Empirical Software Engineering using Ultra Large Repositories

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Empirical Software Engineering using Ultra Large Repositories. Mei Nagappan SAIL. Photo: Doug Menuez /Contour by Getty Images/Stanford University Libraries. Agenda. Part 1 – Introduction Course Overview and Objectives Student introductions and expectations Syllabus Assignment and Project - PowerPoint PPT Presentation

Transcript of Empirical Software Engineering using Ultra Large Repositories

Empirical Software Engineering using Ultra Large Repositories

Mei NagappanSAIL

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

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?

Typical ESE vs ESE in ULR

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

Challenges

Mining Sample Selection Analysis Noise

• Syllabus• Project and Assignment• Break

Example Study

How do ratings

evolve?

128K+

Are Most Apps Great ?

NO

Lots of Apps with very few Ratings

128K+

10K+

Most apps are Average

More Raters => Steady Ratings

More Raters => Steady Ratings

Low Local Rating => Stable

High Local Rating => Unstable

More than 1 star drop => Unrecoverable

Dimensions of StudyDesign