| |||||||||||||||||
ESEM 2016 : Empirical Software Engineering and MeasurementConference Series : Empirical Software Engineering and Measurement | |||||||||||||||||
Link: http://alarcos.esi.uclm.es/eseiw2016/importantdates.html | |||||||||||||||||
| |||||||||||||||||
Call For Papers | |||||||||||||||||
The ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM) is the premier conference for research results related to empirical software engineering. These include discussions of: • empirical methods and the design and analysis of empirical 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. We encourage the submission of both novel work and replication studies. 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 also exchanging ideas, experiences and challenging problems. The relevant topics include, but are not restricted to, the following: ● 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 ● Infrastructures and novel techniques/tools for supporting any phase of empirical studies ● 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 and mapping studies ● Meta-analysis, qualitative and quantitative synthesis of studies ● Replication of empirical studies and families of studies ● Empirically-based decision making ● Evaluation and comparison of techniques and models ● Development and evaluation of empirical prediction systems or software estimation models ● mining software engineering repositories ● Modeling, measuring, and assessing product and/or process quality ● Simulation-based studies in software engineering ● Assessing the benefits / costs associated with using certain development technologies ● Industrial experience, Software project experience, and knowledge management ● Software technology transfer to the industry |
|