G06F8/75

Machine-learning models to assess coding skills and video performance

A method includes receiving uncompilable code from a candidate. The method further includes extracting features from the uncompilable code. The method further includes outputting, with a coding machine-learning model, compilable code based on the uncompilable code and the extracted features. The method further includes generating a coding score based on the uncompilable code and the compilable code. The method further includes receiving first media of one or more answers to questions provided by the candidate during an interview. The method further includes outputting, with a media machine-learning model, one or more corresponding ratings for the one or more answers. The method further includes generating a media score based on the one or more corresponding ratings. The method further includes generating a total score based on the coding score and the media score.

CROSS-PLATFORM PROGRAM ANALYSIS USING MACHINES LEARNING BASED ON UNIVERSAL FEATURES
20180012142 · 2018-01-11 ·

A method for performing program analysis includes receiving programs of a first platform that have been assigned a first label and programs of the first platform that have been assigned a second label. Each of the programs of the first platform is expressed as platform-independent logical features. A discriminatory model or classifier is trained, using machine learning, based on the expression of the programs of the first platform as platform-independent logical features, to distinguish between programs of the first label and programs of the second label. An unlabeled program of a second platform is received and is expressed as platform-independent logical features. The trained discriminatory model or classifier is used to determine if the unlabeled program warrants the first label or the second label, based on the expression of the unlabeled program as platform-independent logical features.

Dynamic CFI using line-of-code behavior and relation models
11709981 · 2023-07-25 · ·

Disclosed herein are techniques for analyzing control-flow integrity based on functional line-of-code behavior and relation models. Techniques include receiving data based on runtime operations of a controller; constructing a line-of-code behavior and relation model representing execution of functions on the controller based on the received data; constructing, based on the line-of-code behavioral and relation model, a dynamic control flow integrity model configured for the controller to enforce in real-time; and deploying the dynamic control flow integrity model to the controller.

Dynamic CFI using line-of-code behavior and relation models
11709981 · 2023-07-25 · ·

Disclosed herein are techniques for analyzing control-flow integrity based on functional line-of-code behavior and relation models. Techniques include receiving data based on runtime operations of a controller; constructing a line-of-code behavior and relation model representing execution of functions on the controller based on the received data; constructing, based on the line-of-code behavioral and relation model, a dynamic control flow integrity model configured for the controller to enforce in real-time; and deploying the dynamic control flow integrity model to the controller.

Compliance assessment and simulation system
11709658 · 2023-07-25 · ·

Systems and methods include reception of a first request to check code associated with a first service for compliance with one or more criteria, determination of a plurality of code components associated with the first service, execution of a code check of each of the plurality of code components, generation of a first service compliance statement associated with the first service based on results of the executed code checks, determination of a definition of the first product from a product repository, the definition listing a plurality of services on which the product depends, the plurality of services including the first service, identification of a compliance statement associated with each of the plurality services, and determination of a product compliance statement based on each of the identified compliance statements.

Compliance assessment and simulation system
11709658 · 2023-07-25 · ·

Systems and methods include reception of a first request to check code associated with a first service for compliance with one or more criteria, determination of a plurality of code components associated with the first service, execution of a code check of each of the plurality of code components, generation of a first service compliance statement associated with the first service based on results of the executed code checks, determination of a definition of the first product from a product repository, the definition listing a plurality of services on which the product depends, the plurality of services including the first service, identification of a compliance statement associated with each of the plurality services, and determination of a product compliance statement based on each of the identified compliance statements.

DETECTING DUPLICATED CODE PATTERNS IN VISUAL PROGRAMMING LANGUAGE CODE INSTANCES

A repository of graph based visual programming language code instances is analyzed. A similar code portion pattern duplicated is detected among a group of graph based visual programming language code instances included in the repository of graph based visual programming language code instances including by using an index and tokenizing one or more graph nodes connected by one or more graph edges included in a flow corresponding to at least one graph based visual programming language code instance in the group of graph based visual programming language code instances. Within a visual representation of at least one of the group of graph based visual programming language code instances, elements belonging to the detected similar code portion pattern are visually indicated.

DETECTING DUPLICATED CODE PATTERNS IN VISUAL PROGRAMMING LANGUAGE CODE INSTANCES

A repository of graph based visual programming language code instances is analyzed. A similar code portion pattern duplicated is detected among a group of graph based visual programming language code instances included in the repository of graph based visual programming language code instances including by using an index and tokenizing one or more graph nodes connected by one or more graph edges included in a flow corresponding to at least one graph based visual programming language code instance in the group of graph based visual programming language code instances. Within a visual representation of at least one of the group of graph based visual programming language code instances, elements belonging to the detected similar code portion pattern are visually indicated.

MONOLITHIC COMPUTER APPLICATION REFACTORING

Refactoring a monolithic computer application can include transforming textual input into context-aware tokens represented by machine-processable data structures, the textual input acquired from text associated with a computer application having a monolithic architecture for implementing one or more application processes. Based on co-occurrence frequencies among the context aware tokens, one or more groupings of context-aware tokens can be determined. An association between each grouping and a code construct can be determined. Invocation sequences based on time series analyses of computer-generated usage data generated in response to execution of the one or more application processes can be generated, each invocation sequence linking two or more code constructs based on a time series analysis linking groupings that correspond to the linked code constructs. A recommendation for refactoring the computer application into a plurality of microservices can be generated, each microservice corresponding to one or more invocation sequences.

MONOLITHIC COMPUTER APPLICATION REFACTORING

Refactoring a monolithic computer application can include transforming textual input into context-aware tokens represented by machine-processable data structures, the textual input acquired from text associated with a computer application having a monolithic architecture for implementing one or more application processes. Based on co-occurrence frequencies among the context aware tokens, one or more groupings of context-aware tokens can be determined. An association between each grouping and a code construct can be determined. Invocation sequences based on time series analyses of computer-generated usage data generated in response to execution of the one or more application processes can be generated, each invocation sequence linking two or more code constructs based on a time series analysis linking groupings that correspond to the linked code constructs. A recommendation for refactoring the computer application into a plurality of microservices can be generated, each microservice corresponding to one or more invocation sequences.