Why is generality so hard to find in software engineering? Do such general principles exist (and we just have not found them yet)? Or are we doomed to a perpetual revision of all our coding and management practices for each new project? On this issue, we can identify two feuding schools of thought. Globalists and localists use different strategies for learning best practices. Globalists learn lessons once from all data then reuse those lessons at multiple sites, whereas localists learn best practices many times from local data and use them only at a single site (which implies that project managers must devote their scant resources to a "local lessons team" that pursues best local practices).
This workshop will focus on the following issue: Whose strategy is best for finding project-specific best practices: the globalists or the localists? Or perhaps it is best to combine both approaches. It is certainly important to learn best practices from past projects. However, it is just as important to know how to transfer and adapt that experience to current projects. No project is exactly like previous projects -- hence, the trick is to find which parts of the past are most relevant and can be transferred into the current project.
Call for paper
Submission Topics
Topics of interest are theoretical foundations and practical approaches related, but not limited, to the integration of the transfer learning and software engineering. While our focus in on automatic methods, we are also interested in hybrid human/compute
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