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Formalization of the prediction and ranking of software development life cycle models

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 12 No. 1 (2022)

DOI
10.11591/ijece.v12i1.pp534-540
ISSN
2722-2578, 2088-8708
Published
2022-02-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

The study of software engineering professional practices includes the use of the formal methodology in a software development. Identifying the appropriate methodology will not only reduce the failure of software but will also help to deliver the software in accordance with the predetermined budget and schedule. In literature, few works have been developed a tool for prediction of the most appropriate methodology for the specific software project. In this paper, a method for selecting an appropriate software development life cycle (SDLC) model based on a ranking manner from the highest to the lowest scoring is presented. The selection and ranking of appropriate SDLC elaborate the related SDLC’s critical factors, these factors are given different weights according to the SDLC, then these weights are used by the proposed mathematical method. The proposed approach has been extensively experimented on a dataset by software practitioners who are working in the software industry. Experimental results show that, the proposed method represents an applicable tool in predicting and ranking suitable SDLC models on various types of projects, such as: life-critical systems, commercial uses systems, and entertainment applications.

Collaboration network of the authors

22 authors · 46 co-authorship links · 18 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Al-Hussein Bin Talal University
  • Applied Science Private University
  • Western Michigan University
  • Middle East University
  • American University in the Emirates
  • University of Jordan
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Arar Al TawilApplied Science Private University5
Bilal I. AlqudahAl-Hussein Bin Talal University4
Bradely BazuinWestern Michigan University1
Ikhlas M. Abdel-QaderWestern Michigan University1
Reham Al-MohtadiAffiliation unknown1
Mohammed A. AbuhelalehAl-Hussein Bin Talal University1
Raed AltabeiriAl-Hussein Bin Talal University1
Mohanad AlhasanatAl-Hussein Bin Talal University1
Rima AbdelhadiAl-Hussein Bin Talal University1
Abedallah Zaid AbualkishikAmerican University in the Emirates1
Ali A. AlwanAffiliation unknown1
Amneh ShabanApplied Science Private University1
Lara Al-ShboulUniversity of Jordan1
Mohammad AlshinwanMiddle East University1
Worood Al-MuhtasebApplied Science Private University1
Hanaa FathiMiddle East University1
Abdullah I. AlhasanatAl-Hussein Bin Talal University1
Samiha AlfalahatAl-Hussein Bin Talal University1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Formalization of the prediction and ranking of software development life cycle models</dc:title><dc:creator>Almazaydeh, Laiali</dc:creator><dc:creator>Alsafasfeh, Moath</dc:creator><dc:creator>Alsalameen, Reyad</dc:creator><dc:creator>Alsharari, Shoroq</dc:creator><dc:description>&lt;jats:p&gt;The study of software engineering professional practices includes the use of the formal methodology in a software development. Identifying the appropriate methodology will not only reduce the failure of software but will also help to deliver the software in accordance with the predetermined budget and schedule. In literature, few works have been developed a tool for prediction of the most appropriate methodology for the specific software project. In this paper, a method for selecting an appropriate software development life cycle (SDLC) model based on a ranking manner from the highest to the lowest scoring is presented. The selection and ranking of appropriate SDLC elaborate the related SDLC’s critical factors, these factors are given different weights according to the SDLC, then these weights are used by the proposed mathematical method. The proposed approach has been extensively experimented on a dataset by software practitioners who are working in the software industry. Experimental results show that, the proposed method represents an applicable tool in predicting and ranking suitable SDLC models on various types of projects, such as: life-critical systems, commercial uses systems, and entertainment applications.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2022-02-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v12i1.pp534-540</dc:identifier><dc:identifier>10.11591/ijece.v12i1.pp534-540</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 12 No 1 (2022); 534</dc:source><dc:source>2722-2578</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://ijece.iaescore.com/index.php/IJECE/article/viewFile/25616/15430</dc:relation><dc:rights>http://creativecommons.org/licenses/by-sa/4.0</dc:rights></oai_dc:dc>