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Variants of adaptation techniques have been proposed in previous studies to improve the performance of analogy-based effort estimation. The results of these studies are often contradictory and cannot simply be generalized because there are many uncontrollable source of variations between adaptation studies. The study presented in this paper has been carried(More)
Accurate and credible software effort estimation is a challenge for academic research and software industry. From many software effort estimation models in existence, Estimation by Analogy (EA) is still one of the preferred techniques by software engineering practitioners because it mimics the human problem solving approach. Accuracy of such a model depends(More)
Context: Software effort estimation at early stage is a crucial task for project bedding and feasibility study. Since collected data at early stage of software development lifecycle is always imprecise and uncertain, it is very hard to deliver accurate estimate. Analogy-based estimation, which is one of the popular estimation methods, is rarely used at(More)
A reliable and accurate similarity measurement between two software projects has always been a challenge for analogy-based software cost estimation. Since the effort for a new project is retrieved from similar historical projects, it is essentially to use the appropriate similarity measure that finds those close projects which in turn increases the(More)
Software effort prediction is an important task in the software development life cycle. Many models including regression models, machine learning models, algorithmic models, expert judgment and estimation by analogy have been widely used to estimate software effort and cost. In this work, a Treeboost (Stochastic Gradient Boosting) model is put forward to(More)
Delivering accurate software effort estimation has been a research challenge for a long time, where none of the existing estimation methods has proven to consistently deliver an accurate estimate. Previous studies have demonstrated that estimation by analogy (EBA) is a viable alternative to other conventional estimation methods in terms of predictive(More)