Analyzing the Entire Program: Applying Natural Language Processing to Software Engineering
- Michael D. Ernst | University of Washington
A powerful, but limited, way to view software is as source code alone. Mathematical techniques, such as abstract interpretation and model checking, can indicate whether the program satisfies a formal specification. But, where does the formal specification come from? A program consists of much more than a sequence of instructions. Developers make use of test cases, documentation, variable names, program structure, the version control repository, and more. I argue that it is time to take the blinders off of software analysis tools: tools should use all these artifacts to deduce more powerful and useful information about the program. Researchers are beginning to make progress towards this vision. In this talk, I will discuss four initial results that find bugs and generate code, by making use of variable names, error messages, procedure documentation, and user questions.
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Tom Zimmermann
Sr. Principal Researcher
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Series: Microsoft Research Talks
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Decoding the Human Brain – A Neurosurgeon’s Experience
- Dr. Pascal O. Zinn
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Challenges in Evolving a Successful Database Product (SQL Server) to a Cloud Service (SQL Azure)
- Hanuma Kodavalla,
- Phil Bernstein
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Improving text prediction accuracy using neurophysiology
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Tongue-Gesture Recognition in Head-Mounted Displays
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DIABLo: a Deep Individual-Agnostic Binaural Localizer
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Audio-based Toxic Language Detection
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From SqueezeNet to SqueezeBERT: Developing Efficient Deep Neural Networks
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- Sujeeth Bharadwaj
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Hope Speech and Help Speech: Surfacing Positivity Amidst Hate
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Towards Mainstream Brain-Computer Interfaces (BCIs)
- Brendan Allison
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Learning Structured Models for Safe Robot Control
- Subramanian Ramamoorthy
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