<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.gif" overflow="scroll"><mml:msub><mml:mrow><mml:mtext>NAT2TEST</mml:mtext></mml:mrow><mml:mrow><mml:mi mathvariant="italic">SCR</mml:mi></mml:mrow></mml:msub></mml:math>: Test case generation from natural language requirements based on SCR specifications

Carvalho, Gustavo; Falcão, Diogo; Barros, Flávia A.; Sampaio, Augusto; Mota, Alexandre; Motta, Leonardo; Blackburn, Mark

doi:10.1016/j.scico.2014.06.007

Cited by 35 publications

(10 citation statements)

References 27 publications

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“…There are approaches generating functional system test cases from NL requirements [16], [17], [18], [19]. However, these approaches can be adopted in the context of security functional testing, but not security vulnerability testing since they generate test cases only for the intended behavior of the system.…”

Section: Related Workmentioning

confidence: 99%

MCP: A Security Testing Tool Driven by Requirements

Pastore

Göknil

et al. 2019

2019 IEEE/ACM 41st International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)

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We present MCP, a tool for automatically generating executable security test cases from misuse case specifications in natural language (i.e., use case specifications capturing the behavior of malicious users). MCP relies on Natural Language Processing (NLP), a restricted form of misuse case specifications, and a test driver API implementing basic utility functions for security testing. NLP is used to identify the activities performed by the malicious user and the control flow of misuse case specifications. MCP matches the malicious user's activities to the methods of the provided test driver API in order to generate executable security test cases that perform the activities described in the misuse case specifications. MCP has been successfully evaluated on an industrial case study.

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Section: Related Workmentioning

confidence: 99%

MCP: A Security Testing Tool Driven by Requirements

Pastore

Göknil

et al. 2019

2019 IEEE/ACM 41st International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)

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“…There are approaches that generate functional system test cases from NL requirements (e.g., [19], [20], [21], [22], [23]). For instance, Wang et al [21], [22] automatically generate functional test cases from use case specifications written in RUCM.…”

Section: Related Workmentioning

confidence: 99%

“…Unfortunately, engineers tend to avoid such models because of the costs related to their development and maintenance, especially in contexts where system requirements in Natural Language (NL) are already available. There are approaches that generate functional system test cases from NL requirements [19], [20], [21], [22], [23]. However, these approaches can be adopted in the context of security functional testing, but not security vulnerability testing since they generate test cases only for the intended behavior of the system.…”

Section: Introductionmentioning

confidence: 99%

A Natural Language Programming Approach for Requirements-Based Security Testing

Pastore

Göknil

et al. 2018

2018 IEEE 29th International Symposium on Software Reliability Engineering (ISSRE)

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To facilitate communication among stakeholders, software security requirements are typically written in natural language and capture both positive requirements (i.e., what the system is supposed to do to ensure security) and negative requirements (i.e., undesirable behavior undermining security). In this paper, we tackle the problem of automatically generating executable security test cases from security requirements in natural language (NL). More precisely, since existing approaches for the generation of test cases from NL requirements verify only positive requirements, we focus on the problem of generating test cases from negative requirements. We propose, apply and assess Misuse Case Programming (MCP), an approach that automatically generates security test cases from misuse case specifications (i.e., use case specifications capturing the behavior of malicious users). MCP relies on natural language processing techniques to extract the concepts (e.g., inputs and activities) appearing in requirements specifications and generates executable test cases by matching the extracted concepts to the members of a provided test driver API. MCP has been evaluated in an industrial case study, which provides initial evidence of the feasibility and benefits of the approach.

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“…However to support a model based approach to development these NL or CNL specifications would have to be converted into models. In [1], NL requirements specifications are first translated to CNL . Natural language processing techniques are then used to generate Software Cost Reduction (SCR) textual models for model based testing.…”

Section: Problem and Motivationmentioning

confidence: 99%

A textual domain specific language for requirement modelling

Olajubu

2015

Proceedings of the 2015 10th Joint Meeting on Foundations of Software Engineering

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Requirement specification is usually done with a combination of Natural Language (NL) and informal diagrams. Modelling approaches to support requirement engineering activities have involved a combination of text and graphical models. In this work, a textual domain specific modelling notation for requirement specification is presented. How certain requirement attributes are addressed using this notation is also described.

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NAT2TESTSCR: Test case generation from natural language requirements based on SCR specifications

Cited by 35 publications

References 27 publications

MCP: A Security Testing Tool Driven by Requirements

MCP: A Security Testing Tool Driven by Requirements

A Natural Language Programming Approach for Requirements-Based Security Testing

A textual domain specific language for requirement modelling

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