Parsed use case descriptions as a basis for object-oriented class model generation

Elbendak, Mosa; Vickers, Paul; Rossiter, Nick

doi:10.1016/j.jss.2011.02.025

Cited by 40 publications

(24 citation statements)

References 16 publications

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“…The target is models and UML diagrams, for instance, creation of use case diagrams [21] and UML Activity Diagrams using identification of simple verbal sentences [22] from textual requirements in Arabic. UML class diagrams from textual requirements [23], and from use case descriptions [24] are created in English. Researchers also analyse textual user requirements in natural language and requirements used by engineering diagrams to create the Use Case Path model, the Hybrid Activity Diagram model and the Domain model [25].…”

Section: Related Workmentioning

confidence: 99%

Extracting TFM Core Elements From Use Case Scenarios by Processing Structure and Text in Natural Language

Nazaruka

Osis

Gribermane

2019

Applied Computer Systems

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Extracting core elements of Topological Functioning Model (TFM) from use case scenarios requires processing of both structure and natural language constructs in use case step descriptions. The processing steps are discussed in the present paper. Analysis of natural language constructs is based on outcomes provided by Stanford CoreNLP. Stanford CoreNLP is the Natural Language Processing pipeline that allows analysing text at paragraph, sentence and word levels. The proposed technique allows extracting actions, objects, results, preconditions, post-conditions and executors of the functional features, as well as cause-effect relations between them. However, accuracy of it is dependent on the used language constructs and accuracy of specification of event flows. The analysis of the results allows concluding that even use case specifications require the use of rigor, or even uniform, structure of paths and sentences as well as awareness of the possible parsing errors.

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Section: Related Workmentioning

confidence: 99%

Extracting TFM Core Elements From Use Case Scenarios by Processing Structure and Text in Natural Language

Nazaruka

Osis

Gribermane

2019

Applied Computer Systems

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“…To validate their approach the authors implemented a tool named ABCD. Elbendak et al [8] present a tool, Class-Gen, which can partially automate the identification of objects/classes from NL requirements specifications for object identification. Ibrahim et al [11] propose a method and a tool to facilitate requirements analysis process and class diagram extraction from textual requirements supporting NLP techniques.…”

Section: Related Workmentioning

confidence: 99%

“…The transition from requirements expressed in NL to a domain model is an important step to obtain a precise and analyzable specification [20]. Automated model extraction from NL requirements has been studied for a long time, with a large body of literature already existing in the area such as [7], [8], [11], [14], [18], [21].…”

Section: Introductionmentioning

confidence: 99%

Assessing the Performance of Automated Model Extraction Rules

Echeverría

Pérez

Pastor

et al. 2018

Lecture Notes in Information Systems and Organisation

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Automated Model Extraction Rules take as input requirements (in natural language) to generate domain models. Despite the existing work on these rules, there is a lack of evaluations in industrial settings. To address this gap, we conduct an evaluation in an industrial context, reporting the extraction rules that are triggered to create a model from requirements and their frequency. We also assess the performance in terms of recall, precision and F-measure of the generated model compared to the models created by domain experts of our industrial partner. Results enable us to identify new research directions to push forward automated model extraction rules: the inclusion of new knowledge sources as input for the extraction rules, and the development of specific experiments to evaluate the understanding of the generated models.

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“…Therefore, the kind of automatic support to provide for requirements formalization, as well as how to provide it, is a crucial problem to be solved in order for software industry to benefit from the formal specification technique. Compared with formal notation, natural language is easier to use and a number of researchers are devoted to automatic or semi-automatic transformation of informal descriptions into formal specifications [3]- [5]. However, most of these transformation methods largely depend on the Natural Language Processing technique which is still facing the problem of the great amount of ambiguity issues at every linguistic level of natural language [5].…”

Section: Introductionmentioning

confidence: 99%

“…Compared with formal notation, natural language is easier to use and a number of researchers are devoted to automatic or semi-automatic transformation of informal descriptions into formal specifications [3]- [5]. However, most of these transformation methods largely depend on the Natural Language Processing technique which is still facing the problem of the great amount of ambiguity issues at every linguistic level of natural language [5]. Although Controlled Natural Languages are proposed to reduce these ambiguities to some extent by restricting the grammar and vocabulary [6], [7], they need to be studied and their completeness is hard to guarantee.…”

Section: Introductionmentioning

confidence: 99%

Computer-Aided Formalization of Requirements Based on Patterns

Wang

Liu

2014

IEICE Trans. Inf. & Syst.

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SUMMARYFormalizing requirements in formal specifications is an effective way to deepen the understanding of the envisioned system and reduce ambiguities in the original requirements. However, it requires mathematical sophistication and considerable experience in using formal notations, which remains a challenge to many practitioners. To handle this challenge, this paper describes a pattern-based approach to facilitate the formalization of requirements. In this approach, a pattern system is predefined to guide requirements formalization where each pattern provides a specific solution for formalizing one kind of function into a formal expression. All of the patterns are classified and organized into a hierarchical structure according to the functions they can be used to formalize. The distinct characteristic of our approach is that all of the patterns are stored on computer as knowledge for creating effective guidance to facilitate the developer in requirements formalization; they are "understood" only by the computer but transparent to the developer. We also describe a prototype tool that supports the approach. It adopts Hierarchical Finite State Machine (HFSM) to represent the pattern knowledge and implements an algorithm for applying it to assist requirements formalization. Two experiments on the tool are presented to demonstrate the effectiveness of the approach.

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Parsed use case descriptions as a basis for object-oriented class model generation

Cited by 40 publications

References 16 publications

Extracting TFM Core Elements From Use Case Scenarios by Processing Structure and Text in Natural Language

Extracting TFM Core Elements From Use Case Scenarios by Processing Structure and Text in Natural Language

Assessing the Performance of Automated Model Extraction Rules

Computer-Aided Formalization of Requirements Based on Patterns

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