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PROSE

AI-Assisted Programming

新闻与深度文章

Research Focus: May 07, 2025
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In this issue: New research on compound …

Research Focus: Week of November 11, 2024
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Holistic motion-capture calibration tech…

background pattern
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New Research | FLASH: Workflow automatio…

Research Focus | October 7, 2024
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Simplifying secure decision tree trainin…

Rubicon paper at Alware 2024
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| Param Biyani, Yasharth Bajpai, Arjun Radhakrishna, Gustavo Soares, 和 Sumit Gulwani

RUBICON evaluates AI-driven conversation…

Research Focus: Week of April 29, 2024
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In this edition: Can LLMs transform natu…

Research Focus March 20, 2024
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Welcome to Research Focus, a series of b…

Microsoft Research Focus 19 | Week of July 3, 2023
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In this issue: A new study looks at engi…

An illustration of resolving a bad merge into a safe merge. Moving from left to right, circles on a continuous line represent code commits in a version control system. A circle labeled “Base” is the most common ancestor of the commits marked A and B, respectively. All three commits pass the project’s quality gates, denoted by green check marks alongside each of these commits. The subsequent merge results in a failure of some quality gate, denoted by a blue circle labeled “Bad merge” with a red x above it. The repair uses machine learning, denoted by an abstract image of a neural network, and program verification and synthesis, denoted by a formal inference rule containing math symbols, to construct a safe merge that passes the quality gate, denoted by a circle outlined in green with a green check mark above it.   
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| Shuvendu Lahiri

Since the computing world began embracin…