Name: Empirical Research in Software Engineering: Concepts, Analysis, and Applications (en Inglés)
SKU: 56037883
Price: 164.99 USD
Availability: InStock
Author: Malhotra, Ruchika
ISBN: 9781498719728

portada Empirical Research in Software Engineering: Concepts, Analysis, and Applications (en Inglés)

Empirical Research in Software Engineering: Concepts, Analysis, and Applications (en Inglés)

Formato

Libro Físico

Autor

Ruchika Malhotra

Editorial

CRC Press

Idioma

Inglés

N° páginas

472

Encuadernación

Tapa Dura

Dimensiones

25.7x17.8x3.3 cm

Peso

1.09 kg.

ISBN13

9781498719728

N° edición

Categorías

Probabilidad y estadística
Ingeniería electrónica
Programación informática/desarrollo de software
Ciencias de la computación

Empirical Research in Software Engineering: Concepts, Analysis, and Applications (en Inglés)

Ruchika Malhotra (Autor) · CRC Press · Tapa Dura

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Reseña del libro "Empirical Research in Software Engineering: Concepts, Analysis, and Applications (en Inglés)"

Empirical research has now become an essential component of software engineering yet software practitioners and researchers often lack an understanding of how the empirical procedures and practices are applied in the field. Empirical Research in Software Engineering: Concepts, Analysis, and Applications shows how to implement empirical research processes, procedures, and practices in software engineering.Written by a leading researcher in empirical software engineering, the book describes the necessary steps to perform replicated and empirical research. It explains how to plan and design experiments, conduct systematic reviews and case studies, and analyze the results produced by the empirical studies. The book balances empirical research concepts with exercises, examples, and real-life case studies, making it suitable for a course on empirical software engineering. The author discusses the process of developing predictive models, such as defect prediction and change prediction, on data collected from source code repositories. She also covers the application of machine learning techniques in empirical software engineering, includes guidelines for publishing and reporting results, and presents popular software tools for carrying out empirical studies.