This paper presents the results of an empirical study undertaken to investigate the utility of COCOMO II model drivers in predicting the understandability of a software project. Understandability is defined as the degree of clarity of the purpose and requirements of a software system to the developers of that system at the end of the Inception phase. COCOMO II scale factors and cost drivers rel...

Now a day’s software cost/effort estimation is a very complex job to do. Several estimation techniques have been developed in this regard. This assessment of parameters like, time, cost, and number of staff required sequentially which in turn is to be done at an early stage. Constructive Cost model which is also known as COCOMO model was one of the best model to estimate the cost and time in pe...

Good software cost prediction is important for effective project management such as budgeting, project planning and control. In this paper, we present an intelligent approach to software cost prediction. By integrating the neuro-fuzzy technique with the well-accepted COCOMO model, our approach can make the best use of both expert knowledge and historical project data. Its major advantages inclu...

Mistakes create rework. Rework takes time and increases costs. The traditional software engineering methodology defines the ratio of Design:Code:Test as 40:20:40. As we can easily see that 40% time and efforts are used in testing phase in traditional approach, that means we have to perform rework again if we found some bugs in testing phase. This rework is being performed after Design and code ...

Software cost estimation is the process of predicting the effort required to develop a software system. The basic input for the software cost estimation is coding size and set of cost drivers, the output is Effort in terms of Person-Months (PM’s). Here, the use of support vector regression (SVR) has been proposed for the estimation of software project effort. We have used the COCOMO dataset and...

In this paper, we have tuned the parameters of COCOMO II model to estimate the software development effort using genetic algorithm (GA). Results obtained by applying GA are have been compared with results obtained by applying particle swarm optimization (PSO) published in previous paper. COCOMO II model is modified by introducing some more parameters to predict the software development effort m...

: The main aim of the proposed system is to assist the software development team to estimate the cost, effort and maintenance of the project under development. Android-based platform, namely MIT App Inventor is used for the development of application, which contains visual block programming language. The current study has following uniqueness of (1)Accuracy of results,(2)user friendly environme...

Problem statement: The precision and reliability of the effort estimation is very important for the competitiveness of software companies. The uncertainty at the input level of the Constructive Cost Model (COCOMO) yields uncertainty at the output, which leads to gross estimation error in the effort estimation. Fuzzy logic-based cost estimation models are more appropriate when vague and imprecis...