A genetic algorithm system generates a set of computer programs and executes a process for assessment and conditional modification of the set, repeating the process over a plurality of generations to mutate the population of solutions over time. At each generation, the system scores each program in the set to generate a respective primary score adjustment, a respective secondary score adjustment, and a respective current score. If a current score for a program is less than or equal to a first threshold, the system removes the computer program from the set. If the current score is greater than or equal to a second threshold, the system modifies the computer program to generate one or more offspring programs for use in subsequent generations. If a primary score adjustment for a program is greater than or equal to a third threshold, the system selects the computer program for performance of a task.

A genetic algorithm system generates a set of computer programs and executes a process for assessment and conditional modification of the set, repeating the process over a plurality of generations to mutate the population of solutions over time. At each generation, the system scores each program in the set to generate a respective primary score adjustment, a respective secondary score adjustment, and a respective current score. If a current score for a program is less than or equal to a first threshold, the system removes the computer program from the set. If the current score is greater than or equal to a second threshold, the system modifies the computer program to generate one or more offspring programs for use in subsequent generations. If a primary score adjustment for a program is greater than or equal to a third threshold, the system selects the computer program for performance of a task.

A method and a system for agitation detection and response for a programming language are provided. The method includes collecting software code and activity data pertaining to one or more activities performed by a developer that is using a segment of a programming language. The method also includes evaluating the activity data to generate an agitation level of the developer when using the segment of the programming language. The method can also include generating a developer context by evaluating the software code. The developer context can include insights into the operation of features in the programming language by the developer. The activity and developer context can be provided to a software development provider for independent analysis.

Methods, system and apparatus for the augmentation of an integrated development environment (IDE). The system and methods provide for the integration of all aspects of a development workflow to be initiated and completed from within the IDE. Every phase of development, including, grabbing a ticket, working on the ticket, asking teammates questions, requesting feedback, initiating code reviews, performing code reviews, creating feature branches, creating pull requests, creating merge requests and generating audit trails of all interactions users have with the IDE are managed and performed from within the IDE, eliminating the need to context switch or open additional application or websites.

Methods, system and apparatus for the augmentation of an integrated development environment (IDE). The system and methods provide for the integration of all aspects of a development workflow to be initiated and completed from within the IDE. Every phase of development, including, grabbing a ticket, working on the ticket, asking teammates questions, requesting feedback, initiating code reviews, performing code reviews, creating feature branches, creating pull requests, creating merge requests and generating audit trails of all interactions users have with the IDE are managed and performed from within the IDE, eliminating the need to context switch or open additional application or websites.

A computer system for analyzing source code is disclosed. The computer system includes a processor and electronic memory storage. The electronic memory storage includes source code and executable instructions. The processor runs the executable instructions to: access the source code from the electronic memory storage; analyze code elements of the accessed source code to extract node data, edge data, and bindings data; and store the node data, edge data, and bindings data, in a graph database structure in the electronic memory storage.

A computer system for analyzing source code is disclosed. The computer system includes a processor and electronic memory storage. The electronic memory storage includes source code and executable instructions. The processor runs the executable instructions to: access the source code from the electronic memory storage; analyze code elements of the accessed source code to extract node data, edge data, and bindings data; and store the node data, edge data, and bindings data, in a graph database structure in the electronic memory storage.

Code search is used to support various features. Code segments may be indexed using a code structure representation of the code segment. Code segments may be compared for similarity to identify a match with an input code segment using a comparison of logic trees generated for the input code segment and a stored code segment in an entry with a matching index value.

According to some embodiments, systems and methods are provided, comprising receiving a code fragment exhibiting a static code issue; determining, via a trained exemption neural network, whether the received code fragment is exempt or not exempt from resolution; in a case it is not exempt, inputting the code fragment to a trained classification neural network; determining whether the static code issue is a syntactical static code issue or a non-syntactical static code issue; in a case it is a syntactical static code issue, inputting the code fragment to a first trained network to generate a first resolution; and in a case the static code issue is a non-syntactical static code issue, inputting the code fragment to a second trained network to generate a second resolution of the non-syntactical static code issue. Numerous other aspects are provided.

According to some embodiments, systems and methods are provided, comprising receiving a code fragment exhibiting a static code issue; determining, via a trained exemption neural network, whether the received code fragment is exempt or not exempt from resolution; in a case it is not exempt, inputting the code fragment to a trained classification neural network; determining whether the static code issue is a syntactical static code issue or a non-syntactical static code issue; in a case it is a syntactical static code issue, inputting the code fragment to a first trained network to generate a first resolution; and in a case the static code issue is a non-syntactical static code issue, inputting the code fragment to a second trained network to generate a second resolution of the non-syntactical static code issue. Numerous other aspects are provided.