Noor Khalaf L. Alhammad, Esra Alzaghoul, Fawaz A. Alzaghoul, Mohammed Akour
{"title":"Evolutionary neural network classifiers for software effort estimation","authors":"Noor Khalaf L. Alhammad, Esra Alzaghoul, Fawaz A. Alzaghoul, Mohammed Akour","doi":"10.1504/IJCAET.2020.10027779","DOIUrl":null,"url":null,"abstract":"The estimation of software development efforts has become a crucial activity in software project management. Due to this importance, many researchers focused their efforts on proposing models for relationship construction between efforts and software size and requirements. However, there are still gaps and problems in software effort's estimation process; due to the lack of enough data available in the initial stage of project life cycle. The need for an enhanced and an accurate method for software effort estimation is an urgent issue that challenged software project-management researchers around the world. This work proposes a model based on artificial neural network (ANN) and dragonfly algorithm (DA), in order to provide more accurate model for software effort estimation. The applicability of the model was evaluated using several experiments and the results were in favour of the enhancement with more accurate effort estimation.","PeriodicalId":346646,"journal":{"name":"Int. J. Comput. Aided Eng. Technol.","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Comput. Aided Eng. Technol.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJCAET.2020.10027779","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The estimation of software development efforts has become a crucial activity in software project management. Due to this importance, many researchers focused their efforts on proposing models for relationship construction between efforts and software size and requirements. However, there are still gaps and problems in software effort's estimation process; due to the lack of enough data available in the initial stage of project life cycle. The need for an enhanced and an accurate method for software effort estimation is an urgent issue that challenged software project-management researchers around the world. This work proposes a model based on artificial neural network (ANN) and dragonfly algorithm (DA), in order to provide more accurate model for software effort estimation. The applicability of the model was evaluated using several experiments and the results were in favour of the enhancement with more accurate effort estimation.