The ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM) is the premier conference for presenting research results related to empirical software engineering. ESEM provides a stimulating forum where researchers and practitioners can present and discuss recent research results on a wide range of topics, in addition to exchanging ideas, experiences and challenging problems. The 13th edition of ESEM will be held in Porto de Galinhas, Brazil, from September 19th to 20th, 2019 as part of the Empirical Software Engineering International Week (Sept., 16th to 20th, 2019) with several co-located events:

• Annual International Software Engineering Network (ISERN) meeting
• International Doctoral Symposium on Empirical Software Engineering (IDoESE)
• International Advanced School on Empirical Software Engineering (IASESE)

List of Topics

In addition to the specific scope of each track, submissions may address any aspect of software engineering but must tackle the problem from an empirical perspective and using a rigorous empirical method, including:

• Empirical studies using qualitative, quantitative, and mixed methods
• Cross- and multi-disciplinary methods and studies
• Experiments and quasi-experiments
• Case studies, action research, ethnography and field studies
• Survey research
• Simulation
• Artifact studies
• Data mining, machine learning, and AI-based approaches
• Secondary and tertiary studies including
  • Systematic literature reviews that include a strong synthesis part
  • Meta-analysis, qualitative and quantitative synthesis of studies
• Replication of empirical studies and families of studies

Topics commonly addressed using an empirical approach include, but are not limited to:

• Evaluation and comparison of software technologies
• Evaluation and comparison of software development methods, techniques, and practices
• Modeling, measuring, and assessing product and/or process quality
• Modeling, measuring, and assessing software development productivity
• Defect and quality prediction
• Software cost and size estimation
• Software evolution
• Software verification and validation, including analysis and testing
• Evaluation and modeling of contemporary software systems (IoT, Industry 4.0, Context-Awareness Systems, Cyber-physical, among others)
• Human factors, teamwork, and behavioral aspects of software engineering

We welcome submissions on these meta-topics:

• Development, evaluation, and comparison of empirical approaches and methods
• Infrastructure for conducting empirical studies
• Techniques and tools for supporting empirical studies
• Empirically-based decision making

We also welcome submissions that:

• demonstrate multi-disciplinary work,
• transfer and apply empirical methods from other disciplines,
• replication studies, and studies with negative findings.