Pruning Engine
    1.
    发明申请

    公开(公告)号:US20250068400A1

    公开(公告)日:2025-02-27

    申请号:US18943525

    申请日:2024-11-11

    Inventor: Tushar Makkar

    Abstract: A method and apparatus are disclosed for enhancing operable functionality of input source code files from a software program by preprocessing input source code files with codeword processing operations to generate a plurality of preprocessed input source code files, identifying candidate code snippets by pruning one or more preprocessed input source code files that do not meet a similarity threshold measure for library functions stored in the system library, and identifying at least a first validated code snippet from the one or more candidate code snippets that matches a first library function stored in the system memory on the basis of at least first and second matching metrics.

    Method and apparatus for automatically generating an application code and framework

    公开(公告)号:US12229537B2

    公开(公告)日:2025-02-18

    申请号:US18202342

    申请日:2023-05-26

    Abstract: Various methods, apparatuses/systems, and media for automatically building an application framework are disclosed. An internal database stores available design patterns and code snippets for developing an application. A receiver receives, as input, a requirement document that includes one or more requirements for developing the application. A processor parses the requirement document by implementing a natural language processing algorithm; creates, based on the parsed requirement document, a plurality of code blocks for generating a structure and a design pattern to be used to develop the application by matching the one or more requirements with the available design patterns; accesses the database to obtain the code snippets for the plurality of code blocks; and automatically builds an application framework based on the code snippets.

    Augmented intelligence for creating software development artifacts

    公开(公告)号:US12229535B2

    公开(公告)日:2025-02-18

    申请号:US18130032

    申请日:2023-04-03

    Inventor: Sunil Kaitha

    Abstract: Embodiments disclose systems and methods for generating source code. One or more application specific inputs and one or more external inputs are received. Using a machine learning model, source code is automatically generated based on the one or more application specific inputs and the one or more external inputs. The source code can embody the one or more application specific inputs and the one or more external inputs. One or more revisions to the automatically generated source code may be made, and a difference determined between the generated source code and the revised source code. The machine learning model may be further trained to generate a future source code based on the differences it determines.

    SOURCE AND MODEL FRAMEWORK
    4.
    发明申请

    公开(公告)号:US20250053393A1

    公开(公告)日:2025-02-13

    申请号:US18766531

    申请日:2024-07-08

    Abstract: The inventions disclosed herein relate to frameworks for abstracting specifics, and in particular to frameworks for abstracting specifics about datasets from jobs and frameworks for specifying models for data in data sets. Objects in a data stream can be described by the same non-recursive data model, which may be declared for example as a non-recursive Scala type in the framework.

    MAPPING DESIGN ARTIFACTS TO A REFERENCE FRAMEWORK

    公开(公告)号:US20250053386A1

    公开(公告)日:2025-02-13

    申请号:US17664341

    申请日:2022-05-20

    Abstract: This disclosure describes techniques that include the design, development, and/or use of a structure, metadata specification, or language that facilitates the transition of design artifacts directly into a structured programming code template. In one example, this disclosure describes a method comprising enabling a domain-driven design process for an application, wherein the domain-driven design process produces a plurality of design artifacts associated with a domain-driven design of the application; outputting, by a computing system, a user interface configured to receive information about a mapping of the plurality of design artifacts to a framework of library code; identifying, by the computing system and for the design artifacts, a code template from the framework of library code; generating, by the computing system and based on the identified code templates, a skeleton application; enabling, by the computing system, modification of the skeleton application to produce a production application.

    Augmented reality powered auto code generator

    公开(公告)号:US12223295B2

    公开(公告)日:2025-02-11

    申请号:US18138779

    申请日:2023-04-25

    Abstract: A method for deploying executable programming code, in real-time, leveraging an augmented reality (“AR”) device may be provided. The AR device may be a part of a network of AR devices. Each AR device within the network may be in electronic communication with each other during a duration of time that data displayed is captured, converted, analyzed, code generated and further visualized as a preview in an AR display through the AR device. The method may include capturing, continuously, images of data displayed on a display screen. The method may further include analyzing each captured image in order to identify a captured image comprising a plurality of text associated with computer processing steps for processing a set of documents. In response to the identifying, converting the captured image into a text file and searching to find an optimal function for each step in the set of computer processing steps.

    METHODS AND SYSTEMS FOR SELF-OPTIMIZING LIBRARY FUNCTIONS

    公开(公告)号:US20250036377A1

    公开(公告)日:2025-01-30

    申请号:US18225712

    申请日:2023-07-25

    Inventor: Sandeep Verma

    Abstract: Provided herein is a machine learning engine for increasing efficiency of an application written in a computer code, the code associated with a programing library that includes a library function, the function being associated with a default algorithm and a plurality of alternate algorithms. The machine learning engine may be configured to scan the code to identify occurrences of the library function; create altered application versions having altered algorithm(s); instruct a processor to iteratively execute the altered versions of the application; record an execution parameter associated with executing the library function at each occurrence; and output an optimized algorithm associated with the library function for each occurrence, based at least in part on the execution parameter.

    SYSTEMS AND METHODS FOR PROVIDING INTERACTIVE SOFTWARE-DEVELOPMENT LINKS VIA USER INTERFACES

    公开(公告)号:US20250028524A1

    公开(公告)日:2025-01-23

    申请号:US18353872

    申请日:2023-07-17

    Abstract: Providing interactive software-development links via user interfaces, based on remotely retrieved information from remote computer networks without requiring users to transition between websites within the user interfaces may be facilitated. In some embodiments, an Application Programming Interface (API) may be provided that is configured to receive one or more commands from a first server and a second server. The system may receive via a monitoring-function installed on a client device, a first message from the first server to update a source code file stored in a software-version controlled repository. The system may determine from the first message, a source code file identifier. The system may then receive, via the monitoring-function, a second message from the second server indicating an update associated with a software-development automation service platform. The system may determine, from the second message, a feature update characteristic and may display a message comprising the source code file identifier and the feature update characteristic.

    Machine learning methods for source code quality analysis

    公开(公告)号:US12197913B1

    公开(公告)日:2025-01-14

    申请号:US17114049

    申请日:2020-12-07

    Applicant: MUSE DEV, INC.

    Abstract: A preferably cloud-based platform supports improvements in software development by assessing quality of source code files, for example, when files are pushed to a software repository. Various static analysis tools are executed on a source file, and the resulting bug reports, which reflect native features of the tools are assembled in a dataset. The bug dataset is enhanced by adding additional features that are not natively generated by the static analysis tool. An ML classifier is trained to predict a selected bug feature, and the classifier is used to update the bug dataset to include estimated values of the selected feature. In an embodiment, post-processing analysis of bug report datasets applies machine learning methods to predict the “severity” of bug reports, an indication of whether they are likely to be true or false. Further, a report of code quality can be returned based on the severity predictions.

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