Formal Analysis of Java Programs in JavaFAN

Farzan, Azadeh; Feng, Chen; Meseguer, José; Roşu, Grigore

doi:10.1007/978-3-540-27813-9_46

Cited by 66 publications

(58 citation statements)

References 5 publications

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“…We have presented our approach in terms of a sequential fragment of Java bytecode but the term rewriting setting is well suited to deal with the extension to concurrent aspects of Java and to the handling of exceptions [16,7].…”

Section: Resultsmentioning

confidence: 99%

“…From a bytecode Java program p, we have developed a prototype that automatically produces a TRS R modeling a significant part of the Java semantics (stacks, frames, objects, references, methods, heaps, integers) as well as the semantics of p. For the moment, exceptions and threads are not taken into account but they can be elegantly encoded using rewriting [16,7]. The formalization follows the structure of standard Java semantics formalizations [2,9].…”

Section: Formalization Of the Java Bytecode Semantics Using Rewritingmentioning

confidence: 99%

“…However, this subject has recently reappeared for verification purposes. In [7,16], rewriting is also used as operational semantics for Java. The verification done on the obtained rewriting system is closer to finite model-checking or to simulation, since it can only deal with finite state programs.…”

Section: Related Workmentioning

confidence: 99%

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Rewriting Approximations for Fast Prototyping of Static Analyzers

Boichut

Genet

Jensen

et al. 2007

Lecture Notes in Computer Science

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Abstract. This paper shows how to construct static analyzers using tree automata and rewriting techniques. Starting from a term rewriting system representing the operational semantics of the target programming language and given a program to analyze, we automatically construct an over-approximation of the set of reachable terms, i.e. of the program states that can be reached. The approach enables fast prototyping of static analyzers because modifying the analysis simply amounts to changing the set of rewrite rules defining the approximation. A salient feature of this approach is that the approximation is correct by construction and hence does not require an explicit correctness proof. To illustrate the framework proposed here on a realistic programming language we instantiate it with the Java Virtual Machine semantics and perform class analysis on Java bytecode programs.

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Section: Resultsmentioning

confidence: 99%

Section: Formalization Of the Java Bytecode Semantics Using Rewritingmentioning

confidence: 99%

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Rewriting Approximations for Fast Prototyping of Static Analyzers

Boichut

Genet

Jensen

et al. 2007

Lecture Notes in Computer Science

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show abstract

“…They also do not use the adapter code generation framework. On the other hand, Maude has been used to give semantics to a wide range of programming and modeling languages (see, e.g., [18,19]). Real-Time Maude is also used to analyze AADL [20] models of avionics embedded systems, but we are not aware of any translation of a synchronous real-time language into Maude or Real-Time Maude.…”

Section: Related Workmentioning

confidence: 99%

Verifying Ptolemy II Discrete-Event Models Using Real-Time Maude

Bae

Ölveczky

Feng

et al. 2009

Formal Methods and Software Engineering

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This paper shows how Ptolemy II discrete-event (DE) models can be formally analyzed using Real-Time Maude. We formalize in RealTime Maude the semantics of a subset of hierarchical Ptolemy II DE models, and explain how the code generation infrastructure of Ptolemy II has been used to automatically synthesize a Real-Time Maude verification model from a Ptolemy II design model. This enables a model-engineering process that combines the convenience of Ptolemy II DE modeling and simulation with formal verification in Real-Time Maude.

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“…In our experience, it is often possible to specify most of the semantic axioms with equations, with relatively few rules needed for truly concurrent or nondeterministic features. For example, the semantics of the JVM described in [21,19] has about 300 equations and 40 rules; and that of Java described in [19] has about 600 equations but only 15 rules. A semantics for an ML-like language with threads given in [30] has only two rules.…”

Section: Unifying Sos and Equational Semanticsmentioning

confidence: 99%

Computational Logical Frameworks and Generic Program Analysis Technologies

Meseguer

Roşu

2008

Verified Software: Theories, Tools, Experiments

Self Cite

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The technologies developed to solve the verifying compiler grand challenge should be generic, that is, not tied to a particular language but widely applicable to many languages. Such technologies should also be semantics-based, that is, based on a rigorous formal semantics of the languages.For this, a computational logical framework with efficient executability and a spectrum of meta-tools can serve as a basis on which to: (1) define the formal semantics of any programming language; and (2) develop generic program analysis techniques and tools that can be instantiated to generate powerful analysis tools for each language of interest.Not all logical frameworks can serve such purposes well. We first list some specific requirements that we think are important to properly address the grand challenge. Then we present our experience with rewriting logic as supported by the Maude system and its formal tool environment. Finally, we discuss some future directions of research. Logical Framework RequirementsBased on experience, current trends, and the basic requirements of the grand challenge problem, we believe that any logical framework serving as a computational infrastructure for the various technologies for solving the grand challenge should have at least the following features:1. good data representation capabilities, 2. support for concurrency and nondeterminism, 3. simplicity of the formalism, 4. efficient implementability, and efficient meta-tools, 5. support for reflection, 6. support for inductive reasoning, preferably with initial model semantics, 7. support for generation of proof objects, acting as correctness certificates.While proponents of a framework may claim that it has all these features, in some cases further analysis can show that it either lacks some of them, or can only "simulate" certain features in a quite artificial way. A good example is the

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Formal Analysis of Java Programs in JavaFAN

Cited by 66 publications

References 5 publications

Rewriting Approximations for Fast Prototyping of Static Analyzers

Rewriting Approximations for Fast Prototyping of Static Analyzers

Verifying Ptolemy II Discrete-Event Models Using Real-Time Maude

Computational Logical Frameworks and Generic Program Analysis Technologies

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