Towards an Ontology for Software Product Quality Attributes

Kayed, Ahmad; Hirzalla, Nael; Samhan, Ahmad; Al-Fayoumi, Mustafa

doi:10.1109/iciw.2009.36

Cited by 21 publications

(9 citation statements)

References 4 publications

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“…Our first word-list set, exp1, was generated using the ontology described in Kayed et al [13] . That paper constructs an ontology for software quality measurement using eighty source documents, including research papers and international standards.…”

Section: Generating Word Listsmentioning

confidence: 99%

Automated topic naming to support cross-project analysis of software maintenance activities

Hindle

Ernst

Godfrey

et al. 2011

Proceedings of the 8th Working Conference on Mining Software Repositories

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Researchers have employed a variety of techniques to extract underlying topics that relate to software development artifacts. Typically, these techniques use semi-unsupervised machine-learning algorithms to suggest candidate word-lists. However, word-lists are difficult to interpret in the absence of meaningful summary labels. Current topic modeling techniques assume manual labelling and do not use domainspecific knowledge to improve, contextualize, or describe results for the developers. We propose a solution: automated labelled topic extraction. Topics are extracted using Latent Dirichlet Allocation (LDA) from commit-log comments recovered from source control systems such as CVS and BitKeeper. These topics are given labels from a generalizable cross-project taxonomy, consisting of non-functional requirements. Our approach was evaluated with experiments and case studies on two large-scale RDBMS projects: MySQL and MaxDB. The case studies show that labelled topic extraction can produce appropriate, context-sensitive labels relevant to these projects, which provides fresh insight into their evolving software development activities.

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Section: Generating Word Listsmentioning

confidence: 99%

Automated topic naming to support cross-project analysis of software maintenance activities

Hindle

Ernst

Godfrey

et al. 2011

Proceedings of the 8th Working Conference on Mining Software Repositories

View full text Add to dashboard Cite

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“…Table A1 (in appendix) presents the secondary quality attributes of GoF and POSA1 patterns after normalization. The quality attributes used in our analysis can be referred from [1,13,36,48]. Following are some of the conclusions that can be inferred from Figure 7:…”

Section: Pattern To Quality Attribute Relationshipmentioning

confidence: 90%

Pattern-oriented knowledge model for architecture design

Kumar

Prabhakar

2010

Proceedings of the 17th Conference on Pattern Languages of Programs

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Abstract. Software design patterns document the most recommended solutions to recurring design problems. Selection of the best design pattern in a given context involves analysis of available alternatives, which is a knowledge-intensive task. Pattern knowledge overload (due to the large number of design patterns) makes such analysis difficult. A knowledge base to generate available alternatives can alleviate the problem. In this paper, we propose a pattern-oriented knowledge model which considers four dimensions of the pattern knowledge space: Pattern to Tactic relationship, Pattern to Pattern relationship, Pattern to Quality-attribute relationship and Pattern to Application-type relationship. We perform analysis of these relationships for patterns in the two popular pattern catalogues viz GoF and POSA1.

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“…Several contributions address the topic of constructing a common set of concepts that are incorporated in quality models. A study [11] that employs extraction of a condensed model for software product quality attributes is using the frequency and association of terminology and concepts that appear in different sources such as models, standards and related documents to software quality. Based on this, an ontology involving semantics of quality attributes is built.…”

Section: Sq Modelsmentioning

confidence: 99%

Evolution of Software Quality Models from an NLP Perspective

Lupsa

Motogna

Ciuciu

2020

Studia UBB Informatica

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The research question addressed in this study is to analyze the evolution of software quality models, and to investigate the similarities between the most known quality models. The models are decomposed according to their inherent structure, then are analyzed based on their subcharacteristics, at several levels. The focus of the study is on the lexical analysis of software quality models based on natural language processing, with the purpose to highlight the similarities in software quality models. In the end, the current software quality model ISO25010 is compared with all previous ones.

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Towards an Ontology for Software Product Quality Attributes

Cited by 21 publications

References 4 publications

Automated topic naming to support cross-project analysis of software maintenance activities

Automated topic naming to support cross-project analysis of software maintenance activities

Pattern-oriented knowledge model for architecture design

Evolution of Software Quality Models from an NLP Perspective

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