471 research outputs found
An integration of partial evaluation in a generic abstract interpretation framework
Information generated by abstract interpreters has long been
used to perform program specialization. Additionally, if the
abstract interpreter generates a multivariant analysis, it is also possible to perform múltiple specialization. Information about valúes of variables is propagated by simulating program execution and performing fixpoint computations for recursive calis. In contrast, traditional partial evaluators (mainly) use unfolding for both propagating valúes of variables and transforming the program. It is known that abstract interpretation is a better technique for propagating success valúes than unfolding. However, the program transformations induced by unfolding may lead to important optimizations which are not directly achievable in the existing frameworks for múltiple specialization based on abstract interpretation. The aim of this work is to devise a specialization framework which integrates the better information propagation of abstract interpretation with the powerful program transformations performed by partial evaluation, and which can be implemented via small modifications to existing generic abstract interpreters. With this aim, we will relate top-down abstract interpretation with traditional concepts in partial evaluation and sketch how the sophisticated techniques developed for controlling partial evaluation can be adapted to the proposed specialization framework. We conclude that there can be both practical and conceptual advantages in the proposed integration of partial evaluation
and abstract interpretation
A practical approach to the global analysis of CLP programs
This paper presents and illustrates with an example a practical approach to the dataflow analysis of programs written in constraint logic programming (CLP) languages using abstract interpretation. It is first argued that,
from the framework point of view, it sufnces to propose relatively simple extensions of traditional analysis methods which have already been proved useful and practical and for which efncient fixpoint algorithms have been
developed. This is shown by proposing a simple but quite general extensión of Bruynooghe's traditional framework to the analysis of CLP programs. In this extensión constraints are viewed not as "suspended goals" but rather as new information in the store, following the traditional view of CLP. Using this approach, and as an example of its use, a complete, constraint system independent, abstract analysis is presented for approximating definiteness information. The analysis is in fact of quite general applicability. It has been implemented and used in the analysis of CLP(R) and Prolog-III applications. Results from the implementation of this analysis are also presented
A Backward Analysis for Constraint Logic Programs
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.Comment: 32 page
Incremental and Modular Context-sensitive Analysis
Context-sensitive global analysis of large code bases can be expensive, which
can make its use impractical during software development. However, there are
many situations in which modifications are small and isolated within a few
components, and it is desirable to reuse as much as possible previous analysis
results. This has been achieved to date through incremental global analysis
fixpoint algorithms that achieve cost reductions at fine levels of granularity,
such as changes in program lines. However, these fine-grained techniques are
not directly applicable to modular programs, nor are they designed to take
advantage of modular structures. This paper describes, implements, and
evaluates an algorithm that performs efficient context-sensitive analysis
incrementally on modular partitions of programs. The experimental results show
that the proposed modular algorithm shows significant improvements, in both
time and memory consumption, when compared to existing non-modular, fine-grain
incremental analysis techniques. Furthermore, thanks to the proposed
inter-modular propagation of analysis information, our algorithm also
outperforms traditional modular analysis even when analyzing from scratch.Comment: 56 pages, 27 figures. To be published in Theory and Practice of Logic
Programming. v3 corresponds to the extended version of the ICLP2018 Technical
Communication. v4 is the revised version submitted to Theory and Practice of
Logic Programming. v5 (this one) is the final author version to be published
in TPL
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