool allows using properties such as types, modes, non-failure, determinacy, and computational cost, and can treat modules separately, performing incremental analysis. In practice, this modularity allows detecting statically bugs in user programs even if they do not contain any assertions.

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Several models for context-sensitive analysis of modular programs have been proposed, each with different characteristics and representing different trade-offs. The advantage of these context-sensitive analyses is that they provide information which is potentially more accurate than that provided by context-free analyses. Such information can then be applied to validating/debugging the program and/or to specializing the program in order to obtain important performance improvements. Some very preliminary experimental results have also been reported for some of these models which provided initial evidence on their potential. However, further experimentation, which is needed in order to understand the many issues left open and to show that the proposed modes scale and are usable in the context of large, real-life modular programs, was left as future work. The aim of this paper is two-fold. On one hand we provide an empirical comparison of the different models proposed in previous work, as well as experimental data on the different choices left open in those designs. On the other hand we explore the scalability of these models by using larger modular programs as benchmarks. The results have been obtained from a realistic implementation of the models, integrated in a production-quality compiler (CiaoPP/Ciao). Our experimental results shed light on the practical implications of the different design choices and of the models themselves. We also show that contextsensitive analysis of modular programs is indeed feasible in practice, and that in certain critical cases it provides better performance results than those achievable by analyzing the whole program at once, specially in terms of memory consumption and when reanalyzing after making changes to a program, as is often the case during program development.

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It is now widely accepted that separating programs into modules is useful in program development and maintenance. While many Prolog implementations include useful module systems, we argüe that these systems can be improved in a number of ways, such as, for example, being more amenable to effective global analysis and transformation and allowing sepárate compilation or sensible creation of standalone executables. We discuss a number of issues related to the design of such an improved module system for Prolog and propose some novel solutions. Based on this, we present the choices made in the Ciao module system, which has been designed to meet a number of objectives: allowing sepárate compilation, extensibility in features and in syntax, amenability to modular global analysis and transformation, enhanced error detection, support for meta-programming and higher-order, compatibility to the extent possible with official and de-facto standards, etc.

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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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Distributed parallel execution systems speed up applications by splitting tasks into processes whose execution is assigned to different receiving nodes in a high-bandwidth network. On the distributing side, a fundamental problem is grouping and scheduling such tasks such that each one involves sufñcient computational cost when compared to the task creation and communication costs and other such practical overheads. On the receiving side, an important issue is to have some assurance of the correctness and characteristics of the code received and also of the kind of load the particular task is going to pose, which can be specified by means of certificates. In this paper we present in a tutorial way a number of general solutions to these problems, and illustrate them through their implementation in the Ciao multi-paradigm language and program development environment. This system includes facilities for parallel and distributed execution, an assertion language for specifying complex programs properties (including safety and resource-related properties), and compile-time and run-time tools for performing automated parallelization and resource control, as well as certification of programs with resource consumption assurances and efñcient checking of such certificates.

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Global data-flow analysis of (constraint) logic programs, which is generally based on abstract interpretation [7], is reaching a comparatively high level of maturity. A natural question is whether it is time for its routine incorporation in standard compilers, something which, beyond a few experimental systems, has not happened to date. Such incorporation arguably makes good sense only if: • the range of applications of global analysis is large enough to justify the additional complication in the compiler, and • global analysis technology can deal with all the features of "practical" languages (e.g., the ISO-Prolog built-ins) and "scales up" for large programs. We present a tutorial overview of a number of concepts and techniques directly related to the issues above, with special emphasis on the first one. In particular, we concéntrate on novel uses of global analysis during program development and debugging, rather than on the more traditional application área of program optimization. The idea of using abstract interpretation for validation and diagnosis has been studied in the context of imperative programming [2] and also of logic programming. The latter work includes issues such as using approximations to reduce the burden posed on programmers by declarative debuggers [6, 3] and automatically generating and checking assertions [4, 5] (which includes the more traditional type checking of strongly typed languages, such as Gódel or Mercury [1, 8, 9]) We also review some solutions for scalability including modular analysis, incremental analysis, and widening. Finally, we discuss solutions for dealing with meta-predicates, side-effects, delay declarations, constraints, dynamic predicates, and other such features which may appear in practical languages. In the discussion we will draw both from the literature and from our experience and that of others in the development and use of the CIAO system analyzer. In order to emphasize the practical aspects of the solutions discussed, the presentation of several concepts will be illustrated by examples run on the CIAO system, which makes extensive use of global analysis and assertions.

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Context-sensitive analysis provides information which is potentially more accurate than that provided by context-free analysis. Such information can then be applied in order to validate/debug the program and/or to specialize the program obtaining important improvements. Unfortunately, context-sensitive analysis of modular programs poses important theoretical and practical problems. One solution, used in several proposals, is to resort to context-free analysis. Other proposals do address context-sensitive analysis, but are only applicable when the description domain used satisfies rather restrictive properties. In this paper, we argüe that a general framework for context-sensitive analysis of modular programs, Le., one that allows using all the domains which have proved useful in practice in the non-modular setting, is indeed feasible and very useful. Driven by our experience in the design and implementation of analysis and specialization techniques in the context of CiaoPP, the Ciao system preprocessor, in this paper we discuss a number of design goals for context-sensitive analysis of modular programs as well as the problems which arise in trying to meet these goals. We also provide a high-level description of a framework for analysis of modular programs which does substantially meet these objectives. This framework is generic in that it can be instantiated in different ways in order to adapt to different contexts. Finally, the behavior of the different instantiations w.r.t. the design goals that motivate our work is also discussed.

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In an advanced program development environment, such as that discussed in the introduction of this book, several tools may coexist which handle both the program and information on the program in different ways. Also, these tools may interact among themselves and with the user. Thus, the different tools and the user need some way to communicate. It is our design principie that such communication be performed in terms of assertions. Assertions are syntactic objects which allow expressing properties of programs. Several assertion languages have been used in the past in different contexts, mainly related to program debugging. In this chapter we propose a general language of assertions which is used in different tools for validation and debugging of constraint logic programs in the context of the DiSCiPl project. The assertion language proposed is parametric w.r.t. the particular constraint domain and properties of interest being used in each different tool. The language proposed is quite general in that it poses few restrictions on the kind of properties which may be expressed. We believe the assertion language we propose is of practical relevance and appropriate for the different uses required in the tools considered.

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Separating programs into modules is a well-known technique which has proven very useful in program development and maintenance. Starting by introducing a number of possible scenarios, in this paper we study different issues which appear when developing analysis and specialization techniques for modular logic programming. We discuss a number of design alternatives and their consequences for the different scenarios considered and describe where applicable the decisions made in the Ciao system analyzer and specializer. In our discussion we use the module system of Ciao Prolog. This is both for concreteness and because Ciao Prolog is a second-generation Prolog system which has been designed with global analysis and specialization in mind, and which has a strict module system. The aim of this work is not to provide a theoretical basis on modular analysis and specialization, but rather to discuss some interesting practical issues.

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It is now widely accepted that separating programs into modules has proven very useful in program development and maintenance. While many Prolog implementations include useful module systems, we feel that these systems can be improved in a number of ways, such as, for example, being more amenable to effective global analysis and allowing sepárate compilation or sensible creation of standalone executables. We discuss a number of issues related to the design of such an improved module system for Prolog. Based on this, we present the choices made in the Ciao module system, which has been designed to meet a number of objectives: allowing sepárate compilation, extensibility in features and in syntax, amenability to modular global analysis, etc.