Towards feature-oriented requirements validation for automotive systems

Zhou, Jiale; Lu, Yue; Lundqvist, Kristina; Lönn, Henrik; Karlsson, Daniel; Liwang, B.

doi:10.1109/re.2014.6912294

Cited by 15 publications

(6 citation statements)

References 14 publications

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“…Our motivation is to rely, to the largest extent possible, on practices that are already in place in many companies developing embedded systems, including our industry partner, i.e., IEE S.A. (in the following "IEE") [17], with whom we performed multiple case studies reported in this paper. In many environments like IEE, development processes are use case-driven and arXiv:1907.08490v1 [cs.SE] 19 Jul 2019 this strongly influences their requirements engineering and system testing practices. Use case specifications are widely used for communicating requirements among stakeholders and, in particular, facilitating communication with customers, while a domain model clarifies the terminology and concepts shared among all stakeholders and thus avoids misunderstandings.…”

Section: Introductionmentioning

confidence: 99%

Automatic generation of system test cases from use case specifications

Wang

Pastore

Göknil

et al. 2015

Proceedings of the 2015 International Symposium on Software Testing and Analysis

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In safety critical domains, system test cases are often derived from functional requirements in natural language (NL) and traceability between requirements and their corresponding test cases is usually mandatory. The definition of test cases is therefore time-consuming and error prone, especially so given the quickly rising complexity of embedded systems in many critical domains. Though considerable research has been devoted to automatic generation of system test cases from NL requirements, most of the proposed approaches require significant manual intervention or additional, complex behavioral modelling. This significantly hinders their applicability in practice.In this paper, we propose Use Case Modelling for System Tests Generation (UMTG), an approach that automatically generates executable system test cases from use case specifications and a domain model, the latter including a class diagram and constraints. Our rationale and motivation are that, in many environments, including that of our industry partner in the reported case study, both use case specifications and domain modelling are common and accepted practice, whereas behavioural modelling is considered a difficult and expensive exercise if it is to be complete and precise. In order to extract behavioral information from use cases and enable test automation, UMTG employs Natural Language Processing (NLP), a restricted form of use case specifications, and constraint solving.

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Section: Introductionmentioning

confidence: 99%

Automatic generation of system test cases from use case specifications

Wang

Pastore

Göknil

et al. 2015

Proceedings of the 2015 International Symposium on Software Testing and Analysis

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“…Moreover, works not using the use cases for the capture of SPL variabilities were not considered (e.g. Zhou et al (2014)). …”

Section: Discussionmentioning

confidence: 99%

Templates for textual use cases of software product lines: results from a systematic mapping study and a controlled experiment

Santos

Andrade

Neto

2015

J Softw Eng Res Dev

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Use case templates can be used to describe functional requirements of a Software Product Line. However, to the best of our knowledge, no efforts have been made to collect and summarize these existing templates and no empirical evaluation of the use cases' comprehensibility provided by these templates has been addressed yet. The contributions of this paper are twofold. First, we present a systematic mapping study about the SPL variability description using textual use cases. From this mapping, we found twelve SPL use case templates and observed the need not only for the application of these templates in real SPL but also for supporting tools. Secondly, this work presents an evaluation of the comprehensibility of SPL use cases specified in these templates through a controlled experiment with 48 volunteers. The results of this experiment show that the specification of variabilities in the steps' numeric identifiers of the textual use cases is better to the use case understanding than the other approaches identified. We also found evidence that the specification of variabilities at the end of the use cases favors the comprehension of them and the use of questions associated to the variation points in the use cases improves the understanding of use cases. We conclude that each characteristic of the existing templates has an impact on the SPL use case understanding and this should be taken into account when choosing one.

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“…RUCM is based on a template and restriction rules, reducing ambiguities and incompleteness in use cases. It has been successfully applied in many domains [33], [34], [35], [36], [37], [38], [39], [40]. This section does not distinguish between the original RUCM features and the extensions for RMCM, and we furthermore focus on misuse case specifications only.…”

Section: A Eliciting Misuse Cases With Rmcmmentioning

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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Towards feature-oriented requirements validation for automotive systems

Cited by 15 publications

References 14 publications

Automatic generation of system test cases from use case specifications

Automatic generation of system test cases from use case specifications

Templates for textual use cases of software product lines: results from a systematic mapping study and a controlled experiment

A Natural Language Programming Approach for Requirements-Based Security Testing

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