ALGORITHM OF SELECTING COST ESTIMATION METHODS FOR ERP SOFTWARE IMPLEMENTATION

The article discusses the problem of selecting estimation methods for cost and implementation time for ERP systems, in case when system modifications are necessary. The authors reviewed the methods available in the literature and characterised the stages of strategic phase in the implementation process. On the basis of the analysis of data range and quality required by each method and the data obtained at different stages, a selection algorithm for each stage was proposed

Parameter estimation of cocomo model using the jaya algorithm for software cost estimation

In line with the advancement of computer technology, software is increasingly being used in place of hardware to help human do the daily chores. Estimate of the software development costs can be a major issue (i.e. in terms of determining the actual development costs). To date, many techniques have been proposed to help the software engineer determine the actual software cost. This thesis proposed the Jaya algorithm based on estimation of the software based on the COCOMO I model. The Constructive Cost Model (COCOMO) is a procedural software cost estimation model developed by Barry W. Boehm. In this case, the estimation of value of the COCOMO model parameters are determined for the cost and time estimation of the COCOMO model. As a result, COCOMO Jaya Algorithm (COCOMO JA) has been developed. The dataset NASA 63 project, Turkish dataset, and Kemerer dataset have been used. The experiment result shows the comparison between the standard COCOMO and COCOMO JA. The COCOMO JA demonstrated more minimize error as compare to the standard COCOMO. In conclusion, the JA suitable to evaluate the estimation effort and time for the COCOMO model

Software effort estimation by tuning COOCMO model parameters using differential evolution

Abstract- Accurate estimation of software projects costs represents a challenge for many government organizations such as the Department of Defenses (DOD) and NASA. Statistical models considerably used to assist in such a computation. There is still an urgent need on finding a mathematical model which can provide an accurate relationship between the software project effort/cost and the cost drivers. A powerful algorithm which can optimize such a relationship via tuning mathematical model parameters is urgently needed. In [1) two new model structures to estimate the effort required for software projects using Genetic Algorithms (GAs) were proposed as a modifica tion to the famous COnstructive COst MOdel (COCOMO). In this paper, we follow up on our previous work and present Differential Evolution (DE) as an alternative technique to estimate the COCOMO model parameters. The performance of the developed models were tested on NASA software project dataset provided in (2). The developed COCOMO-DE model was able to provide good estimation capabilities. I