Listen to this interview of Arjun Guha, Associate Professor, Northeastern University. We talk about his coauthored paper MultiPL-E: A Scalable and Polyglot Approach to Benchmarking Neural Code Generation (TSE 2023).
Arjun Guha : "My group and our collaborating colleagues really try to pick problems carefully so that we choose a problem that we can attack with the expertise that we have. So, for example, to pull off a benchmark like the one in this paper, you needed a group of students who were all interested in their own weird programming languages."
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Scholarly Communication