Analogy-based software development effort estimation in global software development

被引:9
作者
El Bajta, Manal [1 ]
机构
[1] Mohammed V Souissi Univ, Software Project Management Res Team, ENSIAS, Rabat, Morocco
来源
2015 IEEE 10TH INTERNATIONAL CONFERENCE ON GLOBAL SOFTWARE ENGINEERING WORKSHOPS (ICGSEW 2015) | 2015年
关键词
global software development; effort estimation; analogy-based estimation;
D O I
10.1109/ICGSEW.2015.19
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Context: Software development has always been characterised by certain parameters. In the case of global software development, one of the important challenges for software developers is that of predicting the development effort of a software system on the basis of developer details, size, complexity, and other measures. Objective: The main research topics related to global software development effort estimation are the definition and empirical evaluation of a search-based approach with which to build new estimation models and the definition and empirical evaluation of all available early data. Datasets have been used as a basis to carry out an analogy-based estimation using similarity functions and measures. Method: Many of the problems concerning the existing effort estimation challenges can be solved by creating an analogy. This paper describes an enhanced analogy-based model for the estimation of software development effort and proposes a new approach using similarity functions and measures for software effort estimation. Result: A new approach for analogy-based reasoning with which to enhance the performance of cost estimation in distributed or combined software projects dealing with numerical and categorical data. The proposed method will be validated empirically using The International Software Benchmarking Standards Group dataset as a basis. Conclusion: The proposed estimation model could be a useful approach for early stage effort estimation on distributed projects.
引用
收藏
页码:51 / 54
页数:4
相关论文
共 50 条
[1]   Towards Improvement of Analogy-Based Software Development Effort Estimation: A Review [J].
Bardsiri, Vahid Khatibi ;
Jawawi, Dayang Norhayati Abang ;
Khatibi, Elham .
INTERNATIONAL JOURNAL OF SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING, 2014, 24 (07) :1065-1089
[2]   DABE: Differential evolution in analogy-based software development effort estimation [J].
Benala, Tirimula Rao ;
Mall, Rajib .
SWARM AND EVOLUTIONARY COMPUTATION, 2018, 38 :158-172
[3]   Development of Analogy-Based Estimation Method for Software Development Cost Estimation in Government Agencies [J].
Kurniawan, Imam ;
Arman, Arry Akhmad ;
Mardiyanto, Sukrisno .
PROCEEDINGS OF THE 2017 6TH INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING AND INFORMATICS (ICEEI'17), 2017,
[4]   Empirical study of analogy-based software effort estimation [J].
Walkerden F. ;
Jeffery R. .
Empirical Software Engineering, 1999, 4 (2) :135-158
[5]   Stacking regularization in analogy-based software effort estimation [J].
Kaushik, Anupama ;
Kaur, Prabhjot ;
Choudhary, Nisha ;
Priyanka .
SOFT COMPUTING, 2022, 26 (03) :1197-1216
[6]   Insightful analogy-based software development effort estimation through selective classification and localization [J].
Khatibi Bardsiri V. ;
Khatibi E. .
Innovations in Systems and Software Engineering, 2014, 11 (01) :25-38
[7]   An evolutionary ensemble analogy-based software effort estimation [J].
Shahpar, Zahra ;
Bardsiri, Vahid Khatibi ;
Bardsiri, Amid Khatibi .
SOFTWARE-PRACTICE & EXPERIENCE, 2022, 52 (04) :929-946
[8]   Stacking regularization in analogy-based software effort estimation [J].
Anupama Kaushik ;
Prabhjot Kaur ;
Nisha Choudhary .
Soft Computing, 2022, 26 :1197-1216
[9]   Ensembling Artificial Bee Colony With Analogy-Based Estimation to Improve Software Development Effort Prediction [J].
Shah, Muhammad Arif ;
Jawawi, Dayang Norhayati Abang ;
Isa, Mohd Adham ;
Younas, Muhammad ;
Abdelmaboud, Abdelzahir ;
Sholichin, Fauzi .
IEEE ACCESS, 2020, 8 :58402-58415
[10]   Analogy-Based Approaches to Improve Software Project Effort Estimation Accuracy [J].
Resmi, V ;
Vijayalakshmi, S. .
JOURNAL OF INTELLIGENT SYSTEMS, 2020, 29 (01) :1468-1479