A comparison of cross-company and within-company effort estimation models for Web applications

2004 ◽  
Author(s):  
B.A. Kitchenham
Keyword(s):  
Web Applications ◽  
Effort Estimation ◽  
Estimation Models

Feasibility and effort estimation models for medium and small size information mining projects

2015 ◽  
Vol 47 ◽  
pp. 1-14 ◽  
Author(s):  
Pablo Pytel ◽  
Alejandro Hossian ◽  
Paola Britos ◽  
Ramón García-Martínez
Keyword(s):  
Effort Estimation ◽  
Information Mining ◽  
Size Information ◽  
Mining Projects ◽  
Estimation Models

The Application of Meta-Heuristic Algorithms to Improve the Performance of Software Development Effort Estimation Models

2015 ◽  
Vol 6 (4) ◽  
pp. 39-68 ◽  
Author(s):  
Maryam Hassani Saadi ◽  
Vahid Khatibi Bardsiri ◽  
Fahimeh Ziaaddini
Keyword(s):  
Software Development ◽  
Optimization Algorithms ◽  
Heuristic Optimization ◽  
Development Effort ◽  
Special Role ◽  
Effort Estimation ◽  
Software Projects ◽  
Software Development Effort ◽  
Estimation Models ◽  
Software Development Effort Estimation

One of the major activities in effective and efficient production of software projects is the precise estimation of software development effort. Estimation of the effort in primary steps of software development is one of the most important challenges in managing software projects. Some reasons for these challenges such as: discordant software projects, the complexity of the manufacturing process, special role of human and high level of obscure and unusual features of software projects can be noted. Predicting the necessary efforts to develop software using meta-heuristic optimization algorithms has made significant progressions in this field. These algorithms have the potent to be used in estimation of the effort of the software. The necessity to increase estimation precision urged the authors to survey the efficiency of some meta-heuristic optimization algorithms and their effects on the software projects. To do so, in this paper, they investigated the effect of combining various optimization algorithms such as genetic algorithm, particle swarm optimization algorithm and ant colony algorithm on different models such as COCOMO, estimation based on analogy, machine learning methods and standard estimation models. These models have employed various data sets to evaluate the results such as COCOMO, Desharnais, NASA, Kemerer, CF, DPS, ISBSG and Koten & Gary. The results of this survey can be used by researchers as a primary reference.

Understanding Project Data

2008 ◽  
pp. 303-374
Author(s):  
Emilia Mendes
Keyword(s):  
Large Body ◽  
Statistical Techniques ◽  
Effort Estimation ◽  
Estimation Techniques ◽  
Body Of Knowledge ◽  
Project Data ◽  
Estimation Models

The objective of this chapter is to provide an introduction to statistical techniques and concepts that are frequently used when dealing with data for effort estimation. The concepts presented here are in no way exhaustive since statistics comprises a very large body of knowledge where entire books are devoted to specific topics. The parts that are the focus of this chapter are those that are necessary to use when building effort estimation models, and also when comparing different effort estimation techniques.

Sign in / Sign up

Export Citation Format

Share Document