Software Cost Estimation using Soft Computing Approaches

2010 ◽  
pp. 499-518 ◽  
Author(s):  
K. Vinaykumar ◽  
V. Ravi ◽  
Mahil Carr
Keyword(s):  
Software Development ◽  
Soft Computing ◽  
Cost Estimation ◽  
Radial Basis Function Network ◽  
Development Effort ◽  
Software Cost ◽  
Ensemble Models ◽  
Software Products ◽  
Software Development Effort ◽  
The Cost

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.

scholarly journals Empirical Study of Homogeneous and Heterogeneous Ensemble Models for Software Development Effort Estimation

2013 ◽  
Vol 2013 ◽  
pp. 1-21 ◽  
Author(s):  
Mahmoud O. Elish ◽  
Tarek Helmy ◽  
Muhammad Imtiaz Hussain
Keyword(s):  
Empirical Study ◽  
Software Development ◽  
Computational Intelligence ◽  
Accurate Estimation ◽  
Development Effort ◽  
Effort Estimation ◽  
Ensemble Models ◽  
Intelligence Models ◽  
Software Development Effort ◽  
Software Development Effort Estimation

Accurate estimation of software development effort is essential for effective management and control of software development projects. Many software effort estimation methods have been proposed in the literature including computational intelligence models. However, none of the existing models proved to be suitable under all circumstances; that is, their performance varies from one dataset to another. The goal of an ensemble model is to manage each of its individual models’ strengths and weaknesses automatically, leading to the best possible decision being taken overall. In this paper, we have developed different homogeneous and heterogeneous ensembles of optimized hybrid computational intelligence models for software development effort estimation. Different linear and nonlinear combiners have been used to combine the base hybrid learners. We have conducted an empirical study to evaluate and compare the performance of these ensembles using five popular datasets. The results confirm that individual models are not reliable as their performance is inconsistent and unstable across different datasets. Although none of the ensemble models was consistently the best, many of them were frequently among the best models for each dataset. The homogeneous ensemble of support vector regression (SVR), with the nonlinear combiner adaptive neurofuzzy inference systems-subtractive clustering (ANFIS-SC), was the best model when considering the average rank of each model across the five datasets.

scholarly journals Soft Computing and Decision Support System for Software Process Improvement: A Systematic Literature Review

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
He Xiaolong ◽  
Zhao Huiqi ◽  
Zhong Lunchao ◽  
Shah Nazir ◽  
Deng Jun ◽  
...  
Keyword(s):  
Literature Review ◽  
Software Development ◽  
Soft Computing ◽  
Systematic Literature Review ◽  
High Performance ◽  
Software Process Improvement ◽  
Assessment Process ◽  
Development Effort ◽  
Software Project ◽  
Software Development Effort

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.

scholarly journals A Study of Software Development Cost Estimation Techniques and Models

2020 ◽  
Vol 39 (2) ◽  
pp. 413-431 ◽  
Author(s):  
Junaid Rashid ◽  
Muhammad Wasif Nisar ◽  
Toqeer Mahmood ◽  
Amjad Rehman ◽  
Yasser Arafat Syed
Keyword(s):  
Software Development ◽  
Cost Estimation ◽  
Hybrid Approach ◽  
Parametric Models ◽  
Development Effort ◽  
Development Cost ◽  
Software Development Effort ◽  
Percent Accuracy ◽  
Single Technique ◽  
Estimation Models

SDCE (Software Development Cost Estimation) has always been an interesting and budding field in Software Engineering. This study supports the SDCE by exploring its techniques and models and collecting them in one place. This contribution in the literature will assist future researchers to get maximum knowledge about SDCE techniques and models from one paper and to save their time. In this paper, we review numerous software development effort and cost estimation models and techniques, which are divided into different categories. These categories are parametric models, expertise-based techniques, learning-oriented techniques, dynamicsbased models, regression-based techniques, fuzzy logic-based methods, size-based estimation models, and composite techniques. Some other techniques which directly do not lie in any specific category are also briefly explained. We have concluded that no single technique is best for all situations; rather they are applicable in different nature of projects. All techniques have their own pros and cons and they are challenged by the rapidly changing software industry. Since no single technique gives a hundred percent accuracy, that is why one technique and model should not be preferred over all others. We recommend a hybrid approach for SDCE because in this way the limitations of one model and technique are complemented by the merits of the other model/technique. We also recommend a model calibration to obtain accurate results because if a model was developed in a different environment, we cannot expect reliable estimates from it in a completely new environment.

scholarly journals A Study of Software Development Cost Estimation Techniques and Models

2020 ◽  
Vol 39 (2) ◽  
pp. 413-431
Author(s):  
Junaid Rashid ◽  
Muhammad Wasif Nisar ◽  
Toqeer Mahmood ◽  
Amjad Rehman ◽  
Yasser Arafat Syed
Keyword(s):  
Software Development ◽  
Cost Estimation ◽  
Hybrid Approach ◽  
Parametric Models ◽  
Development Effort ◽  
Development Cost ◽  
Software Development Effort ◽  
Percent Accuracy ◽  
Single Technique ◽  
Estimation Models

SDCE (Software Development Cost Estimation) has always been an interesting and budding field in Software Engineering. This study supports the SDCE by exploring its techniques and models and collecting them in one place. This contribution in the literature will assist future researchers to get maximum knowledge about SDCE techniques and models from one paper and to save their time. In this paper, we review numerous software development effort and cost estimation models and techniques, which are divided into different categories. These categories are parametric models, expertise-based techniques, learning-oriented techniques, dynamicsbased models, regression-based techniques, fuzzy logic-based methods, size-based estimation models, and composite techniques. Some other techniques which directly do not lie in any specific category are also briefly explained. We have concluded that no single technique is best for all situations; rather they are applicable in different nature of projects. All techniques have their own pros and cons and they are challenged by the rapidly changing software industry. Since no single technique gives a hundred percent accuracy, that is why one technique and model should not be preferred over all others. We recommend a hybrid approach for SDCE because in this way the limitations of one model and technique are complemented by the merits of the other model/technique. We also recommend a model calibration to obtain accurate results because if a model was developed in a different environment, we cannot expect reliable estimates from it in a completely new environment.

scholarly journals Pengukuran Sistem Informasi Menggunakan Metode Function Point (FP) pada Siakad Universitas XYZ

2020 ◽  
Vol 7 (1) ◽  
pp. 122
Author(s):  
Elok Tiara Cahya Septi ◽  
Firdayatul Dewi Sartika ◽  
Renny Sari Dewi
Keyword(s):  
Information System ◽  
Software Development ◽  
Cost Calculation ◽  
Development Effort ◽  
Software Cost ◽  
Function Points ◽  
Function Point ◽  
Strategic Role ◽  
Software Development Effort ◽  
Academic Information

Software cost calculation is an activity carried out to determine the value of a software using a quantitative approach. Seeing that there are various measurement methods and there are still no standards in assessing software, this measurement process is ignored, even though this process has a strategic role in software development. This research intends to calculate the size of the business of developing academic information system software with the Function Point (FP) method. The steps taken are (1) calculating the amount of function points, (2) calculating the software development effort, and (3) distributing the amount of effort to each activity. The results of this study are efforts to develop an academic information system is 1,460 people / hour and the nominal amount is IDR 177,917,997.

Hybridization of Class Responsibility Collaborators Model (HCRCM) with Function Point to enhance Project Estimation Cost in Agile Software Development

2017 ◽  
Vol 2 (6) ◽  
pp. 20-24
Author(s):  
Faki Agebee Silas ◽  
Musa Yusuf ◽  
Anah Hassan Bijik
Keyword(s):  
Software Development ◽  
Cost Estimation ◽  
Agile Software Development ◽  
Agile Development ◽  
Software Cost Estimation ◽  
Software Cost ◽  
Function Point ◽  
Project Estimation ◽  
Agile Software ◽  
The Cost

Estimating software cost in an agile system in terms of effort is very challenging. This is because the traditional models of software cost estimation do not completely fit in the agile development process. This paper presents a methodology to enhance the cost of project estimation in agile development. The hybridization adopts Class Responsibility Collaborators models with function point thereby boosting the agile software development estimation process. The study found out that adopting the Hybridized Class Responsibility Collaborator with function point has great improvement on cost estimation in agile software development.

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