A new software cost estimation approach is proposed in this paper, which attempts to cluster empirical, non-homogenous project data samples via an entropy-based fuzzy k-modes clustering algorithm. The target is to identify groups of projects sharing similar characteristics in terms of cost attributes or descriptors, and utilise this grouping information to provide estimations of the effort need...

0164-1212/$ see front matter 2009 Elsevier Inc. A doi:10.1016/j.jss.2009.10.044 * Corresponding author. E-mail addresses: [email protected] (N. Mittas), The well-balanced management of a software project is a critical task accomplished at the early stages of the development process. Due to this requirement, a wide variety of prediction methods has been introduced in order to identify the best...

Estimating the cost of software is a complex process for almost all engineering companies. Uncertainties about development method, design, estimation process, data, and processing affect the accuracy of estimation. Underestimation results in fewer resources being committed than the project really needs, an unrealistic schedule, and low quality outputs. On the other hand, overestimation wastes r...

This paper investigates the use of various techniques including genetic programming, with public data sets, to attempt to model and hence estimate software project effort. The main research question is whether genetic programs can offer 'better' solution search using public domain metrics rather than company specific ones. Unlike most previous research, a realistic approach is taken, whereby pr...

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Calibration, has been .found to be difficult in practice. Wide experience in using the estimation model is necessary; experience which the beginner naturally lacks. This paper indicates why it is important to calibrate a model and how the inexperienced user can be helped by an expert system. In addition, the development of, and experience with, the prototype of an expert system are described. T...

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...

Effort estimation is a key factor for software project success, defined as delivering software of agreed quality and functionality within schedule and budget. Traditionally, effort estimation has been used for planning and tracking project resources. Effort estimation methods founded on those goals typically focus on providing exact estimates and usually do not support objectives that have rece...

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...