1st International Symposium on Empirical Software Engineering and Measurement, Madrid, Spanien

ISESE and Metrics symposia have just merged and the 2007 symposium will be the first combined International Symposium on Empirical Software Engineering and Measurement (ESEM&#8242;07)&#046; ISESE and Metrics have continuously attracted participants from industry, research, and academia alike, confirming that both symposia provide topics that are up&#8211;to&#8211;date, significant, and interesting&#046;<br>The objective of ESEM is to provide a forum where researchers and practitioners can report and discuss recent research results in the areas of empirical software engineering and software measurement&#046;<br>The symposium encourages the exchange of ideas that help understand, from an empirical viewpoint, the strengths and weaknesses of software engineering technologies&#046; It focuses on the processes, design and structure of empirical studies, and the results of specific studies&#046; These studies may vary from controlled experiments to field studies and from quantitative to qualitative studies&#046; The symposium also provides a forum for exploring the use of data and measurement to understand, evaluate, and model software engineering phenomena&#046;<br><b>Keywords:</b> * Empirical studies of software processes and products<br>* Evaluation and comparison of techniques and models<br>* Reports on the benefits derived from using certain technologies<br>* Empirically&#8211;based decision making<br>* Development of predictive models<br>* Measurement theory and fundamental issues<br>* Qualitative methods<br>* Families of experiments<br>* Replication of empirical studies<br>* Industrial experience in process improvement<br>* Quality measurement and assurance<br>* Experience management<br>* Systematic reviews<br>* Evidence&#8211;based software engineering<br>* Infrastructures and novel techniques for conducting empirical/experimental studies<br>* Mining data from software repositories<br>* Measurement education and empirical studies with students<br>* Effort and cost estimation, defect rate and reliability prediction<br>