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Empirical Software Engineering in Ultra Large Repositories: Course Overview and Insights

This course explores empirical software engineering using ultra large repositories (ULRs) to understand software evolution, challenges, and opportunities for analysis. Participants will gain insights into accessing and utilizing the World of Code repository, engage in discussions on typical ESE practices versus those observed in ULRs, and study the evolution of app ratings. The syllabus includes practical assignments and projects aimed at deepening understanding of software engineering through large-scale data analysis. Join us to learn how to leverage ULRs for advanced software engineering practices.

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Empirical Software Engineering in Ultra Large Repositories: Course Overview and Insights

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  1. Empirical Software Engineering using Ultra Large Repositories Mei Nagappan SAIL

  2. Photo: Doug Menuez/Contour by Getty Images/Stanford University Libraries

  3. Agenda • Part 1 – Introduction • Course Overview and Objectives • Student introductions and expectations • Syllabus • Assignment and Project • Part 2 – Example of an Ultra Large Repository • World of Code • How to access it? • Part 3 – Example of on ESE study • What we did? • How we did it?

  4. Typical ESE vs ESE in ULR

  5. What can we learn about SE from these Ultra Large Repositories?

  6. Challenges Mining Sample Selection Analysis Noise

  7. Syllabus • Project and Assignment • Break

  8. Example Study How do ratings evolve?

  9. 128K+

  10. Are Most Apps Great ? NO

  11. Lots of Apps with very few Ratings 128K+ 10K+

  12. Most apps are Average

  13. More Raters => Steady Ratings

  14. More Raters => Steady Ratings

  15. Low Local Rating => Stable More than 1 star drop => Unrecoverable High Local Rating => Unstable

  16. Dimensions of Study Design

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