Mining Software Engineering Data for Software Reuse Mining Software Engineering Data for Software Reuse
Advanced Information and Knowledge Processing

Mining Software Engineering Data for Software Reuse

    • 87,99 €
    • 87,99 €

Descripción editorial

This monograph discusses software reuse and how it can be applied at different stages of the software development process, on different types of data and at different levels of granularity. Several challenging hypotheses are analyzed and confronted using novel data-driven methodologies, in order to solve problems in requirements elicitation and specification extraction, software design and implementation, as well as software quality assurance.

The book is accompanied by a number of tools, libraries and working prototypes in order to practically illustrate how the phases of the software engineering life cycle can benefit from unlocking the potential of data.


Software engineering researchers, experts, and practitioners can benefit from the various methodologies presented and can better understand how knowledge extracted from software data residing in various repositories can be combined and used to enable effective decision making and save considerable time and effort through software reuse. Mining Software Engineering Data for Software Reuse can also prove handy for graduate-level students in software engineering.

GÉNERO
Informática e internet
PUBLICADO
2020
30 de marzo
IDIOMA
EN
Inglés
EXTENSIÓN
263
Páginas
EDITORIAL
Springer International Publishing
TAMAÑO
14,4
MB

Otros libros de esta serie

Seriation in Combinatorial and Statistical Data Analysis Seriation in Combinatorial and Statistical Data Analysis
2022
Provenance in Data Science Provenance in Data Science
2021
Smart Systems for E-Health Smart Systems for E-Health
2021
Artificial Intelligence in Economics and Finance Theories Artificial Intelligence in Economics and Finance Theories
2020
Adaptive Resonance Theory in Social Media Data Clustering Adaptive Resonance Theory in Social Media Data Clustering
2019
Data-intensive Systems Data-intensive Systems
2019