Collaborative Verification and Testing with Explicit Assumptions

Christakis, Maria; Müller, Péter; Wüstholz, Valentin

doi:10.1007/978-3-642-32759-9_13

Cited by 58 publications

(46 citation statements)

References 25 publications

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“…One active area of research is the combination of static analysis and testing, e.g. [4,9,12,14,15,18]. A direct comparison of our work with those would not be fully fair as we have different objectives.…”

Section: Related Workmentioning

confidence: 99%

A Specification Language for Static and Runtime Verification of Data and Control Properties

Ahrendt

Chimento

Pace

et al. 2015

FM 2015: Formal Methods

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Abstract. Static verification techniques can verify properties across all executions of a program, but powerful judgements are hard to achieve automatically. In contrast, runtime verification enjoys full automation, but cannot judge future and alternative runs. In this paper we present a novel approach in which data-centric and control-oriented properties may be stated in a single formalism, amenable to both static and dynamic verification techniques. We develop and formalise a specification notation, ppDATE, extending the control-flow property language used in the runtime verification tool Larva with pre/post-conditions and show how specifications written in this notation can be analysed both using the deductive theorem prover KeY and the runtime verification tool Larva. Verification is performed in two steps: KeY first partially proves the data-oriented part of the specification, simplifying the specification which is then passed on to Larva to check at runtime for the remaining parts of the specification including the control-centric aspects. We apply the approach to Mondex, an electronic purse application.

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Section: Related Workmentioning

confidence: 99%

A Specification Language for Static and Runtime Verification of Data and Control Properties

Ahrendt

Chimento

Pace

et al. 2015

FM 2015: Formal Methods

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“…In our previous work, an explicit assumption of the form assumed P as a expresses that an analysis assumed property P to hold at this point in the code without checking it [6,8,5,30]. The unique assumption identifier a may be used to refer to this explicit assumption at other program points.…”

Section: Verification Annotationsmentioning

confidence: 99%

“…As demonstrated in this section, the encoded intermediate results make it possible to ignore certain parts of the program state or even entire program paths. Our previous work has specifically shown that this instrumentation is suitable for subsequent analyses, in the context of dynamic test generation [6,8] and deductive verification [25].…”

Section: Bounding Spurious Errorsmentioning

confidence: 99%

“…Bounding the time of the analysis is easy and very useful in practice, however, the analysis results are too unpredictable for us to draw any meaningful conclusions, for instance about the number of genuine bugs. We did not evaluate how the collaboration of multiple analyses helps reduce the number of spurious errors as we have experimented with several such scenarios in our previous work [6,8,5,30].…”

Section: Joinsmentioning

confidence: 99%

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Bounded Abstract Interpretation

Christakis

Wüstholz

2016

Static Analysis

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Abstract. In practice, software engineers are only able to spend a limited amount of resources on statically analyzing their code. Such resources may refer to their available time or their tolerance for imprecision, and usually depend on when in their workflow a static analysis is run. To serve these different needs, we propose a technique that enables engineers to interactively bound a static analysis based on the available resources. When all resources are exhausted, our technique soundly records the achieved verification results with a program instrumentation. Consequently, as more resources become available, any static analysis may continue from where the previous analysis left off. Our technique is applicable to any abstract interpreter, and we have implemented it for the .NET static analyzer Clousot. Our experiments show that bounded abstract interpretation can significantly increase the performance of the analysis (by up to 8x) while also increasing the quality of the reported warnings (more definite warnings that detect genuine bugs).

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“…Tools such as DSD-Crasher [12] and our EVE [33] integrate testing and static checking to find when the errors reported by the latter are spurious. Collaborative verification [9] is also based on the combination of testing and static verification, and on the explicit formalization of the restrictions of each tool used in the combination. Two-step verification also integrates the results of different techniques, with the main purpose of improving error reporting and reducing the number of annotations needed, rather than complementing the limitations of specific techniques.…”

Section: Related Workmentioning

confidence: 99%

Program Checking with Less Hassle

Tschannen

Furia

Nordio

et al. 2014

Verified Software: Theories, Tools, Experiments

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Abstract. The simple and often imprecise specifications that programmers may write are a significant limit to a wider application of rigorous program verification techniques. Part of the reason why non-specialists find writing good specification hard is that, when verification fails, they receive little guidance as to what the causes might be, such as implementation errors or inaccurate specifications. To address these limitations, this paper presents two-step verification, a technique that combines implicit specifications, inlining, and loop unrolling to provide improved user feedback when verification fails. Two-step verification performs two independent verification attempts for each program element: one using standard modular reasoning, and another one after inlining and unrolling; comparing the outcomes of the two steps suggests which elements should be improved. Two-step verification is implemented in AutoProof, our static verifier for Eiffel programs integrated in EVE (the Eiffel Verification Environment) and available online. The Trouble with SpecsThere was a time when formal verification required heroic efforts and was the exclusive domain of a small group of visionaries. That time is now over; but formal techniques still seem a long way from becoming commonplace. If formal verification techniques are to become a standard part of the software development process-and they are-we have to understand and remove the obstacles that still prevent non-specialists from using them.A crucial issue is specification. Program correctness is a relative notion, in that a program is correct not in absolute terms but only relative to a given specification of its expected behavior; in other words, verified programs are only as good as their specification. Unfortunately, many programmers are averse to writing specifications, especially formal ones, for a variety of reasons that mostly boil down a benefit-to-effort ratio perceived as too low. Writing formal specifications may require specialized skills and experience; and the concrete benefits are dubious in environments that value productivity, assessed through simple quantitative measures, more than quality. Why should programmers subject themselves to the taxing exercise of writing specifications in addition to implementations, if there is not much in it for them other than duplicated work?

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Collaborative Verification and Testing with Explicit Assumptions

Cited by 58 publications

References 25 publications

A Specification Language for Static and Runtime Verification of Data and Control Properties

A Specification Language for Static and Runtime Verification of Data and Control Properties

Bounded Abstract Interpretation

Program Checking with Less Hassle

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