Exploiting goal independence in the analysis of logic programs (original) (raw)

Goal dependent vs. goal independent analysis of logic programs

Lecture Notes in Computer Science, 1994

Goal independent analysis of logic programs is commonly discussed in the context of the bottom-up approach. However, while the literature is rich in descriptions of top-down analysers and their application, practical experience with bottom-up analysis is still in a preliminary stage. Moreover, the practical use of existing top-down frameworks for goal independent analysis has not been addressed in a practical system. We illustrate the efficient use of existing goal dependent, top-down frameworks for abstract interpretation in performing goal independent analyses of logic programs much the same as those usually derived from bottom-up frameworks. We present several optimizations for this flavour of top-down analysis. The approach is fully implemented within an existing top-down framework. Several implementation tradeoffs are discussed as well as the influence of domain characteristics. An experimental evaluation including a comparison with a bottom-up analysis for the domain Prop is presented. We conclude that the technique can offer advantages with respect to standard goal dependent analyses.

Path Dependent Analysis of Logic Programs

Higher-Order and Symbolic Computation (formerly LISP and Symbolic Computation), 2003

This paper presents an abstract semantics that uses information about execution paths to improve precision of data flow analyses of logic programs. The abstract semantics is illustrated by abstracting execution paths using call strings of fixed length and the last transfer of control. Abstract domains that have been developed for logic program analyses can be used with the new abstract semantics without modification.

Optimized algorithms for incremental analysis of logic programs

Static Analysis, 1996

Global analysis of logic programs can be performed effectively by the use of one of several existing efficient algorithms. However, the traditional global analysis scheme in which all the program code is known in advance and no previous analysis information is available is unsatisfactory in many situations. Incrementa! analysis of logic programs has been shown to be feasible and much more efficient in certain contexts than traditional (non-incremental) global analysis. However, incremental analysis poses additional requirements on the fixpoint algorithm used. In this work we identify these requirements, present an important class of strategies meeting the requirements, present sufficient a priori conditions for such strategies, and propose, implement, and evalúate experimentally a novel algorithm for incremental analysis based on these ideas. The experimental results show that the proposed algorithm performs very efficiently in the incremental case while being comparable to (and, in some cases, considerably better than) other state-of-the-art analysis algorithms even for the non-incremental case. We argüe that our discussions, results, and experiments also shed light on some of the many tradeoffs involved in the design of algorithms for logic program analysis.

Incremental analysis of logic programs

1995

Global analyzers traditionally read and analyze the entire program at once, in a non-incremental way. However, there are many situations which are not well suited to this simple model and which instead require reanalysis of certain parts of a program which has already been analyzed. In these cases, it appears ine cient to perform the analysis of the program again from scratch, as needs to be done with current systems. We describe how the xpoint algorithms in current generic analysis engines can be extended to support incremental analysis. The possible changes to a program are classi ed into three types: addition, deletion, and arbitrary change. For each one of these, we provide one or more algorithms for identifying the parts of the analysis that must be recomputed and for performing the actual recomputation. The potential bene ts and drawbacks of these algorithms are discussed. Finally, we present some experimental results obtained with an implementation of the algorithms in the PLAI generic abstract interpretation framework. The results show signi cant bene ts when using the proposed incremental analysis algorithms.

A Backward Analysis for Constraint Logic Programs

Theory and Practice of Logic Programming, 2002

One recurring problem in program development is that of understanding how to re-use code developed by a third party. In the context of (constraint) logic programming, part of this problem reduces to figuring out how to query a program. If the logic program does not come with any documentation, then the programmer is forced to either experiment with queries in an ad hoc fashion or trace the control-flow of the program (backward) to infer the modes in which a predicate must be called so as to avoid an instantiation error. This paper presents an abstract interpretation scheme that automates the latter technique. The analysis presented in this paper can infer moding properties which if satisfied by the initial query, come with the guarantee that the program and query can never generate any moding or instantiation errors. Other applications of the analysis are discussed. The paper explains how abstract domains with certain computational properties (they condense) can be used to trace control-flow backward (right-to-left) to infer useful properties of initial queries. A correctness argument is presented and an implementation is reported.

Incremental analysis of constraint logic programs

ACM Transactions on Programming Languages and Systems, 2000

Global analyzers traditionally read and analyze the entire program at once, in a nonincremental way. However, there are many situations which are not well suited to this simple model and which instead require reanalysis of certain parts of a program which has already been analyzed. In these cases, it appears inefficient to perform the analysis of the program again from scratch, as needs to be done with current systems. We describe how the fixed-point algorithms used in current generic analysis engines for (constraint) logic programming languages can be extended to support incremental analysis. The possible changes to a program are classified into three types: addition, deletion, and arbitrary change. For each one of these, we provide one or more algorithms for identifying the parts of the analysis that must be recomputed and for performing the actual recomputation. The potential benefits and drawbacks of these algorithms are discussed. Finally, we present some experimental results o...

Differential methods in logic program analysis

The Journal of Logic Programming, 1998

Program analysis based on abstract interpretation has proven very useful in compilation of constraint and logic programming languages. Unfortunately, the traditional goal-dependent framework is inherently imprecise. This is because it handles call and return in such a way that dataflow information may be reasserted unnecessarily, leading to a loss of precision for many description domains. For a few specific domains, the literature contains proposals to overcome the problem, and some implementations use various unpublished tricks that sometimes avoid the precision loss. The purpose of this paper is to map the landscape of goal-dependent, goalindependent, and combined approaches to generic analysis of logic programs. This includes formalising existing methods and tricks in a way that is independent of specific description domains. Moreover, we suggest new methods for overcoming the loss of precision-altogether eight different semantics are considered and compared. We provide theoretical results determining the relative accuracy of the approaches. These show that two of our new semantics are uniformly more accurate than existing approaches. Experiments that we have performed (for two description domains) with implementations of the eight different approaches enable a discussion of their relative runtime performances. We discuss the expected effect on other domains as well and conclude that our new methods can be trusted to yield significantly more accurate analysis for a small extra implementation effort, without compromising the efficiency of analysis.

Analysing Logic Programs by Reasoning Backwards

Program Development in Computational Logic, 2004

One recent advance in program development has been the application of abstract interpretation to verify the partial correctness of a (constraint) logic program. Traditionally forwards analysis has been applied that starts with an initial goal and traces the execution in the direction of the control-flow to approximate the program state at each program point. This is often enough to verify assertions that a property holds. The dual approach is to apply backwards analysis to propagate properties of the allowable states against the control-flow to infer queries for which the program will not violate any assertion. Backwards analysis also underpins other program development tasks such as verifying the termination of a logic program or proving that a logic program with a delay mechanism cannot reduce to a state that contains sub-goals which suspend indefinitely. This paper reviews various backwards analyses that have been proposed for logic programs, identifying common threads in these techniques. The analyses are explained through a series of worked examples. The paper concludes with some suggestions for research in backwards analysis for logic program development.