Using topic models to understand programming languages literature
Kathleen Fisher is Professor in the Computer Science Department at Tufts. Previously, she was a Principal Member of the Technical Staff at AT&T Labs Research, a Consulting Faculty Member in the Computer Science Department at Stanford University, and a program manager at DARPA where she started and managed the HACMS and PPAML programs. Kathleen’s research focuses on advancing the theory and practice of programming languages and on applying ideas from the programming language community to the problem of ad hoc data management. The main thrust of her work has been in domain-specific languages to facilitate programming with massive amounts of ad hoc data, including the Hancock system for efficiently building signatures from massive transaction streams and the PADS system for managing ad hoc data.
Kathleen is an ACM Fellow. She has served as program chair for FOOL, ICFP, CUFP, and OOPSLA. Kathleen is past Chair of the ACM Special Interest Group in Programming Languages (SIGPLAN), past Co-Chair of CRA’s Committee on the Status of Women (CRA-W), and a former editor of the Journal of Functional Programming.
Tue 7 Jul Times are displayed in time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
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|Problems and opportunities — Program similarity|
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|Inferring Coding Conventions with Machine Learning|
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|Using topic models to understand programming languages literature|
Kathleen FisherTufts University
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|Scaling Program Synthesis by Exploiting Existing Code|