NAT2TEST Tool: From Natural Language Requirements to Test Cases Based on CSP

Carvalho, Gustavo; Barros, Flávia A.; Carvalho, Ana; Cavalcanti, Ana; Mota, Alexandre; Sampaio, Augusto

doi:10.1007/978-3-319-22969-0_20

Cited by 18 publications

(21 citation statements)

References 9 publications

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“…In this way, the same models used to reason about specifications and designs can also be used in testing. CSP models can be automatically generated, for example, from diagrammatic domain-specific models for (control) systems, from Java programs [8]- [10], and even from natural language requirements [11].…”

Section: Introductionmentioning

confidence: 99%

A Suspension-Trace Semantics for CSP

Cavalcanti

Hierons

Nogueira

et al. 2016

2016 10th International Symposium on Theoretical Aspects of Software Engineering (TASE)

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Abstract-CSP is well established as a process algebra for refinement. Most refinement relations for CSP do not differentiate between inputs and outputs, and so are unsuitable for testing. This paper provides CSP with a denotational semantics based on suspension traces; it gives the traditional CSP operators a novel view, catering for the differences between inputs and outputs. We identify healthiness conditions for the suspension-traces model and include a treatment of termination not contemplated in the context of input-output labelled transition systems. Using our suspension-traces semantics, we provide for CSP a characterisation of the conformance relation ioco, which is widely used in testing. Finally, we propose a strategy to mechanise the verification of conformance according to ioco and suspensiontrace refinement using CSP tools. This work provides the basis for a theory of testing for CSP with inputs and outputs, and opens up the possibility of studying algebraic laws and compositional reasoning techniques based on ioco. Ultimately, it contributes to making CSP models useful for both design and testing of systems.

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Section: Introductionmentioning

confidence: 99%

A Suspension-Trace Semantics for CSP

Cavalcanti

Hierons

Nogueira

et al. 2016

2016 10th International Symposium on Theoretical Aspects of Software Engineering (TASE)

Self Cite

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“…Comparatively to [1], their approach does not restrict the requirements to be written in a controlled language. From requirement sentences, several ontology concepts are inferred (i.e.…”

Section: Background and Related Workmentioning

confidence: 99%

“…In software engineering, Carvalho [1] has shown how to combine NLP and formal methods to automatically generate test cases from the written software requirements. The work proposes a framework to process and transform the requirement texts into a formalism called data flow reactive system (DFRS), which then is used to generate the test cases.…”

Section: Background and Related Workmentioning

confidence: 99%

“…In Carvalho's approach, these case frames are transformed into the DFRS formalism and then translated into different target formal methods for verification to generate candidates for test cases. For example, the process algebra CSP [14] was used as the basis for generating test cases in [1]. Once the CSP specifications have been generated, the model checker FDR [15] can check the traces from the refinement property which then serve as test scenarios.…”

Section: Background and Related Workmentioning

confidence: 99%

“…Inspired by the approach done by Carvalho et al [1] for software requirements, we explore more complex cases of controlled natural language (CNL) as used in therapy algorithms. From each sentence in the therapy algorithm we automatically generate a parse tree and derive case frames.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Formal Verification of CNL Health Recommendations

Rahman

Bowles

2017

Lecture Notes in Computer Science

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Abstract. Clinical texts, such as therapy algorithms, are often described in natural language and may include hidden inconsistencies, gaps and potential deadlocks. In this paper, we propose an approach to identify such problems with formal verification. From each sentence in the therapy algorithm we automatically generate a parse tree and derive case frames. From the case frames we construct a state-based representation (in our case a timed automaton) and use a model checker (here UPPAAL) to verify the model. Throughout the paper we use an example of the algorithm for blood glucose lowering therapy in adults with type 2 diabetes to illustrate our approach.

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