Interactive Testing with HOL-TestGen

Brucker, Achim D.; Wolff, Burkhart

doi:10.1007/11759744_7

Cited by 14 publications

(8 citation statements)

References 10 publications

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“…Applying proof assistants to testing has first been advocated in [3]. In [4], the same authors present an integrated testing framework with Isabelle/HOL at its core, which allows for test strategy elaboration (a strategy is called a test theorem in [4]), fault coverage proof, test case and test data generation in the same tool.…”

Section: Related Workmentioning

confidence: 99%

“…Following the depicted strategy, we first prove that it is sufficient to search for minimal sequences to failures extending a deterministic state cover of M 1 (1). Next, we show that a value calculated by the LB function in the algorithm is a valid lower bound on |M 2 | (2) under certain assumptions, which are proven to be met by minimal sequences to failures (3). Additionally, we show that if an input sequence is not contained in T S, then either T S.Ω uncovers a failure or the lower bound for any reaction of M 2 to that input sequence exceeds m (4).…”

Section: Proof Strategymentioning

confidence: 99%

“…The test strategy uses an adaptive state counting approach to generate finite test suites guaranteeing complete fault coverage under the assumption of an upper bound for the number of states contained in the (unknown) observable, minimised FSM representing the SUT behaviour. In many situations, this results in significantly fewer test cases than the well-known "brute force" strategy based on product FSMs 3 , which requires O(a mn ) test cases 4 to guarantee full fault coverage.…”

Section: Introductionmentioning

confidence: 99%

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A Mechanised Proof of an Adaptive State Counting Algorithm

Sachtleben

Hierons

Wei

et al. 2019

Testing Software and Systems

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In this paper it is demonstrated that the capabilities of stateof-the-art proof assistant tools are sufficient to present mechanised and, at the same time, human-readable proofs establishing completeness properties of test methods and the correctness of associated test generation algorithms. To this end, the well-known Isabelle/HOL proof assistant is used to mechanically verify a complete test theory elaborated by the second author for checking the reduction conformance relation between a possibly nondeterministic finite state machine (FSM) serving as reference model and an implementation whose behaviour can also be represented by an FSM. The formalisation also helps to clarify an ambiguity in the original test generation algorithm which was specified in natural language and could be misinterpreted in a way leading to insufficient fault coverage.

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Section: Related Workmentioning

confidence: 99%

Section: Proof Strategymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Mechanised Proof of an Adaptive State Counting Algorithm

Sachtleben

Hierons

Wei

et al. 2019

Testing Software and Systems

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“…-Perhaps the most striking trend is that deductive verification is emerging as a base technology. It is not only employed for correctness proofs, but in automatic test generation [19,34,30,10], and bug finding [50,36]. Among the state of the art efforts is the KeY tool [2], which it is close to complete coverage of the Java programming language [9].…”

Section: Static Verification Of Software Principlesmentioning

confidence: 99%

A Unified Approach for Static and Runtime Verification: Framework and Applications

Ahrendt

Pace

Schneider

2012

Leveraging Applications of Formal Methods, Verification and Validation. Technologies for Mastering Change

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Abstract. Static verification of software is becoming ever more effective and efficient. Still, static techniques either have high precision, in which case powerful judgements are hard to achieve automatically, or they use abstractions supporting increased automation, but possibly losing important aspects of the concrete system in the process. Runtime verification has complementary strengths and weaknesses. It combines full precision of the model (including the real deployment environment) with full automation, but cannot judge future and alternative runs. Another drawback of runtime verification can be the computational overhead of monitoring the running system which, although typically not very high, can still be prohibitive in certain settings. In this paper we propose a framework to combine static analysis techniques and runtime verification with the aim of getting the best of both techniques. In particular, we discuss an instantiation of our framework for the deductive theorem prover KeY, and the runtime verification tool Larva. Apart from combining static and dynamic verification, this approach also combines the data centric analysis of KeY with the control centric analysis of Larva. An advantage of the approach is that, through the use of a single specification which can be used by both analysis techniques, expensive parts of the analysis could be moved to the static phase, allowing the runtime monitor to make significant assumptions, dropping parts of expensive checks at runtime. We also discuss specific applications of our approach.

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“…Even if the area of formal verification made tremendous progress and provided powerful tools in the last decade or so, these methods are still rather heavy for mainstream usage. However, along with these developments there emerged various lightweight formal methods, where formal verification is used as a base technology for a more lightweight purpose, like automated test generation [6,14,11,2]. (In the remainder of the paper, we will simply say 'verification' when referring to 'formal verification', in particular also when using the phrase 'verification based test generation'.…”

Section: Introductionmentioning

confidence: 99%

Real-time Java API specifications for high coverage test generation

Ahrendt

Mostowski

Paganelli

2012

Proceedings of the 10th International Workshop on Java Technologies for Real-Time and Embedded Systems

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We present the test case generation method and tool KeY-TestGen in the context of real-time Java applications and libraries. The generated tests feature strong coverage criteria, like the Modified Condition/Decision Criterion, by construction. This is achieved by basing the test generation on formal verification techniques, namely the KeY system for Java source code verification. Moreover, we present formal specifications for the classes and methods in the real-time Java API. These specifications are used for symbolic execution when generating tests for real-time Java applications, and for oracle construction when generating tests for realtime Java library implementations. The latter application exhibited a mismatch between a commercial library implementation and the official RTSJ documentation. Even if there is a rationale behind this particular inconsistency, it demonstrates the effectiveness of our method on production code.

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Interactive Testing with HOL-TestGen

Cited by 14 publications

References 10 publications

A Mechanised Proof of an Adaptive State Counting Algorithm

A Mechanised Proof of an Adaptive State Counting Algorithm

A Unified Approach for Static and Runtime Verification: Framework and Applications

Real-time Java API specifications for high coverage test generation

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