Automated Software Engineering: A Deep Lea...

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Sprache: Englisch

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Beschreibung

This book discusses various open issues in software engineering, such as the efficiency of automated testing techniques, predictions for cost estimation, data processing, and automatic code generation. Many traditional techniques are available for addressing these problems. But, with the rapid changes in software development, they often prove to be outdated or incapable of handling the software¿s complexity. Hence, many previously used methods are proving insufficient to solve the problems now arising in software development.

The book highlights a number of unique problems and effective solutions that reflect the state-of-the-art in software engineering. Deep learning is the latest computing technique, and is now gaining popularity in various fields of software engineering. This book explores new trends and experiments that have yielded promising solutions to current challenges in software engineering. As such, it offers a valuable reference guide for a broad audience including systems analysts, software engineers, researchers, graduate students and professors engaged in teaching software engineering.

Zusammenfassung

Offers potential deep learning concepts for handling open issues in software engineering, such as the efficiency of automated testing techniques, predictions for cost estimation, data processing, and automatic code generation

Presents a deep learning based approach to Automated Software Engineering

Provides new ideas in the field of software engineering

Inhaltsverzeichnis

Chapter 1: Selection of Significant Metrics for Improving the Performance of Change-Proneness Modules.- Chapter 2: Effort Estimation of Web based Applications using ERD, use Case Point Method and Machine Learning.- Chapter 3: Usage of Machine Learning in Software Testing.- Chapter 4: Test Scenarios Generation using Combined Object-Oriented Models.- Chapter 5: A Novel Approach of Software Fault Prediction using Deep Learning Technique.- Chapter 6: Feature-Based Semi-Supervised Learning to Detect Malware from Android.

Medium:	Taschenbuch
Seiten:	132
Reihe:	Learning and Analytics in Intelligent Systems
Inhalt:	xi 118 S.
ISBN-13:	9783030380083
ISBN-10:	3030380084
Sprache:	Englisch
Ausstattung / Beilage:	Paperback
Einband:	Kartoniert / Broschiert
Autor:	Satapathy, Suresh Chandra Bilgaiyan, Saurabh Singh, Jagannath Jena, Ajay Kumar
Auflage:	1st ed. 2020
Hersteller:	Springer International Publishing Springer International Publishing AG Learning and Analytics in Intelligent Systems
Maße:	235 x 155 x 8 mm
Von/Mit:	Suresh Chandra Satapathy (u. a.)
Erscheinungsdatum:	08.01.2021
Gewicht:	0,213 kg

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