No Code Required: Giving Users Tools to Transform the Web
No Code Required: Giving Users Tools to Transform the Web
A qualitative study of animation programming in the wild
Proceedings of the 2010 ACM-IEEE International Symposium on Empirical Software Engineering and Measurement
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Repositories of code written by end-user programmers are beginning to emerge, but when a piece of code is new or nobody has yet reused it, then current repositories provide users with no information about whether that code might be appropriate for reuse. Addressing this problem requires predicting reusability based on information that exists when a script is created. To provide such a model for web macro scripts, we identified script traits that might plausibly predict reuse, then used IBM CoScripter repository logs to statistically test how well each corresponded to reuse. We then built a machine learning model that combines the useful traits and evaluated how well it can predict four different types of reuse that we saw in the repository logs. Our model was able to predict reuse from a surprisingly small set of traits. It is simple enough to be explained in only 6–11 rules, making it potentially viable for integration in repository search engines for end-user programmers.