Towards a consistent terminology for software measurement

García, Félix; Bertoa, Manuel F.; Calero, Coral; Vallecillo, Antonio; Ruíz, Francisco; Piattini, Mario; Genero, Marcela

doi:10.1016/j.infsof.2005.07.001

Cited by 147 publications

(125 citation statements)

References 8 publications

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“…For instance, cutting down the software engineering terminology to those development processes actually used. Thus, we did not find a satisfactory ontology among the plethora of those somehow related to software development (see e.g., [1,15,13,20,19] and [5] for further references), as they were missing the domain specific parts. Moreover, we were not able to combine several ontologies on different domains to get what we needed, as merging the interesting ontologies would have produced a too large result and required careful work to avoid duplicates of concepts on the overlapping areas.…”

Section: Ontologymentioning

confidence: 99%

Gesper: Support to Capitalize on Experience in a Network of SMEs

Cerioli

Lagorio

Morten

et al. 2008

Communications in Computer and Information Science

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Abstract. Small and medium enterprises (SMEs) are the most affected by the exponentially increasing complexity of the average software system: not losing the grip on the new technologies may turn out to be an unsustainable drain on productive effort, as their developers need to devote a substantial part of their time to learning instead of producing. In order to support continuous education and gathering/reusing solutions, SMEs need a tool supported management of experience and knowledge, providing problem-driven searches. We describe the experience gained in designing and developing Gesper, a tool for knowledge sharing that provides semantic searches based on ontologies. This tool has been tailored to the needs of SMEs and a prototype implementation has been built using free and open source tools.

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Section: Ontologymentioning

confidence: 99%

Gesper: Support to Capitalize on Experience in a Network of SMEs

Cerioli

Lagorio

Morten

et al. 2008

Communications in Computer and Information Science

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“…The value of a basic attribute is a base measure (Garcia et al, 2006), i.e., a measure that does not depend upon any other measure. -Derived attribute.…”

Section: Quality Attributesmentioning

confidence: 99%

Quality-aware analysis in product line engineering with the orthogonal variability model

et al. 2011

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Software product line engineering (SPLE) is about producing a set of similar products in a certain domain. A variability model documents the variability amongst products in a product line. The specification of variability can be extended with quality information, such as measurable quality attributes (e.g., CPU and memory consumption) and constraints on these attributes (e.g., memory consumption should be in a range of values). However, the wrong use of constraints may cause anomalies in the specification which must be detected (e.g., the model could represent no products). Furthermore, based on such quality information it is possible to carry out quality-aware analyses, i.e., the product line engineer may want to verify whether it is possible to build a product that satisfies a desired quality. The challenge for quality-aware specification and analysis is three-fold. First, there should be a way to specify quality information in variability models. Second, it should be possible to detect anomalies in the variability specification associated with quality information. Third, there should be mechanisms to verify the variability model to extract useful information, such as the possibility to build a product that fulfils certain quality conditions (e.g., is there any product that requires less than 512MB of memory?). In this article, we present an approach for quality-aware analysis in software product lines using the orthogonal variability model (OVM) to represent variability. We propose to map variability represented in the OVM associated with quality information to a constraint satisfaction problem and to use an off-the-shelf constraint programming solver to automatically perform the verification task. To illustrate our approach, we use a product line in the automotive domain which is an example that was created in a national project by a leading car company. We have developed a prototype tool named FaMa-OVM, which works as a proof of concepts. We were able to identify void models, dead and false optional elements, and check whether the product line example satisfies quality conditions.

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“…We follow the guidelines of García et al (2006) and use the term "measure" instead of the term "metric". In this paper the word "measure" denotes "software measure", if not stated otherwise.…”

Section: Introductionmentioning

confidence: 99%

Towards a Semiotic Quality Framework of Software Measures

Eessaar

2008

Proceedings of the Tenth International Conference on Enterprise Information Systems

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Abstract:Each software entity should have as high quality as possible in the context of limited resources. A software quality measure is a kind of software entity. Existing studies about the evaluation of software measures do not pay enough attention to the quality of specifications of measures. Semiotics has been used as a basis in order to evaluate the quality of different types of software entities. In this paper, we propose a multidimensional, semiotic quality framework of software quality measures. We apply this framework in order to evaluate the syntactic and semantic quality of two sets of database design measures. The evaluation shows that these measures have some quality problems.

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Towards a consistent terminology for software measurement

Cited by 147 publications

References 8 publications

Gesper: Support to Capitalize on Experience in a Network of SMEs

Gesper: Support to Capitalize on Experience in a Network of SMEs

Quality-aware analysis in product line engineering with the orthogonal variability model

Towards a Semiotic Quality Framework of Software Measures

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