A requirements engineering methodology combining models and controlled natural language

Fockel, Markus; Holtmann, Jörg

doi:10.1109/modre.2014.6890827

Cited by 25 publications

(13 citation statements)

References 20 publications

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“…Holtmann et al proposed a semiautomatic method for establishing and maintaining requirement traceability in the process of automated development based on the CNL requirement specification method [50], [68], [69]. Meanwhile, Yue et al realized an RUCM tools-aToucan [52]; it can automatically generate a UML analysis model and automatically establish trace links between model elements of the use case model and the generated analysis model.…”

Section: B Automated Traceabilitymentioning

confidence: 99%

An Approach to Generate the Traceability Between Restricted Natural Language Requirements and AADL Models

Wang¹,

Yang²,

Huang³

et al. 2020

IEEE Trans. Rel.

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Requirements traceability is broadly recognized as a critical element of any rigorous software development process, especially for building safety-critical software (SCS) systems. Modeldriven development (MDD) is increasingly used to develop SCS in many domains, such as automotive and aerospace. MDD provides new opportunities for establishing traceability links through modeling and model transformations. Architecture Analysis and Design Language (AADL) is a standardized architecture description language for embedded systems, which is widely used in avionics and aerospace industries to model safety-critical applications. However, there is a big challenge to automatically establish the traceability links between requirements and AADL models in the context of MDD, because requirements are mostly written as free natural language texts, which are often ambiguous and difficult to be processed automatically. To bridge the gap between natural language requirements (NLRs) and AADL models, we propose an approach to generate the traceability links between NLRs and AADL models. First, we propose a requirement modeling method based on the restricted natural language, which is named as RM-RNL. The RM-RNL can eliminate the ambiguity of NLRs and barely change engineers' habits of requirement specification. Second, we present a method to automatically generate the initial AADL models from the RM-RNLs and to automatically establish traceability links between the elements of the RM-RNL and the generated AADL models. Third, we refine the initial AADL models through patterns to achieve the change of requirements and traceability links. Finally, we demonstrate the effectiveness of our approach with industrial case studies and evaluation experiments.

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Section: B Automated Traceabilitymentioning

confidence: 99%

An Approach to Generate the Traceability Between Restricted Natural Language Requirements and AADL Models

Wang¹,

Yang²,

Huang³

et al. 2020

IEEE Trans. Rel.

View full text Add to dashboard Cite

show abstract

“…For instance, Maiden et al [7] use i* models to derive requirements and De Landtsheer et al [21] propose a similar approach for the KAOS goal-oriented method. Fockel and Holtmann [22] present a model-driven RE approach with tool support that provides synchronisation capabilities for the applied RE models and their textual representations. Still, these approaches are specialised to specific techniques during requirements elicitation and management.…”

Section: A Possible Solutionsmentioning

confidence: 99%

A Case Study on a Specification Approach Using Activity Diagrams in Requirements Documents

Beckmann¹,

Vogelsang²,

Reuter³

2017

2017 IEEE 25th International Requirements Engineering Conference (RE)

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Rising complexity of systems has long been a major challenge in requirements engineering. This manifests in more extensive and harder to understand requirements documents. At the Daimler AG, an approach is applied that combines the use of activity diagrams with natural language specifications to specify system functions. The approach starts with an activity diagram that is created to get an early overview. The contained information is then transferred to a textual requirements document, where details are added and the behavior is refined. While the approach aims to reduce efforts needed to understand a system's behavior, the application of the approach itself causes new challenges on its own. By examining existing specifications at Daimler, we identified nine categories of inconsistencies and deviations between activity diagrams and their textual representations. In a case study, we examined one system in detail to assess how often these occur. In a follow-up survey, we presented instances of the categories to different stakeholders of the system and let them asses the categories regarding their severity. Our analysis indicates that a coexistence of textual and graphical representations of models without proper tool support results in inconsistencies and deviations that may cause severe maintenance costs or even provoke faults in subsequent development steps.

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“…The authors of [2] propose a model driven methodology for requirements engineering that integrate the use of requirement models with CNL specifications. The methodology aims to combine the advantages of NL-based and model based documentation formats through bidirectional model transformations.…”

Section: Related Workmentioning

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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A requirements engineering methodology combining models and controlled natural language

Cited by 25 publications

References 20 publications

An Approach to Generate the Traceability Between Restricted Natural Language Requirements and AADL Models

An Approach to Generate the Traceability Between Restricted Natural Language Requirements and AADL Models

A Case Study on a Specification Approach Using Activity Diagrams in Requirements Documents

A textual domain specific language for requirement modelling

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