Data Flow Coverage for Circus-Based Testing

Cavalcanti, Ana; Gaudel, Marie-Claude

doi:10.1007/978-3-642-54804-8_29

Cited by 7 publications

(12 citation statements)

References 14 publications

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“…These approaches are usually complementary to each other. Coverage-based testing is proposed for Circus in [28]. It is worth investigating how fault-based testing can complement the coverage testing.…”

Section: Introductionmentioning

confidence: 99%

“…[22], or coverage criteria of the specification [28]. This paper addresses fault-based selection techniques.…”

mentioning

confidence: 99%

“…Therefore, we use specification traces, as defined in [45,28], to build the tests aimed at killing a mutant. In [28], specification traces are used to consider data-flow coverage, which is also based on the text of a specification.…”

mentioning

confidence: 99%

“…In [28], specification traces are used to consider data-flow coverage, which is also based on the text of a specification. While cstraces are useful for trace selection based on constraints on the traces, they do not support selection based on the text of the specification, as we explain in the sequel.…”

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confidence: 99%

“…In [28], a subset of specification traces, sptraces, is considered for the definition of tests satisfying data-flow coverage criteria, namely, the set of specification traces where the last event is an observable event. Some of the specification traces given in Figures 7 and 8 are not sptraces.…”

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confidence: 99%

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Formal mutation testing for

Alberto

Cavalcanti

Gaudel

et al. 2017

Information and Software Technology

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Context: The demand from industry for more dependable and scalable test-development mechanisms has fostered the use of formal models to guide the generation of tests. Despite many advancements having been obtained with state-based models, such as Finite State Machines (FSMs) and Input/Output Transition Systems (IOTSs), more advanced formalisms are required to specify large, state-rich, concurrent systems. Circus, a state-rich process algebra combining Z, CSP and a refinement calculus, is suitable for this; however, deriving tests from such models is accordingly more challenging. Recently, a testing theory has been stated for Circus, allowing the verification of process refinement based on exhaustive test sets. Objective: We investigate fault-based testing for refinement from Circus specifications using mutation. We seek the benefits of such techniques in test-set quality assertion and fault-based test-case selection. We target results relevant not only for Circus, but to any process algebra for refinement that combines CSP with a data language. Method: We present a formal definition for fault-based test sets, extending the Circus testing theory, and an extensive study of mutation operators for Circus. Using these results, we propose an approach to generate tests to kill mutants. Finally, we explain how prototype tool support can be obtained with the implementation of a mutant generator, a translator from Circus to CSP, and a refinement checker for CSP, and with a more sophisticated chain of tools that support the use of symbolic tests. Results: We formally characterise mutation testing for Circus, defining the exhaustive test sets that can kill a given mutant. We also provide a technique to select tests from these sets based on specification traces of the mutants. Finally, we present mutation operators that consider faults related to both reactive and data manipulation behaviour. Altogether, we define a new fault-based test-generation technique for Circus. Conclusion: We conclude that mutation testing for Circus can truly aid making test generation from state-rich model more tractable, by focussing on particular faults.

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Section: Introductionmentioning

confidence: 99%

“…[22], or coverage criteria of the specification [28]. This paper addresses fault-based selection techniques.…”

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Formal mutation testing for

Alberto

Cavalcanti

Gaudel

et al. 2017

Information and Software Technology

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Bringing RoboStar and RT-Tester Together

Cavalcanti

Miyazawa

Schulze³

et al. 2023

Lecture Notes in Computer Science

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Model-Based Robustness Testing in Event-B Using Mutation

Savary

Frappier

Leuschel

et al. 2015

Software Engineering and Formal Methods

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Abstract. Robustness testing aims at finding errors in a system under invalid conditions, such as unexpected inputs. We propose a robustness testing approach for Event-B based on specification mutation and model-based testing. We assume that a specification describes the valid inputs of a system. By applying negation rules, we mutate the precondition of events to explore invalid behaviour. Tests are generated from the mutated specification using ProB. ProB has been adapted to efficiently process mutated events. Mutated events are statically checked for satisfiability and enability using constraint satisfaction, to prune the transition search space. This has dramatically improve the performance of test generation. The approach is applied to the Java Card bytecode verifier. Large mutated specifications (containing 921 mutated events) can be easily tackled to ensure a good coverage of the robustness test space.

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Data Flow Coverage for Circus-Based Testing

Cited by 7 publications

References 14 publications

Formal mutation testing for

Formal mutation testing for

Bringing RoboStar and RT-Tester Together

Model-Based Robustness Testing in Event-B Using Mutation

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