Challenges in software project cost estimation : a comparative case study

Abstract

Estimating the cost, effort, and size to complete a software project is one of the most difficult and confusing tasks confronted by software project managers. Though, an early estimate is very crucial when bidding for contracts or determining whether the project viable, it’s accuracy cannot be guaranteed because of factors like incomplete requirements, inadequate information from past projects and the experience of the estimator. Accurate software cost estimate can help the developer make more logical decisions in planning, scheduling, allocating resource, and monitoring the project progress. Considering all the estimation models developed by various researchers, it is inevitable to say that there has not been a perfect estimation method that solves all estimation problem. The first part of this thesis provides a general overview of software estimation and some models, which are classified as algorithm and non-algorithm models. The second part is a comparative case study research, which emphasizes on two non-algorithm model, Top-down and Bottom-Up method in comparison with the estimate gotten from a software development project. The main result of this study is that it is almost impossible to evaluate an accurate and error-free estimate at the beginning of a software project. Combining two or more estimation models at the beginning of the project and enhancing the estimate as the project progresses could give the better estimate, but other factors like risk assessment, resetting expectation, unexpected unknowns and exploring the use of automation should also be considered.