Methods, systems, and media for dynamically detecting mobile environment information are provided. In some implementations, a method for detecting mobile environment information for advertisement requests, the method comprising: receiving a request for advertising content from an advertisement tag; applying one or more JavaScript objects to return a URL of an advertisement web view, wherein the advertisement website is generated by an advertisement software development kit to contain an advertisement responsive to the request; extracting keywords from the URL of the advertisement web view; determining whether the advertisement tag is running within a mobile application based on a comparison of the extracted keywords with known mobile application information; in response to determining that the advertisement tag is running within the mobile application, determining the advertisement software development kit from a plurality of advertisement software development kits that the advertisement tag is running in by: applying a plurality of JavaScript objects that are made available by the advertisement software development kit to return properties of the advertisement software development kit; and comparing the returned properties with a database of known software development kit information; and transmitting an indication that associates the advertisement software development kit used within a mobile application environment with the advertisement tag.

Disclosed is a solution for diagnosing problems from logs used in an application development environment. A random sample of log statements is collected. The log statements can be completely unstructured and/or do not conform to any natural language. The log statements are tagged with predefined classifications. A natural language processing (NLP) classifier model is trained utilizing the log statements tagged with the predefined classification. New log statements can be classified into the plurality of predefined classifications utilizing the trained NLP classifier model. From the log statements thus classified, statements having a problem classification can be identified and presented through a dashboard running in a browser. Outputs from the trained NLP classifier model can be provided as input to another trained model for automatically and quickly identifying a type of problem associated with the statements, eliminating a need to manually sift through tens or hundreds of thousands of lines of logs.

Disclosed is a solution for diagnosing problems from logs used in an application development environment. A random sample of log statements is collected. The log statements can be completely unstructured and/or do not conform to any natural language. The log statements are tagged with predefined classifications. A natural language processing (NLP) classifier model is trained utilizing the log statements tagged with the predefined classification. New log statements can be classified into the plurality of predefined classifications utilizing the trained NLP classifier model. From the log statements thus classified, statements having a problem classification can be identified and presented through a dashboard running in a browser. Outputs from the trained NLP classifier model can be provided as input to another trained model for automatically and quickly identifying a type of problem associated with the statements, eliminating a need to manually sift through tens or hundreds of thousands of lines of logs.

Techniques for runtime customization and management of user interfaces for enterprise applications are disclosed. In some embodiments, the techniques include tools, systems, and processes for building frontend, technology-independent user interfaces. A system may consume user input files that are language dependent and generate a metadata file that is language independent. The metadata file may be updated to customize or otherwise modify a user interface of an application at runtime. An event signal may be raised to notify the application when a new user interface is available. In response to detecting the signal, the application may refresh the user interface, including the application page being currently viewed, to modify the set of user interface components that are rendered and displayed to the end user. The system may store metadata for multiple versions of the user interface to allow users to quickly roll back to prior versions of a user interface.

The correct clusters of operating system (OS) components to package for hydration to client devices is learned through analyzing telemetry data of numerous end devices. The telemetry data captures snapshots of the OS components that were used or loaded by the end devices during runs of different applications. An OS component service mines this telemetry data and compares the frequency in which pairs of OS components are used by the end devices together during the different applications runs. Using on these frequencies, the OS components are filtered in a relationship graph and an clustering algorithm is applied to determine whether the OS components are interdependent (meaning used together) or independent (meaning not used together). Interdependent OS components are packaged together into a hydration package and may be transmitted to client computing devices requesting any of their constituent OS components.

Systems, computer program products, and methods are described herein for implementing intelligent data analysis. The present invention is configured to receive, from a computing device of a user, a first data file, wherein the first data file is associated with a base version of a data source; receive, from the computing device of the user, a second data file, wherein the second data file is associated with an updated version of the data source; initiate an intelligent data analysis engine on the first data file and the second data file; analyze the second data file to determine one or more discrepancies in relation to the first data file; determine one or more discrepancy types associated with the one or more discrepancies; retrieve, from an action datastore, one or more offset actions to rectify the one or more discrepancies; and automatically execute the one or more offset actions.

A system configuration derivation device 90 includes a storage unit 91 that stores a concretization rule in which a method is specified for concretizing abstract configuration information by confirming an unconfirmed portion of the abstract configuration information, which is information indicating configuration of a system in which the unconfirmed portion is included, and a generation unit 92 that concretizes the abstract configuration information included in configuration requirements of the system using the concretization rule stored to generate system configuration information, which is information indicating the configuration of the system in which the unconfirmed portion is not included, on the basis of the configuration requirements.

Disclosed herein are system, method, and computer program product embodiments for providing an auto-mapping recommendation between a source asset and a target asset in an integration flow design tool. Because the number of fields passed from a source asset to a target asset may be multitudinous, by auto-recommending mappings between fields provided by the source asset to the target asset, an integration flow design tool may save time developers a significant amount of time and optimize the integration flow design process.

Disclosed herein are system, method, and computer program product embodiments for providing an auto-mapping recommendation between a source asset and a target asset in an integration flow design tool. Because the number of fields passed from a source asset to a target asset may be multitudinous, by auto-recommending mappings between fields provided by the source asset to the target asset, an integration flow design tool may save time developers a significant amount of time and optimize the integration flow design process.

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.