Soft computing based estimation of software development effort

Author(s):  
S Saraswathi ◽  
N Kannan
2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
He Xiaolong ◽  
Zhao Huiqi ◽  
Zhong Lunchao ◽  
Shah Nazir ◽  
Deng Jun ◽  
...  

Software project development is very crucial, and measuring the exact cost and effort of development is becoming tedious and challenging. Organizations are trying to wind up their project of software development within the agreed budget and schedule successfully. Traditional practices are inadequate to achieve the current needs of the software industry. Underestimation and overestimation of software development effort lead to financial implications in the form of resources, cost of staffing, and budget of developing the software project. Soft computing (SC) approaches and tools deliver an addition of techniques for anticipating resistance to the deception, defect, incomplete truth for traceability and ambiguity, low arrangement cost, and strength. A large amount of SC approaches is prevailing in the literature to accomplish way-out to difficulties precisely, practically, and speedily. The approaches of SC can give better prediction, high performance, and dynamic behavior. SC deals with computational intelligence which integrates the concept of agent paradigm and SC. The proposed study presents a systematic literature review (SLR) of the approaches, tools, and techniques of SC used in the literature. The study presented a comprehensive review by searching the defined keywords in the popular libraries, filtered the paper, and obtained most relevant papers. After the selection of the papers, the quality assessment process of the included papers has been done in order to determine the relevancy of the papers. The study will help researchers in the area of research to devise novel ideas and solutions to overcome the existing issue on the basis of this study as evidence of the literature.


Author(s):  
K. Vinaykumar ◽  
V. Ravi ◽  
Mahil Carr

Software development has become an essential investment for many organizations. Software engineering practitioners have become more and more concerned about accurately predicting the cost of software products to be developed. Accurate estimates are desired but no model has proved to be successful at effectively and consistently predicting software development cost. This chapter investigates the use of the soft computing approaches in predicting the software development effort. Various statistical and intelligent techniques are employed to estimate software development effort. Further, based on the abovementioned techniques, ensemble models are developed to forecast software development effort. Two types of ensemble models viz., linear (average) and nonlinear are designed and tested on COCOMO’81 dataset. Based on the experiments performed on the COCOMO’81 data, it was observed that the nonlinear ensemble using radial basis function network as arbitrator outperformed all the other ensembles and also the constituent statistical and intelligent techniques. The authors conclude that using soft computing models they can accurately estimate software development effort.


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