Annie T.T. Ying

PhD Candidate, McGill University

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I am a computer scientist. I seek problems with impact and solve them using methods from a variety of fields, from software engineering/programming language technologies to machine learning/data mining (I believe in opportunities in data) and qualitative methods (I believe in the people and stories beyond the numbers).

I am currently finishing my PhD thesis at McGill University, while taking a leave of absence from IBM T.J. Watson Research Center.

My PhD thesis is about summarization of code examples: the generation succinct version of the original code.

First, I used a machine-learning based approach to highlight important lines of code, based on some easy-to-generate code features. Even with this approach I can generate summaries that are comparable to what a human would generate. [ESEC/FSE 2013 paper]

Second, using a mix of qualitative and quantitative methods, I studied how humans summarize code examples and elicited a list of summarization practices. [FSE 2014 paper - Winner of an ACM SIGSOFT Distinguished Paper Award]

Based on these practices, I formulate a novel summarization problem: the generation of 2-dimensional code summaries, and an optimization based algorithm.




Predicting software changes by mining revision history
M.Sc. Thesis, University of British Columbia, 2003

Visualizing global exception flow
B.Sc. (Honours) Thesis, University of British Columbia, 2001

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