eprintid: 8801 rev_number: 11 eprint_status: archive userid: 2 dir: disk0/00/00/88/01 datestamp: 2023-09-14 23:30:10 lastmod: 2024-04-30 22:32:41 status_changed: 2023-09-14 23:30:10 type: article metadata_visibility: show creators_name: Rashid, Chaudhary Hamza creators_name: Shafi, Imran creators_name: Ahmad, Jamil creators_name: Bautista Thompson, Ernesto creators_name: Masías Vergara, Manuel creators_name: Diez, Isabel De La Torre creators_name: Ashraf, Imran creators_id: creators_id: creators_id: creators_id: ernesto.bautista@unini.edu.mx creators_id: manuel.masias@uneatlantico.es creators_id: creators_id: title: Software Cost and Effort Estimation: Current Approaches and Future Trends ispublished: pub subjects: uneat_eng divisions: uneatlantico_produccion_cientifica divisions: uninimx_produccion_cientifica divisions: uninipr_produccion_cientifica divisions: unic_produccion_cientifica divisions: uniromana_produccion_cientifica full_text_status: public keywords: Software cost estimation; systematic literature review; tollgate approach; Likert scale; quality assessment; software dependability; project planning abstract: Software cost and effort estimation is one of the most significant tasks in the area of software engineering. Research conducted in this field has been evolving with new techniques that necessitate periodic comparative analyses. Software project success largely depends on accurate software cost estimation as it gives an idea of the challenges and risks involved in the development. The great diversity of ML and Non-ML techniques has generated a comparison and progressed into the integration of these techniques. Based on varying advantages it has become imperative to work out preferred estimation techniques to improve the project development process. This study aims to present a systematic literature review (SLR) to investigate the trends of the articles published in the recent one and a half decades and to propose a way forward. This systematic literature review has proposed a three-stage approach to plan (Tollgate approach), conduct (Likert type scale), and report the results from five renowned digital libraries. For the selected 52 articles, artificial neural network model (ANN) and constructive cost model (COCOMO) based approaches have been the favored techniques. The mean magnitude of relative error (MMRE) has been the preferred accuracy metric, software engineering, and project management are the most relevant fields, and the promise repository has been identified as the widely accessed database. This review is likely to be of value for the development, cost, and effort estimations. date: 2023-09 publication: IEEE Access pagerange: 1-1 id_number: doi:10.1109/ACCESS.2023.3312716 refereed: TRUE issn: 2169-3536 official_url: http://doi.org/10.1109/ACCESS.2023.3312716 access: open language: en citation: Artículo Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica Universidad Internacional Iberoamericana México > Investigación > Producción Científica Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica Universidad Internacional do Cuanza > Investigación > Producción Científica Universidad de La Romana > Investigación > Producción Científica Abierto Inglés Software cost and effort estimation is one of the most significant tasks in the area of software engineering. Research conducted in this field has been evolving with new techniques that necessitate periodic comparative analyses. Software project success largely depends on accurate software cost estimation as it gives an idea of the challenges and risks involved in the development. The great diversity of ML and Non-ML techniques has generated a comparison and progressed into the integration of these techniques. Based on varying advantages it has become imperative to work out preferred estimation techniques to improve the project development process. This study aims to present a systematic literature review (SLR) to investigate the trends of the articles published in the recent one and a half decades and to propose a way forward. This systematic literature review has proposed a three-stage approach to plan (Tollgate approach), conduct (Likert type scale), and report the results from five renowned digital libraries. For the selected 52 articles, artificial neural network model (ANN) and constructive cost model (COCOMO) based approaches have been the favored techniques. The mean magnitude of relative error (MMRE) has been the preferred accuracy metric, software engineering, and project management are the most relevant fields, and the promise repository has been identified as the widely accessed database. This review is likely to be of value for the development, cost, and effort estimations. metadata Rashid, Chaudhary Hamza; Shafi, Imran; Ahmad, Jamil; Bautista Thompson, Ernesto; Masías Vergara, Manuel; Diez, Isabel De La Torre y Ashraf, Imran mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, ernesto.bautista@unini.edu.mx, manuel.masias@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR (2023) Software Cost and Effort Estimation: Current Approaches and Future Trends. IEEE Access. p. 1. ISSN 2169-3536 document_url: http://repositorio.unic.co.ao/id/eprint/8801/1/Software_Cost_and_Effort_Estimation_Current_Approaches_and_Future_Trends.pdf