Exploiting refactoring in formal verification

Yin, Xiang; Knight, John; Weimer, Westley

doi:10.1109/dsn.2009.5270355

Cited by 13 publications

(13 citation statements)

References 8 publications

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“…The manual annotation of AES with sufficient invariants to admit machine-checked full formal verification was a significant undertaking involving hours of tool-assisted manual effort [25], [26]. Annotating pre-and postconditions and loop invariants has not been solved in general and is known to be a key bottleneck in approaches based on axiomatic semantics [27].…”

Section: B Results Qualitymentioning

confidence: 99%

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Using dynamic analysis to discover polynomial and array invariants

Nguyen

Kapur

Weimer

et al. 2012

2012 34th International Conference on Software Engineering (ICSE)

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Section: B Results Qualitymentioning

confidence: 99%

“…The second benchmark, AES , is an annotated AES implementation from Yin et al [25]. It exemplifies a realworld security-critical application and contains nontrivial array invariants.…”

Section: A Programsmentioning

confidence: 99%

Using dynamic analysis to discover polynomial and array invariants

Nguyen

Kapur

Weimer

et al. 2012

2012 34th International Conference on Software Engineering (ICSE)

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“…Other possibilities for integrating sound program analysis techniques into unsound approaches for program repair include automatically generating proofs for repairs in the context of proof carrying code (Necula 1997), or automatically mutating code in a semantics-preserving way with a goal of simplifying automatic verification (because equisatisfiable verification conditions are not always equally easy to discharge) (Yin et al 2009). These potential applications could lead to higher-quality repairs as well as repairs that are easier for humans to validate and trust.…”

Section: Combining Unsound Repair Algorithms and Formal Methodsmentioning

confidence: 99%

Current challenges in automatic software repair

Goues¹,

Forrest²,

Weimer³

2013

Software Qual J

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156

105

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The abundance of defects in existing software systems is unsustainable. Addressing them is a dominant cost of software maintenance, which in turn dominates the life cycle cost of a system. Recent research has made significant progress on the problem of automatic program repair, using techniques such as evolutionary computation, instrumentation and run-time monitoring, and sound synthesis with respect to a specification. This article serves three purposes. First, we review current work on evolutionary computation approaches, focusing on GenProg, which uses genetic programming to evolve a patch to a particular bug. We summarize algorithmic improvements and recent experimental results. Second, we review related work in the rapidly growing subfield of automatic program repair. Finally, we outline important open research challenges that we believe should guide future research in the area.

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“…While this and other works, e.g. Garrido & Meseguer (2006), Carvalho Júnior et al (2007, Ubayashi et al (2008) and Yin et al (2009), show that verification is possible in principle, practical verification of refactoring engines for Haskell or Erlang remains some way off, and is predicated on the mechanisation of the static and dynamic semantics as well as the module structure and type systems of the languages in question. 10 A generic general-purpose refactoring tool?…”

Section: Trust and Verificationmentioning

confidence: 97%

Refactoring tools for functional languages

Thompson¹,

Li²

2013

J. Funct. Prog.

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Refactoring is the process of changing the design of a program without changing what it does. Typical refactorings, such as function extraction and generalisation, are intended to make a program more amenable to extension, more comprehensible and so on. Refactorings differ from other sorts of program transformation in being applied to source code, rather than to a 'core' language within a compiler, and also in having an effect across a code base, rather than to a single function definition, say. Because of this, there is a need to give automated support to the process. This paper reflects on our experience of building tools to refactor functional programs written in Haskell (HaRe) and Erlang (Wrangler). We begin by discussing what refactoring means for functional programming languages, first in theory, and then in the context of a larger example. Next, we address system design and details of system implementation as well as contrasting the style of refactoring and tooling for Haskell and Erlang. Building both tools led to reflections about what particular refactorings mean, as well as requiring analyses of various kinds, and we discuss both of these. We also discuss various extensions to the core tools, including integrating the tools with test frameworks; facilities for detecting and eliminating code clones; and facilities to make the systems extensible by users. We then reflect on our work by drawing some general conclusions, some of which apply particularly to functional languages, while many others are of general value.

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Exploiting refactoring in formal verification

Abstract: In previous work, we introduced

Cited by 13 publications

References 8 publications

Using dynamic analysis to discover polynomial and array invariants

Using dynamic analysis to discover polynomial and array invariants

Current challenges in automatic software repair

Refactoring tools for functional languages

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