28,907 research outputs found
A generic framework for context-sensitive analysis of modular programs
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
A Practical Type Analysis for Verification of Modular Prolog Programs
Regular types are a powerful tool for computing very precise descriptive types for logic programs. However, in the context of real life, modular Prolog programs, the accurate results obtained by regular types often come at the price of efficiency. In this paper we propose a combination of techniques aimed at improving analysis efficiency in this context. As a first technique we allow optionally reducing the accuracy of inferred types by using only the types defined by the user or present in the libraries. We claim that, for the purpose of verifying type signatures given in the form of assertions the precision obtained using this approach is sufficient, and show that analysis times can be reduced significantly. Our second technique is aimed at dealing with situations where we would like to limit the amount of reanalysis performed, especially for library modules. Borrowing some ideas from polymorphic type systems, we show how to solve the problem by admitting parameters in type specifications. This allows us to compose new call patterns with some pre computed analysis info without losing any information. We argue that together these two techniques contribute to the practical and scalable analysis and verification of types in Prolog programs
An efficient, parametric fixpoint algorithm for analysis of java bytecode
Abstract interpretation has been widely used for the analysis of object-oriented languages and, in particular, Java source and bytecode. However, while most existing work deals with the problem of flnding expressive abstract domains that track accurately the characteristics of a particular concrete property, the underlying flxpoint algorithms have received comparatively less attention. In fact, many existing (abstract interpretation based—) flxpoint algorithms rely on relatively inefHcient techniques for solving inter-procedural caligraphs or are speciflc and tied to particular analyses. We also argüe that the design of an efficient fixpoint algorithm is pivotal to supporting the analysis of large programs. In this paper we introduce a novel algorithm for analysis of Java bytecode which includes a number of optimizations in order to reduce the number of iterations. The algorithm is parametric -in the sense that it is independent of the abstract domain used and it can be applied to different domains as "plug-ins"-, multivariant, and flow-sensitive. Also, is based on a program transformation, prior to the analysis, that results in a highly uniform representation of all the features in the language and therefore simplifies analysis. Detailed descriptions of decompilation solutions are given and discussed with an example. We also provide some performance data from a preliminary implementation of the analysis
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
Thread-Modular Static Analysis for Relaxed Memory Models
We propose a memory-model-aware static program analysis method for accurately
analyzing the behavior of concurrent software running on processors with weak
consistency models such as x86-TSO, SPARC-PSO, and SPARC-RMO. At the center of
our method is a unified framework for deciding the feasibility of inter-thread
interferences to avoid propagating spurious data flows during static analysis
and thus boost the performance of the static analyzer. We formulate the
checking of interference feasibility as a set of Datalog rules which are both
efficiently solvable and general enough to capture a range of hardware-level
memory models. Compared to existing techniques, our method can significantly
reduce the number of bogus alarms as well as unsound proofs. We implemented the
method and evaluated it on a large set of multithreaded C programs. Our
experiments showthe method significantly outperforms state-of-the-art
techniques in terms of accuracy with only moderate run-time overhead.Comment: revised version of the ESEC/FSE 2017 pape
Heap Abstractions for Static Analysis
Heap data is potentially unbounded and seemingly arbitrary. As a consequence,
unlike stack and static memory, heap memory cannot be abstracted directly in
terms of a fixed set of source variable names appearing in the program being
analysed. This makes it an interesting topic of study and there is an abundance
of literature employing heap abstractions. Although most studies have addressed
similar concerns, their formulations and formalisms often seem dissimilar and
some times even unrelated. Thus, the insights gained in one description of heap
abstraction may not directly carry over to some other description. This survey
is a result of our quest for a unifying theme in the existing descriptions of
heap abstractions. In particular, our interest lies in the abstractions and not
in the algorithms that construct them.
In our search of a unified theme, we view a heap abstraction as consisting of
two features: a heap model to represent the heap memory and a summarization
technique for bounding the heap representation. We classify the models as
storeless, store based, and hybrid. We describe various summarization
techniques based on k-limiting, allocation sites, patterns, variables, other
generic instrumentation predicates, and higher-order logics. This approach
allows us to compare the insights of a large number of seemingly dissimilar
heap abstractions and also paves way for creating new abstractions by
mix-and-match of models and summarization techniques.Comment: 49 pages, 20 figure
A Graph-Based Semantics Workbench for Concurrent Asynchronous Programs
A number of novel programming languages and libraries have been proposed that
offer simpler-to-use models of concurrency than threads. It is challenging,
however, to devise execution models that successfully realise their
abstractions without forfeiting performance or introducing unintended
behaviours. This is exemplified by SCOOP---a concurrent object-oriented
message-passing language---which has seen multiple semantics proposed and
implemented over its evolution. We propose a "semantics workbench" with fully
and semi-automatic tools for SCOOP, that can be used to analyse and compare
programs with respect to different execution models. We demonstrate its use in
checking the consistency of semantics by applying it to a set of representative
programs, and highlighting a deadlock-related discrepancy between the principal
execution models of the language. Our workbench is based on a modular and
parameterisable graph transformation semantics implemented in the GROOVE tool.
We discuss how graph transformations are leveraged to atomically model
intricate language abstractions, and how the visual yet algebraic nature of the
model can be used to ascertain soundness.Comment: Accepted for publication in the proceedings of FASE 2016 (to appear
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