Empirical Research in Software Engineering: Concepts, Analysis, and Applications Front Cover

Empirical Research in Software Engineering: Concepts, Analysis, and Applications

  • Length: 498 pages
  • Edition: 1
  • Publisher:
  • Publication Date: 2015-10-16
  • ISBN-10: 1498719724
  • ISBN-13: 9781498719728
  • Sales Rank: #4708667 (See Top 100 Books)
Description

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.

Table of Contents

Chapter 1 Introduction
Chapter 2 Systematic Literature Reviews
Chapter 3 Software Metrics
Chapter 4 Experimental Design
Chapter 5 Mining Data from Software Repositories
Chapter 6 Data Analysis and Statistical Testing
Chapter 7 Model Development and Interpretation
Chapter 8 Validity Threats
Chapter 9 Reporting Results
Chapter 10 Mining Unstructured Data
Chapter 11 Demonstrating Empirical Procedures
Chapter 12 Tools for Analyzing Data
Appendix: Statistical Tables

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