Joint 7th International Workshop on Conducting Empirical Studies in Industry (CESI 2019) and 6th International Workshop on Software Engineering Research and Industrial Practice (SER&IP 2019)

Country: Canada

City: Montreal

Abstr. due: 01.02.2019

Dates: 28.05.19 — 28.05.19

Area Of Sciences: Technical sciences;

Organizing comittee e-mail:

Organizers: CESI


Due to their closeness, CESI and SER&IP merged for 2019. Both look into challenges in the cooperation between SE research and industry. Researchers have a view that practitioners are reluctant to share data. Practitioners believe that researchers are mostly working on theoretical challenges. Researchers believe that practitioners are looking for quick fixes to their problems. Practitioners have a view that case studies in research do not represent the complexities of real projects and have doubts in the results produced by research. Hence, empirical studies are necessary to ensure the relevance and applicability of software engineering research. A recent trend is data-driven software development (i.e., software development where development decisions are based on and driven by data from both development time and run time). Building on the results of previous editions of CESI and SER&IP the 2019 edition focuses on investigating the use of data-driven development approaches and how to integrate the gained knowledge and insights from data-driven development with the existing empirical body of knowledge, and how development could complement empirical research or even be supported by empirical research methods.

Topics of interest include, but are not limited to: 

  • Business models or collaboration models between researchers and practitioners 
  • Challenges, issues, bottlenecks and gaps in adoption of research 
  • What industry wants from research and what research wants from industry 
  • Practical challenges that have potential for research 
  • Stories and practices from SE research-practice partnerships 
  • Tools for industry 
  • Data-driven development approaches used in industry (experience reports) 
  • Data analytics in service, product and process development and maintenance 
  • Accessing, sharing, publishing datasets and insights from data analytics 
  • Integration of empirical research and data-driven development/data analytics 
  • Integration of results from data analytics and empirical work 
  • Understanding failures and successes, lessons learned 


Conference Web-Site:

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