Pseudo software: A mediating instrument for modeling software requirements

Jwo, Jung-Sing; Cheng, Yu Chin

doi:10.1016/j.jss.2009.10.042

Cited by 3 publications

(2 citation statements)

References 17 publications

(19 reference statements)

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“…The use of ontologies to support different aspects of software engineering has increase in the last years. A lot of the research work done refers to the elicitation process (Al Balushi, Sampaio, & Loucopoulos, ; Couto, Ribeiro, & Campos, ; Jwo & Cheng, ; Pires et al, ) and to the specification of ontologies for intermediate products (Abebe & Tonella, ; De Graaf, Liang, Tang, Van Hage, & Van Vliet, ). Other works focus on the development of tools based on ontologies that help to support the development process (García‐Peñalvo, Colomo‐Palacios, García, & Therón, ; Henderson‐Sellers, ; Reinhartz‐Berger, Sturm, & Wand, ).…”

Section: Background and Motivationmentioning

confidence: 99%

An ontology to document a quality scheme specification of a software product

2017

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Pressman's (2010) definition of software quality is the conformance to explicitly stated functional and performance requirements, explicitly documented development standards, and implicit characteristics that are expected of all professionally developed software. The achievement of quality is a complex activity that is related with the process quality and product quality. However, still, it is not clear how product quality should apply in the development process. Frequently, the development team does not know what characteristics influence a specific entity and how these characteristics compose the quality of the product. This lack of knowledge reflects the need to define some document that serve as a valid quality specification that should be evaluated along the development process. This contribution addresses this need by introducing an ontology for document a quality scheme based on the product quality model of ISO/IEC 25010. The proposal follows this model with aims to clarify the properties that are normally present in a product and its meaning. The ontology incorporates the metric concept to represent the way in which quality should be measure. The ontology was implemented using Protégé, and it was evaluated using a set of metrics that estimate the required structural characteristics.

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Section: Background and Motivationmentioning

confidence: 99%

An ontology to document a quality scheme specification of a software product

2017

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“…In addition, they do not provide automatic ways to detect data requirements inconsistencies. Software requirements elicitation and modeling are key activities in software development, but requirements-related errors are yet a challenge [22].…”

Section: Background and Related Workmentioning

confidence: 99%

DataMock: An Agile Approach for Building Data Models from User Interface Mockups

et al. 2017

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In modern software development, much time is devoted and much attention is paid to the activity of data modeling and the translation of data models into databases. This has motivated the proposal of different approaches and tools to support this activity, such as semiautomatic approaches that generate data models from requirements artifacts using text analysis and sets of heuristics, among other techniques. However, these approaches still suffer from important limitations, including the lack of support for requirements traceability, the poor support for detecting and solving conflicts in domain-specific requirements, and the considerable effort required for manually checking the generated models. This paper introduces DataMock, an Agile approach that enables the iterative building of data models from requirements specifications, while supporting traceability and allowing inconsistencies detection in data requirements and specifications. The paper also describes Communicated by Dr. Benoit Baudry.

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