Evaluating the Software Requirements Specifications Using Ontology-Based Intelligent Agent

Hovorushchenko, Tetiana; Pavlova, Olga

doi:10.1109/stc-csit.2018.8526730

Cited by 15 publications

(6 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 scores attained for each of the research works are shown in Table 2:  S1 -Williams ( 2018) "An Ontology Based Collaborative Recommender System for Security Requirements Elicitation": The authors propose a collaborative recommendation system based on an ontology with which to obtain security requirements and evaluate the performance of the system.  S2 - Hovorushchenko and Pavlova (2018) "Evaluating the Software Requirements Specifications Using Ontology-Based Intelligent Agent": This work develops an intelligent agent based on ontologies (OBIA) that can evaluate the level of sufficiency of the information in the SRS and detect missing attributes through the creation of methods developed for the analysis.  S3 - Huaqiang et al ( 2017) "The research of domain ontology recommendation method with its applications in requirement traceability":…”

Section: Extraction Of Informationmentioning

confidence: 99%

Building an integrated requirements engineering process based on Intelligent Systems and Semantic Reasoning on the basis of a systematic analysis of existing proposals

Corral¹,

Sanchez²,

Antonelli³

2022

jucs

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Requirements Engineering is one of the fundamental activities in the software development process and is oriented toward what should be produced. One of the development team’s most common problems is a lack of communication regarding an understanding of the discourse domain and how to integrate and process excessive information originating from different sources. This may lead to errors of omission and the consequent production of incomplete and inconsistent artifacts, which will have a direct effect on the quality of the software. The use of machine learning techniques helps the development team produce successful software on the basis of the acquisition of knowledge and human experience with which to understand the domain of the application. This paper, therefore, presents a proposal for a new methodological process oriented toward the construction of a vocabulary concerning the application domain. The authors propose to do this by employing Natural Language Processing (NLP), ontologies and heuristics that will lead to the production of a Lexicon that is common to analysts and customers, both of whom will understand the universe of discourse, thus mitigating problems of completeness. This objective has been achieved by carrying out a Systematic Literature Review of the artificial intelligence techniques employed in the requirements engineering process, which led to the discovery that 41.37% use NLP, while 55.71% apply ontologies such as semantic reasoners which help solve the problem of language ambiguity, the structures in specifications or the identification of key concepts with which to establish traceability links. However, the review also showed that the problems regarding the comprehension and completeness of requirements problems have yet to be resolved.

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“…However, Hovorushchenko and Pavlova [28] proposed the development method for the activity of ontology‐based intelligent agent (OBIA) for evaluating the software requirements specifications (SRS). OBIA evaluates the sufficiency of information in the SRS for assessing the non‐functional software features.…”

Section: Related Workmentioning

confidence: 99%

A reference measurement framework of software security product quality (SPQ ^NFSR )

Al-Sarayreh

Alenezi

Zarour

et al. 2020

IET Information Security

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Currently, the customer's demands have expressively amplified their expectations of getting software at a high‐quality level. However, the non‐functional requirements of the software products attention have been expanded in both the academic and the industrial fields; so, there is no framework for specifying and measuring such kinds of quality constraints for the security requirements of software product quality. This paper presents an integrated framework of the early specification and measurement of the functional and non‐functional software security requirements. Such a measurement framework would help software and systems engineers to improve product qualities whether the software has already been delivered or has yet to be built. The main steps that have been followed include: identify, specify and measure the software security requirements based on ISO/IEC SQuaRE series of international standards for software product quality. A standard measurement framework used to measure the functional size of the software product quality to develop a functional size measurement of the functional and non‐functional security requirements is described. As a result, a functional size measurement framework of the functional and non‐functional security requirements (SPQNFSR) using international standards is proposed. An automatic teller machine case study for the measurement of security requirements based on perspectives of a software functional user requirements is presented. Finally, it is concluded that it is essential to develop such a functional size measurement framework for functional and non‐functional security requirements to support developers to face the challenges derived from early dealing with such requirements.

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Evaluating the Software Requirements Specifications Using Ontology-Based Intelligent Agent

Cited by 15 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

Building an integrated requirements engineering process based on Intelligent Systems and Semantic Reasoning on the basis of a systematic analysis of existing proposals

A reference measurement framework of software security product quality (SPQ ^NFSR )

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Evaluating the Software Requirements Specifications Using Ontology-Based Intelligent Agent

Cited by 15 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

Building an integrated requirements engineering process based on Intelligent Systems and Semantic Reasoning on the basis of a systematic analysis of existing proposals

A reference measurement framework of software security product quality (SPQ NFSR )

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Product

Resources

About

A reference measurement framework of software security product quality (SPQ ^NFSR )