From Natural Language Requirements to Formal Specification Using an Ontology

Sadoun, Driss; Dubois, Catherine; Ghamri‐Doudane, Yacine; Grau, Brigitte

doi:10.1109/ictai.2013.116

Cited by 18 publications

(14 citation statements)

References 8 publications

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“…It is simplistic and graphical hence provides a better understanding of the specification. Ontology population based approach [9] as discussed in the previous section is useful for various kinds of conflict Identification as it relies on both syntactic & semantic knowledge. Another advantage of using this is that it is not domain specific.…”

Section: Discussionmentioning

confidence: 99%

“…Sadoun et.al [9] proposes an ontology population based approach to transform NL requirements to formal specifications. This approach is based on instance property identification using extracting rules.…”

Section: Ontology Based Approachmentioning

confidence: 99%

“…Once property instances are identified, their concept instances are classified & identified. The author [9] uses OWL which applies its semantic property on individuals involved in the population to infer more knowledge & reasoning. Figure 3.…”

Section: Ontology Based Approachmentioning

confidence: 99%

“…For better clarity and more fruitful result it is suggested that for a wholesome framework, rule base can be additionally incorporated that can aid in better linguistic analysis hence can provide a platform for fertile formal specification of loosely binded natural language specification. Latest trends in this subject is inclined towards using NLP techniques [5,8,9,14,15] such as POS Tagging, Parsing etc not just to model and extract UML diagrams but can be used to detect conflicts in requirements. This in combination with Supervised and unsupervised Machine learning can be used to make algorithms more accurate and prolific.…”

Section: Conclusion and Future Scopementioning

confidence: 99%

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Analysis of Modeling Techniques used for Translating Natural Language Specification into Formal Software Requirements

Sandhu¹

2015

IJCA

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The prerequisite to any software development process is to first capture and understand the intended behaviour of the software solution based on the gathered requirements and understanding the constraints related to it. Hence requirement engineering becomes a very crucial step. Requirements are specified in Natural language by the user and it has to be translated to a formal representation for automating the requirement engineering process and also to uncover inconsistencies, ambiguities and perform conflict management in software requirements. This paper studies some existing models used for converting loosely specified natural language to a formal linguistic construct for software requirements. Observations on various existing approaches in this context are made.

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Section: Discussionmentioning

confidence: 99%

Section: Ontology Based Approachmentioning

confidence: 99%

Section: Ontology Based Approachmentioning

confidence: 99%

Section: Conclusion and Future Scopementioning

confidence: 99%

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Analysis of Modeling Techniques used for Translating Natural Language Specification into Formal Software Requirements

Sandhu¹

2015

IJCA

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“…We propose an OWL-DL ontology based on description logics as an intermediate representation. We use this ontology to guide the automatic identification of behavioural rules from NL requirements analysis and to represent them formally [8]. Behavioural rules are represented in the ontology in order to be transformed into a formal specification language.…”

Section: Introductionmentioning

confidence: 99%

Formal Rule Representation and Verification from Natural Language Requirements Using an Ontology

Sadoun

Dubois

Ghamri‐Doudane

et al. 2014

Lecture Notes in Computer Science

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The development of a system is usually based on shared and accepted requirements. Hence, to be largely understood by the stakeholders, requirements are often written in natural language (NL). However, checking requirements completeness and consistency requires having them in a formal form. In this article, we focus on user requirements describing a system behaviour, i.e. its behavioural rules. We show how to transform behavioural rules identified from NL requirements and represented within an OWL ontology into the formal specification language Maude. The OWL ontology represents the generic behaviour of a system and allow us to bridge the gap between informal and formal languages and to automate the transformation of NL rules into a Maude specification.

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Automated generation of terminological dictionary from textual business rules

Haj

Balouki

Gadi

2021

J Software Evolu Process

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To support decision making, organizations tend to operate according to Business Rules, which are usually represented in a natural language format easily understood by all intervenors. According to the business rules manifesto by the Business Rules Group (OMG), rules build on facts, and facts build on concepts as expressed by terms. To avoid ambiguity and misunderstanding, the standardization of the terminology used at the business level becomes a persistent need. However, doing so manually is error prone and time consuming, especially that the Business Rules are the subject of continuous updating. In this paper, we present an automated approach to generate the Business Vocabulary from textual statements of Business Rules. Our approach is distinguished from existing works in that it extracts the Terminological Dictionary as described by the Semantic of Business Vocabulary and Rules (SBVR) standard to provide a more comprehensive meaning for each concept. Accordingly, an in‐depth Natural Language Processing (NLP) is used to extract not only flat list of terms and relations, but also extra specifications and implicit knowledge. With a satisfactory result, our approach has proved its capability to automatically generate the SBVR Terminological Dictionary from large number of natural language business rules statements.

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From Natural Language Requirements to Formal Specification Using an Ontology

Cited by 18 publications

References 8 publications

Analysis of Modeling Techniques used for Translating Natural Language Specification into Formal Software Requirements

Analysis of Modeling Techniques used for Translating Natural Language Specification into Formal Software Requirements

Formal Rule Representation and Verification from Natural Language Requirements Using an Ontology

Automated generation of terminological dictionary from textual business rules

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