An Ontology-based Approach to Support for Requirements Traceability in Agile Development

Murtazina, Marina; Avdeenko, Tatiana

doi:10.1016/j.procs.2019.02.044

Cited by 21 publications

(18 citation statements)

References 8 publications

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“…Current works mainly covered the specification as in the of the [28] where they present a list of guidelines for ontology development, they only identify terms and concepts which involves results only of the first phase of the followed methodology, other works such as in [50] where an ontology (taxonomy) is presented, however, this model was not translated into an ontology language. A few works such as [41, 44, 45] formalise the ontology, which means that the taxonomy or knowledge model domain was converted into an ontology language. In this sense, our work presents a validated ontology for the coding phase of the software development process, which a phase not addressed by any of the works that achieve the formalisation phase. The main research implication of this work is the knowledge condensation through ontologies because previous research has modelled knowledge condensation empirically [13].…”

Section: Discussionmentioning

confidence: 99%

“…Almost all the ontologies work on the requirements phase, targeting activities such as requirement analysis. In [41][42][43][44][45] proposals seek to enhance the software quality by improving the elicitation and administration of the user's needs. Their objective was to eliminate ambiguities and language mistakes.…”

Section: Related Workmentioning

confidence: 99%

“…Another activity performed in the requirements phase is effort estimation. Hamdan et al [50] seek to eliminate mistakes or [46] documentation of term and concepts in GSD [47,48] human resources assign [26] sutomatic software documentation [49] effort Estimation [50] effort estimation [51] software requirements [42,43] documentation of terms and concepts in multisite development [52,53] software requirements [41,44,45] documentation for task allocation [54] documentation to support distributed teams [5] misunderstandings through the use of ontologies in a system, which enables project managers to obtain characteristics and terms of previous projects. Adnan and Afzal [51] present an ontology for knowledge about effort estimation, which has the objective of mitigate problems of distributed teams (e.g.…”

Section: Related Workmentioning

confidence: 99%

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

et al. 2020

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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).

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Section: Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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

et al. 2020

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“…The ontological language [22] processed for years has been transferred to the evolution of applications in the areas of software engineering. Therefore, the ontologies developed in [7,16,32,40] are implemented in the sub-parts of the DS in general, which include: collaboration, workflow, process evaluation, cooperative design, and remediation.…”

Section: Ontological Language (Owl)mentioning

confidence: 99%

A Case Study in the Banking Sector: An Ontology for the Selection of Agile and Lean Software Development Methodologies

Morales

Bonilla-Morales

Vargas-Lombardo

2021

Communications in Computer and Information Science

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Nowadays, the application of methodologies that allow to guide the process of development of Software in the companies has become a fundamental aspect to achieve the suitable management of the processes in the projects. In view of the diversity of existing methodologies, there is a growing interest in defining strategies that allow the selection and application of the correct methodology, which adjusts to the characteristics of the work teams and the software projects. The aim of this work is to develop an ontology for the selection of the methodology that, according to its principles, is most appropriate and beneficial for the development of software projects. The domain of ontology is limited to the Agile and Lean approaches, without defining for Agile the specific method that it applies, but it involves any method that is governed by the agile values and principles established in the Agile manifesto. Onto-logy is applied in two organizations in the banking sector, allowing recommendations to be inferred for the use of Agile methodology in both, which will make it possible to reduce the delivery time of software products, improve communication between project participants, and facilitate the engineering of requirements. On the other hand, the ontology suggests co-regulating characteristic aspects of the Lean practices in order to minimize costs, optimize processes in the software projects and improve the organizational culture.

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“…The proposed approach can be used as part of the intellectual support of the engineering process based on ontological models. The ontology data of requirements can be processed together with the data of other ontologies in the field of requirements engineering described by us in works [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

The detection of conflicts in the requirements specification based on an ontological model and a production rule system

Murtazina

Avdeenko

2019

Proceedings of the v International Conference Information Technology and Nanotechnology 2019

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The paper presents an approach to organizing the detection of conflicts between requirements based on an ontological model and a system of production rules. Requirements in the form of plain text are converted to instances of OWL ontologies for analysis. There are three basic elements “subject”, “action” and “object” in the requirements. These elements become classes of the ontology. The object properties between instances of the same classes are defined in the ontology. In the system of rules it is determined that one of four types of relations can be established between a pair of the requirements: isConflict, isDuplicate, isInterconnect, isNotInterconnect. We develop the software product in the Python language for building and applying production rules system for classes and property objects of the ontology. Protégé 5.2 is used to work with the ontology. Also Python library PySwip and development environment SWI-Prolog 7.6.4 are used in the work. The paper also considers the issues of extracting requirements ontology instances from the automated processing results of textual requirements. The UDPipe with Russian language model is used for text processing.

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An Ontology-based Approach to Support for Requirements Traceability in Agile Development

Cited by 21 publications

References 8 publications

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

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

A Case Study in the Banking Sector: An Ontology for the Selection of Agile and Lean Software Development Methodologies

The detection of conflicts in the requirements specification based on an ontological model and a production rule system

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