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    DISTINGUISHING PATTERN DIFFERENCES FROM NON-PATTERN DIFFERENCES
    1.
    发明公开
    DISTINGUISHING PATTERN DIFFERENCES FROM NON-PATTERN DIFFERENCES 审中-公开

    公开(公告)号：US20230214212A1

    公开(公告)日：2023-07-06

    申请号：US17568597

    申请日：2022-01-04

    Applicant: Microsoft Technology Licensing, LLC

    Inventor： David Ellis PUGH ,  Mark Alistair WILSON-THOMAS ,  Vu Minh LE

    IPC: G06F8/71 ,  G06F40/197

    CPC classification number: G06F8/71 ,  G06F40/197

    Abstract: Distinguishing pattern differences from non-pattern differences. A set of differences is identified. The set comprises a plurality of differences between first and second versions of a document. A pattern is identified. The pattern explains a transformation from a first string in the first version of the document to a second string in the second version of the document. A subset of differences are identified. The subset comprises a plurality of differences, from among the set, which match the pattern. While presenting a user interface that visually highlights differences between the first and second versions of the document, a first visual treatment is applied to a first difference, based on the first difference being included in the subset. A second visual treatment is also applied to a second difference, based on the second difference being excluded from the subset. The second visual treatment is different than the first visual treatment.

    MULTI-MODAL PROGRAM INFERENCE
    2.
    发明公开
    MULTI-MODAL PROGRAM INFERENCE 审中-公开

    公开(公告)号：US20230176829A1

    公开(公告)日：2023-06-08

    申请号：US17544502

    申请日：2021-12-07

    Applicant: Microsoft Technology Licensing, LLC

    Inventor： Kiarash RAHMANI ,  Mohammad RAZA ,  Sumit GULWANI ,  Vu Minh LE ,  Daniel James MORRIS ,  Arjun RADHAKRISHNA ,  Gustavo ARAUJO SOARES ,  Ashish TIWARI

    IPC: G06F8/33 ,  G06F40/40 ,  G06F8/38 ,  G06F40/30 ,  G06F8/10

    CPC classification number: G06F8/33 ,  G06F40/40 ,  G06F8/38 ,  G06F40/30 ,  G06F8/10

    Abstract: Embodiments use a multi-modal approach to generate software programs that match a solution program description. The solution program description may include natural language, input-output examples, partial source code, desired operators, or other hints. Some embodiments use optimized prompts to a pre-trained language model to obtain initial candidate programs. Maximal program components are extracted and then recombined variously using component-based synthesis. Beam search reduces a solution program search space by discarding some candidates from a given synthesis iteration. Relevance metrics, string similarity metrics, operator frequency distributions, token rareness scores, and other optimizations may be employed. By virtue of optimizations and the multi-modal approach, a solution program may be obtained after fewer iterations than by use of a language model alone. The multi-modal approach is domain agnostic, as illustrated by examples using regular expression and cascading style sheet selector domain specific languages.

    SOURCE CODE TEXT REPLACEMENT BY EXAMPLE
    10.
    发明申请
    SOURCE CODE TEXT REPLACEMENT BY EXAMPLE 有权

    公开(公告)号：US20210349698A1

    公开(公告)日：2021-11-11

    申请号：US16869414

    申请日：2020-05-07

    Applicant: Microsoft Technology Licensing, LLC

    Inventor： Mark Alistair WILSON-THOMAS ,  Vu Minh LE ,  Sumit GULWANI

    IPC: G06F8/36 ,  G06F8/33 ,  G06F8/51

    Abstract: Flexible yet efficient “find” operations search source code for matches to a general pattern after a developer provides an example string that matches the pattern, without requiring the developer to write a regular expression or script that will implement the desired pattern. Example-driven find-replace functionality uses regular expressions or other pattern match codes, and scripts or other transforms, which are synthesized automatically from examples provided by a developer. This technology allows the developer to focus on workflow inside an integrated development environment instead of breaking focus to search for external documentation, or unfortunately foregoing the flexibility and power of regular expressions and scripts. Synthesizer outputs may be directly or indirectly ranked through user feedback, allowing their refinement. Find match generality may be controlled, e.g., by specifying regex star positions or star counts. Entry of guiding examples may be assisted by autocompletion. Performance criteria are also described.

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