Integrating knowledge life cycle within software development process to produce a quality software product

Sabri, Omar; Alfifi, Fahad

doi:10.1109/icengtechnol.2017.8308172

Cited by 5 publications

(3 citation statements)

References 15 publications

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“…Due to the insufficient communication, the efficient search results for requirements of each customer is being serious matter for the success of requirements engineering, leading to a lower satisfaction rate and high costs. As a result, the requirement assembling phase—of the software development life cycle (SDLC)—is being challenge [2]. So, an incremental development method is a popular approach introduced for the software development.…”

Section: Introductionmentioning

confidence: 99%

“…The main contributions of the research: (1) Presenting a new hybrid algorithm HGABC (through combining ABC and GA). HGABC is extensively examined using two objective functions over several real-world datasets, and this hybridised algorithm is used for the first time to tackle the MNRP in SE field; (2) Formulate the GA's operators (Crossover and Mutations) mathematically to express clearly their key role in enhancing the produced solutions of HGABC. Concisely, a novel hybrid approach HGABC is therefore presented for multi-objective optimisation problems by combining the ABC and GA algorithms as shown in pseudo-code of Algorithm 1.…”

Section: Introductionmentioning

confidence: 99%

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Software requirement selection using a combined multi‐objective optimisation technique

et al. 2022

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The optimal requirements selection set aims primarily at careful search for the best requirements set of the next release of software during development process. This procedure is widely defined as the next release problem (NRP), which is also classified as NP-hard dilemma. Several techniques, in literature, have been proposed to tackle NRP. However, in real examples, the earlier studies still immature as NRP still suffers interactions and restrictions that makes the problem more complicated. Although few interesting works have been presented, yet NRP, based on our study, could be further investigated and effectively tackled. In this research, therefore, NRP is devised as a multiobjective optimisation problem. Two clashing objectives (satisfaction and cost) and two constraints (interactions forms) are formulated. To tackle NRP effectively, a new hybrid genetic and artificial bee colony algorithm (HGABC) is introduced. HGABC combines features of genetic and artificial bee colony algorithms. Experimental study, using case studies and three criteria, have been conducted to show HGABC's power of generating non-dominated effective Pareto solutions versus the state-of-the-art algorithms. Results indicate that HGABC does not just outperform its rivals, yet also gives better Pareto solutions in terms of diversity and quality for almost all the instances of this problem.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Software requirement selection using a combined multi‐objective optimisation technique

et al. 2022

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“…Knowledge is an asset for every individual or group. Science and technology are created from personal knowledge, and then managed into a knowledge base to become an asset (Sabri & Alfifi, 2017). Individuals or groups will continue to exist and develop if they always use the information or experience to create competence.…”

Section: Introductionmentioning

confidence: 99%

Development of Knowledge Management System for Jaipong Dance

Feta

2022

pilar

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Knowledge for culture is a concept of using information and communication technology to increase usability in the field of culture, especially in managing, documenting, disseminating information and knowledge of cultural arts, especially Sundanese cultural arts, namely the art of jaipong dance. For the art of jaipong dance to be maintained, it is necessary to manage information and knowledge that utilizes the sophistication of information and communication technology towards the noble values of jaipong dance. In that way, the art of jaipong dance can be passed on to each generation to maintain culture as self-identity and show the existence of Sundanese culture in the eyes of the national and even the world. Knowledge Management Systems (KMS) is a solution that can be used to preserve the art of jaipong dance in Indonesia by managing existing knowledge about various things about the art of jaipong dance. The research method uses an integrated knowledge system management cycle. There are three main stages: knowledge capture and/or creation, knowledge sharing and dissemination, and knowledge acquisition and application. Meanwhile, for the formation of knowledge used in this study, the SECI Nonaka model was used. KMS itself can benefit experts, organizations, and the general public. It becomes learning material for every generation. The process of transferring information and knowledge about the movements in the Jaipong dance what musical instruments are used in performances, fashion, and make-up can run. properly and can preserve the art of jaipong dance, which is one of the characteristics of dance in Indonesia.

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Genetic K-Means Adaption Algorithm for Clustering Stakeholders in System Requirements

Reyad

Dukhan

Marghny

et al. 2021

Advances in Intelligent Systems and Computing

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Integrating knowledge life cycle within software development process to produce a quality software product

Cited by 5 publications

References 15 publications

Software requirement selection using a combined multi‐objective optimisation technique

Software requirement selection using a combined multi‐objective optimisation technique

Development of Knowledge Management System for Jaipong Dance

Genetic K-Means Adaption Algorithm for Clustering Stakeholders in System Requirements

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