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. These include results on:
empirical methods as well as the design and analysis of empirical studies, ranging from controlled experiments to case studies and from quantitative to qualitative studies;
the strengths and weaknesses of software engineering technologies and methods from a strong empirical viewpoint, including quantitative, qualitative, and mixed studies; and
the systematic use of data and measurement to understand, evaluate, and model software engineering phenomena.
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 11th edition of ESEM 2017 conference will be held in Toronto, Canada from November 9th to 10th, 2017
Empirical studies using qualitative, quantitative, and mixed methods
Cross- and multi-disciplinary methods and studies
Experiments and quasi-experiments
Case studies, action research, and field studies
Survey research
Systematic literature reviews that include a strong synthesis part (not just mapping studies)
Meta-analysis, qualitative and quantitative synthesis of studies
Replication of empirical studies and families of studies
Modelling, measuring, and assessing product and/or process quality
Development and evaluation of empirical prediction systems or software estimation models
Mining software engineering repositories
Simulation-based studies in software engineering
New ideas pertaining to empirical evaluation of software engineering technologies, methods, and tools, e.g., transferring and applying empirical methods from other disciplines to empirical software engineering
Empirically-based decision making
Evaluation and comparison of techniques and models
Assessing the benefits/costs associated with using certain development technologies
Industrial experience, software project experience, and knowledge management
Software technology transfer to industry
Infrastructures and novel techniques/tools for supporting any phase of empirical studies
11月09日
2017
11月10日
2017
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