An approach to software cost estimation

A general procedure for software cost estimation in any environment is outlined. The basic concepts of work and effort estimation are explained, some popular resource estimation models are reviewed, and the accuracy of source estimates is discussed. A software cost prediction procedure based on the experiences of the Software Engineering Laboratory in the flight dynamics area and incorporating management expertise, cost models, and historical data is described. The sources of information and relevant parameters available during each phase of the software life cycle are identified. The methodology suggested incorporates these elements into a customized management tool for software cost prediction. Detailed guidelines for estimation in the flight dynamics environment developed using this methodology are presented

Qualitative Inquiry of Software Cost and Effort Estimation Techniques

Software cost and effort estimation is one of the supremeimperative asset of software industry. Effort and costprediction plays a vibrantpart in the failure or success of the software project implementation and as well as profited revenue. To survive in the market, a software house need to estimate the development cost and time before starting of project. Cost and effort estimation is most challenging decision making task, because number of developmentnecessities are not well defined and never easy to forecast on starting stage of Software building process. Number of cost and estimation techniques are currently being used, but none of these are given the 100% of accuracy in actual prediction, as these technique fall accurate in one development environment and fail in other one. Organizations want to automate the software effort and cost estimation procedures.This paper unfold the different technique of predicting cost and effort estimation based of literature review.

Software Effort Prediction - A Fuzzy Logic Approach

Accuracy in the estimation of software Effort/Cost is one of the desirable criteria for any software cost estimation model. The estimation of effort or cost before the actual development of any software is the most crucial task of the present day software development project managers. Software project attributes are often measured in terms of linguistic values such as very low, low, Average, high and very high. The imprecise nature of such attributes constitutes uncertainty and vagueness in their subsequent interpretation. In this paper we propose a Fuzzy logic based model for software effort prediction. We feel that fuzzy Software cost estimation Model should be able to deal with imprecision and uncertainty associated with various parameter values. Fuzzy analogy model has been developed and validated upon student data

Selection of software cost estimation methods : a framework regarding project- and organisation context

Abstract : Project managers and organisation management want early and accurate predictions on the effort needed to develop software. A number of alternative estimation methods have been proposed by researchers to support this. The alternative methods all tend to have drawbacks and advantages, making them suitable in different environments. Empirical results on cost estimation accuracy of software projects suggest that the selection of software cost estimation method should be context-dependent. Selecting the most appropriate among the variety of existing estimation methods regarding organisational and project context is important. This topic has almost been neglected in software cost estimation research. Developing and evolving model-based estimation techniques have dominated research. In this thesis I present a framework on software cost estimation method selection. The work is based on a study of published literature on software cost estimation and general prediction theory. The framework is based on a selection strategy called Structured Judgment. Here you evaluate the available estimation methods on a set of selection criteria. First I suggest a categorization of existing methods to sketch the alternatives available. Existing categorization have been evaluated, but found to be biased towards model-based methods. Therefore a new categorization is presented, elaborating different types of expert judgment as well. Then a number of selection criteria are presented. Research has been dominated by publications regarding accuracy as the only criteria. In my framework thirteen selection criteria are suggested to be able to consider context in an appropriate way. I propose selection criteria divided into the categories: 1) Process constraints, 2) Purpose and use, 3) Estimation capability, 4) Project characteristics and 5) Information availability. This framework has been developed considering the fact that estimation is a supportive activity with limited resources available to make a selection among alternative methods