Name: Analysis and Design of Software Development Effort Estimation (Paperback) (en Inglés)
SKU: 50625283
Price: 60.22 USD
Availability: InStock
Author: Vickraman Vignaraj Ananth Narayanan Balaji Nagarajan Shivakumar

portada Analysis and Design of Software Development Effort Estimation (Paperback) (en Inglés)

Analysis and Design of Software Development Effort Estimation (Paperback) (en Inglés)

Formato

Libro Físico

Editorial

LAP Lambert Academic Publishing, Germany

Autor

Vickraman Vignaraj Ananth Narayanan Balaji Nagarajan Shivakumar

Idioma

Inglés

N° páginas

144

Encuadernación

Tapa Blanda

ISBN13

9786139887828

Analysis and Design of Software Development Effort Estimation (Paperback) (en Inglés)

Vickraman Vignaraj Ananth Narayanan Balaji Nagarajan Shivakumar (Autor) · LAP Lambert Academic Publishing, Germany · Tapa Blanda

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Reseña del libro "Analysis and Design of Software Development Effort Estimation (Paperback) (en Inglés)"

The book organized as follows: Chapter 1 describes the Software development process, need for effort estimation, and different approaches in algorithmic effort estimation techniques. chapter 2 presents literature survey of existing approaches available in the effort estimation, and provide a detailed report on the non-algorithmic combination of approaches to improve the estimation accuracy. Chapter 3 proposes a new effort estimation method based on fuzzy logic with function point size. The triangular fuzzy membership function is used with size parameter in function point. This model is compared with COCOMO model for its accuracy. Chapter 4 proposes Adaptive Neuro-fuzzy scheme proposed to integrate the concept of Artificial Neural network and fuzzy logic. Chapter 5 proposes particle swarm optimization and K means hybrid algorithm for clustering the data, and effort is estimated with neural network and analogy based estimation. Chapter 6 is a comparison of all the proposed models in four experiments. The metrics used are MRE, MAE, MBRE and MIBRE. The results show that both neuro-fuzzy and clustering algorithms are the best in estimating the software effort.