Content: Introduction What Is Empirical Software Engineering? Overview of Empirical Studies Types of Empirical Studies Empirical Study Process Ethics of Empirical Research Importance of Empirical Research Basic Elements of Empirical Research Some Terminologies Concluding Remarks Systematic Literature Reviews Basic Concepts Case Study Planning the Review Methods for Presenting Results Conducting the Review Reporting the Review SRs in Software Engineering Software Metrics Introduction Measurement Basics Measuring Size Measuring Software Quality OO Metrics Dynamic Software Metrics System Evolution and Evolutionary Metrics Validation of Metrics Practical Relevance Experimental Design Overview of Experimental Design Case Study: Fault Prediction Systems Research Questions Reviewing the Literature Research Variables Terminology Used in Study Types Hypothesis Formulation Data Collection Selection of Data Analysis Methods Mining Data from Software Repositories Configuration Management Systems Importance of Mining Software Repositories Common Types of Software Repositories Understanding Systems Version Control Systems Bug Tracking Systems Extracting Data from Software Repositories Static Source Code Analysis Software Historical Analysis Software Engineering Repositories and Open Research Data Sets Case Study: Defect Collection and Reporting System for Git Repository Data Analysis and Statistical Testing Analyzing the Metric Data Attribute Reduction Methods Hypothesis Testing Statistical Testing Example-Univariate Analysis Results for Fault Prediction System Model Development and Interpretation Model Development Statistical Multiple Regression Techniques ML Techniques Concerns in Model Prediction Performance Measures for Categorical Dependent Variable Performance Measures for Continuous Dependent Variable Cross-Validation Model Comparison Tests Interpreting the Results Example-Comparing ML Techniques for Fault Prediction Validity Threats Categories of Threats to Validity Example-Threats to Validity in Fault Prediction System Threats and Their Countermeasures Reporting Results Reporting and Presenting Results Guidelines for Masters and Doctoral Students Research Ethics and Misconduct Mining Unstructured Data Introduction Steps in Text Mining Applications of Text Mining in Software Engineering Example-Automated Severity Assessment of Software Defect Reports Demonstrating Empirical Procedures Abstract Introduction Related Work Experimental Design Research Methodology Analysis Results Discussion and Interpretation of Results Validity Evaluation Conclusions and Future Work Appendix Tools for Analyzing Data WEKA KEEL SPSS MATLAB R Comparison of Tools Appendix References Index Exercises and Further Reading appear at the end of most chapters.