An ontology-based approach for integrating tools supporting the software measurement process

Fonseca, Vinícius Soares; Barcellos, Monalessa Perini; Falbo, Ricardo de Almeida

doi:10.1016/j.scico.2016.10.004

Cited by 15 publications

(7 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There are different ways of measuring software development productivity [15], and productivity is typically defined as the output divided by the effort required to produce the output. Following guidelines by Fonseca [16], we specify the operational definition [17] of developer productivity by examining the developers' reported amount of wasted time using weekly web surveys over seven weeks. Since we can determine that the amount of wasted time has a negative impact on software development duration, we define productivity as the ability to deliver high-quality customer value in the shortest amount of time.…”

Section: Introductionmentioning

confidence: 99%

Software developer productivity loss due to technical debt—A replication and extension study examining developers’ development work

Besker

Martini

Bosch

2019

Journal of Systems and Software

View full text Add to dashboard Cite

Software companies need to deliver customer value continuously, both from a shortand long-term perspective. However, software development can be impeded by technical debt (TD). Although significant theoretical work has been undertaken to describe the negative effects of TD, little empirical evidence exists on how much wasted time and additional activities TD causes. The study aims to explore the consequences of TD in terms of wastage of development time. This study investigates on which activities this wasted time is spent and whether different TD types impact the wasted time differently. This study reports the results of a longitudinal study surveying 43 developers and including16 interviews followed by validation by an additional study using a different and independent dataset and focused on replicating the findings addressing the findings. The analysis of the reported wasted time revealed that developers waste, on average, 23% of their time due to TD and that developers are frequently forced to introduce new TD. The most common activity on which additional time is spent is performing additional testing.The study provides evidence that TD hinders developers by causing an excessive waste of working time, where the wasted time negatively affects productivity.

show abstract

Section: Introductionmentioning

confidence: 99%

Software developer productivity loss due to technical debt—A replication and extension study examining developers’ development work

Besker

Martini

Bosch

2019

Journal of Systems and Software

View full text Add to dashboard Cite

show abstract

“…As such, it can serve as conceptual basis to solve interoperability problems between different approaches for the development of adaptive systems -Table 2 even serves as starting point for mapping concepts among the 8 selected approaches. RASO can also be used to develop or integrate existing software tools in this domain, as done, e.g., in the domain of software measurement [12].…”

Section: Discussionmentioning

confidence: 99%

RASO: an Ontology on Requirements for the Development of Adaptive Systems

Peçanha¹,

Duarte²,

Souza³

2018

Anais Do WER18 - Workshop Em Engenharia De Requisitos

View full text Add to dashboard Cite

There is growing interest in software that can adapt their behavior to deal with deviations between their outcome and their requirements at runtime. A systematic mapping of the literature on selfadaptation approaches based on requirements models revealed over 200 papers on this subject. However, there is still a lack of a formal and explicit representation of the concepts in this domain, which can lead to problems in communication, learning, problem-solving, interoperability, etc. To make a clear and precise description of this domain, this paper proposes RASO: the Requirements for Adaptive Systems Ontology. RASO was built using a well-established Ontology Engineering method, is grounded on a foundational ontology and reuses concepts from other software-related ontologies. The ontology was evaluated by mapping constructs from the most referenced approaches from the literature to its concepts, thus creating a path for interoperability among them.

show abstract

“…The aim is to assign developers into projects according to their experience and the needs of the project. On the other hand, Fonseca et al [27] present an ontology for software measurement activity (e.g. measure source code, effort estimation, number of sprints).…”

Section: Related Workmentioning

confidence: 99%

“…3, pp. 234-241 This is an open access article published by the IET under the Creative Commons Attribution-NonCommercial-NoDerivs License (http://creativecommons.org/licenses/by-nc-nd/3.0/) [27], maintenance [28]). In this sense, the challenge is getting a described content capable of: (i) distinguish among different word meanings; (ii) infer relations between words on a specific thematic context; and (iii) retrieve information according to the user needs.…”

Section: Introductionmentioning

confidence: 99%

“…As we can notice, an ontology can provide benefits in software development through an information structure that can do automated reasoning about knowledge in the software development life cycle (e.g. project management [26], software measurement [27], maintenance [28]). In this sense, the challenge is getting a described content capable of: (i) distinguish among different word meanings; (ii) infer relations between words on a specific thematic context; and (iii) retrieve information according to the user needs.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Ontology for knowledge condensation to support expertise location in the code phase during software development process

et al. 2020

View full text Add to dashboard Cite

Software Development is a complex process, in which every software product is a knowledge representation of all the involved people. In agile software development, knowledge is prone to vaporise, because documentation is not a priority as indicated in the agile manifesto. This condition generates problems such as poor understanding of the requirements, knowledge transfer deficiency among developers, time wasted by developers while searching for knowledge. The objective of this work is to reduce architectural knowledge vaporisation by means of knowledge condensation to support expertise location (high-level knowledge at a given time). This through an ontology that will condensate the knowledge in the code phase. This study presents the description of an ontology development process following the Methontology Framework. Results show that the proposed ontology does not present incongruence or inconsistency and answers the competency questions correctly. The main contribution of this study is the ontology which brings several benefits such as a shared concept of the knowledge in the code phase and a way to link the artefacts (resources used by developers in the project) and the experts (artefacts provider).

show abstract

An ontology-based approach for integrating tools supporting the software measurement process

Cited by 15 publications

References 14 publications

Software developer productivity loss due to technical debt—A replication and extension study examining developers’ development work

Software developer productivity loss due to technical debt—A replication and extension study examining developers’ development work

RASO: an Ontology on Requirements for the Development of Adaptive Systems

Ontology for knowledge condensation to support expertise location in the code phase during software development process

Contact Info

Product

Resources

About