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Estimation by Analogy is a popular method in the field of software cost estimation. A number of research approaches focus on optimizing the parameters of the method. This paper proposes an optimal global setup for determining empirically the best method parameter configuration based on genetic algorithms. We describe how such search can be performed, and in particular how spaces whose dimension...

[Background]: Systematic Literature Review (SLR) has become an important software engineering research method but costs tremendous efforts. [Aim]: This paper proposes an approach to leverage on empirically evolved ontology to support automating key SLR activities. [Method]: First, we propose an ontology, SLRONT, built on SLR experiences and best practices as a groundwork to capture common termi...

Accurate cost estimation helps to complete project within time and budget. Many estimation models have been proposed over the last 30 years. This paper provides a detail overview of existing software cost estimation models and techniques. Cost estimation models are basically of two types: algorithmic and non-algorithmic. It also includes the recent developed techniques for software cost estimat...

Problem statement: The spiraling growth of IT industry has witnessed an unprecedented change in the software development paradigm, from algorithmic models to machine learning techniques. At present, there are no standard methods to predict the accuracy of software cost estimation, which is an important goal of the software community. Approach: This study proposes a simple and systematic algorit...

This paper looks into productivity of 634 software projects completed between 2009 and 2013 within the IT department of the Dutch tax administration. A predictive neural network based model is developed in order to produce better estimates for future development efforts. Direct cost drivers and numerous organizational changes are identified in order to analyze their impact on productivity. The ...

Software development effort estimation is one of the most major activities in software project management. A number of models have been proposed to construct a relationship between software size and effort; however we still have problems for effort estimation. This is because project data, available in the initial stages of project is often incomplete, inconsistent, uncertain and unclear. The n...

Software development effort is one of the most important metrics that must be correctly estimated in software projects. Analogy-based estimation (ABE) and artificial neural networks (ANN) are the most popular methods used widely in this field. These methods suffer from inconsistent and irrelevant projects that exist in the software project datasets. In this paper, a new hybrid method is propose...

Software effort estimation is one of the most critical and complex, but an inevitable activity that takes place during the early stages of SDLC. Software size estimate is one of the most popular inputs for software effort prediction models. Providing a good size estimate for the purpose of accurately estimating the development effort is a challenging problem. During estimation activities, the u...

The growing complexity and number of software projects requires both increasingly more experienced developers, testers and other specialists as well as a larger number of persons to fill these roles. This leads to increased personnel and management costs and also makes effort and cost estimation at task and activity levels more difficult for software development companies. An automated solution...