Abstract: Disclosed herein are techniques for identifying software dependencies based on functional line-of-code behavior and relation models. Techniques include accessing a first line-of-code behavior and relation model representing execution of functions of a first portion of executable code, the first portion of executable code being associated with a first symbol; detecting a change to the first portion of executable code; constructing, based on the changed first portion of executable code, a second line-of-code behavior and relation model representing execution of functions of the changed first portion of executable code; determining, based on the constructed second model, a dependency between (i) the changed first portion of executable code or the first symbol and (ii) a second symbol; and generating, based on the determined difference, a report identifying the dependency.

Abstract: Systems and methods are provided for coordinating the deployment of frontend assets to defined user groups. Individual groups of users may be assigned to a track comprising a set of frontend assets. Each set of frontend assets may comprise each of the individual components required to generate an entire frontend for an application. In some embodiments, different versions of a single component may be assigned within different tracks. As such, one set of users may be provided a first version of an application and a second set of users may be provided a second version of that application. By associating a new or updated version of a component to a given track, a new or updated version of a component not yet ready for widespread deployment may be provided to only a limited number of users.

Abstract: Techniques involve determining a job template for executing a development job in the development environment and obtaining configuration information associated with the development job. The configuration information defines a development environment user preference for a configuration parameter. A development job instance is generated based on the job template and the configuration parameter. The development job instance is executed on code from the user to build an image for executing an application program. Rather than write code, developers may generate a development job instance including the desired configuration parameter by modifying the configuration information. Such techniques improve working efficiency of developers and maintain a common development template for use by developers. Such a technique may improve operation by imposing consistent storage application control.

Abstract: A computer system for automated model integration of an information model with a corresponding application includes: an information model server for exposing an information model to a consumer, the exposed information model including model-elements for exposing types or classes, and for exposing instances of types or classes and their member-values; an application component for providing application code augmented with mapping descriptions defining how an internal information model of the application is mapped to the exposed information model; and a model integration component that: registers internal information model-elements to be exposed; maps the registered internal information model-elements to exposed information model-elements in accordance with the mapping descriptions; and updates an information model-element by: detecting a change of an internal or exposed information model-element; determining a synchronization direction; and performing match-making to determine a model-element corresponding to th

Abstract: A software project management system can store object data about components of a software development project, such epics, features, and stories. The software project management system can also store dependency objects that reflect dependency relationships between two or more components of the software development project. The dependency objects can track status information about the dependency relationships, including expected completion dates, acceptance criteria, and state indicators. The information stored in the dependency objects can be updated over time as information about the dependency relationship changes. The software project management system can also use the dependency objects to display information in a user interface about one or more dependency relationships, such as to indicate which dependency relationships are on track or behind schedule.

Abstract: Systems and methods for formal verification of programs. The systems and methods provide a new game-theoretical, strategy-based compositional semantic model for concurrency, a set of formal linking theorems for composing multithreaded and multicore concurrent layers, and a compiler that supports certified thread-safe compilation and linking. Verification of an overlay interface can include determining an intermediate strategy for a primitive operation running on an underlay interface and refining that intermediate strategy to a strategy running on the overlay interface by applying a vertical and a horizontal composition rule. The refined strategy can then be composed with compatible strategies running on the overlay interface according to a parallel composition rule. Strategies may be compatible when rely conditions imposed by each strategy satisfy guarantees provided by the other strategies. The system and method of formal verification can be applied to formal verification of smart contracts.

Abstract: In one embodiment, the present disclosure pertains to automated data type determination of variables that are written in a programming language. In one embodiment, a programming language statement is received. The programming language statement includes a variable, an expression to which the variable is set, and a request to determine a data type of the variable. The expression is processed to deduce a data type of the expression. In certain embodiments, the data type of the expression is then assigned as the data type of the variable such that the data type can be used when the programming language statement is compiled into machine executable code.

Abstract: A code completion tool uses a deep learning model to predict the likelihood of a method completing a method invocation. In one aspect, the deep learning model is a LSTM trained on features that represent the syntactic context of a method invocation derived from an abstract tree representation of the code fragment.

Abstract: Systems and methods for compiling functions into a single entity are disclosed. An execution graph representing dependencies between a plurality of functions is analyzed to identify portions of the graph that include two or more of the plurality of functions used as a combined entity and have a single entry point. The plurality of functions corresponds to a decomposed application. The processing device compiles the functions of each of the identified one or more portions of the graph into a composition. For each portion of the graph that includes two or more of the plurality of functions used as a combined entity and has multiple entry points, the processing device determines whether to compile each function providing a subsequent entry point to the portion into a composition with other functions of the portion based at least in part on a network latency and a scale efficiency of the application.

Abstract: In various embodiments, an organization may be required to comply with one or more legal or industry requirements related to the storage of personal data (e.g., which may, for example, include personally identifiable information) even when responding to and fulfilling Data Subject Access Requests. In particular, when responding to a DSAR, the system may compile one or more pieces of personal data for provision to a data subject. The system may store this compilation of personal data at least temporarily in order to provide access to the data to the data subject. As such, the system may be configured to implement one or more data retention rules in order to ensure compliance with any legal or industry requirements related to the temporary storage of the collected data while still fulfilling any requirements related to providing the data to data subjects that request it, deleting the data upon request, etc.

Abstract: The ability to comprehend the context of a given programming artifact and extracting the underlying functionality is a complex task extending beyond just syntactic and semantic analysis of code. All existing automation capabilities, hence heavily depend on manual involvement of domain experts. Even recent approaches leveraging Machine Learning Capabilities are supervised techniques, whereby the dependency on domain experts still remains—in preparing suitable training sets. A method and system for automated classification of variables using unsupervised distribution agnostic clustering has been provided. The present disclosure focuses to tap the flexibility of the code and presents a domain agnostic approach using unsupervised machine learning which automatically extracts the context from source code, by classifying the underlying elements of the code. The method and system do not require any manual intervention and opens a wide range of opportunities in reverse engineering and variable level analysis space.

Abstract: The management of applications in a computing environment often involves a significant number of computing operations, such as acquiring the application, deploying data objects in various locations, and configuring the application with respect to the deployed device. Conventional computing environments may provide inadequate support throughout a typical application life cycle, especially for a computing environment distributed across many devices. Instead, the computing environment may be represented in a deployable object hierarchy that may be distributed to various devices. An application management service may therefore be provided to install representations of the application in the object hierarchy, and to support many other aspects of the application life cycle, such as application discovery, sharing, updating, and removal.

Abstract: A method is provided for sparse communication in a parallel machine learning environment. The method includes determining a fixed communication cost for a sparse graph to be computed. The sparse graph is (i) determined from a communication graph that includes all the machines in a target cluster of the environment, and (ii) represents a communication network for the target cluster having (a) an overall spectral gap greater than or equal to a minimum threshold, and (b) certain information dispersal properties such that an intermediate output from a given node disperses to all other nodes of the sparse graph in lowest number of time steps given other possible node connections. The method further includes computing the sparse graph, based on the communication graph and the fixed communication cost. The method also includes initiating a propagation of the intermediate output in the parallel machine learning environment using a topology of the sparse graph.

Abstract: A system comprises at least one hardware processor and a memory storing instructions. When executed, the instructions cause the at least one hardware processor to perform operations comprising receiving, in a compiling process, a request to create a Java user-defined table function (Java UDTF), the Java UDTF including code related to receiving one or more input tables and transforming the one or more input tables to an output table; verifying a construct of the Java UDTF in the request is correct; and compiling to generate execution code that includes the Java UDTF when the construct of the Java UDTF is correct.

Abstract: Systems and methods for automated software engineering are disclosed. A particular embodiment is configured to: establish a data connection with a software code repository; provide a collection of autonomous computer programs or bots configured to automatically perform a specific software development life cycle (SDLC) task; use a first bot of the collection of bots to perform an automatic code review of a software module from the software code repository; use a second bot of the collection of bots to perform automatic unit testing of the software module from the software code repository; and use a third bot of the collection of bots to perform an automatic deployment of the software module from the software code repository. A health engine module can monitor the execution of the other software modules and capture execution metrics. Any of the bots in the bot collection can be machine learning models trained using training data.

Abstract: A shared debugging service stores information captured during software debug sessions for future use. The information can include developer identities so that future developers can contact past developers for assistance. The information can also include information such as developer steps, user settings, path-to-current code specifics, and stored breakpoint values. A developer can request a record of previous software debug sessions for a given piece of software and can acquire, store, or display previously collected information to assist in a current software debug session.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for conversion and restoration of computer environments to container-based implementations. In some implementations, an archive of configuration data for a server system is obtained, where the server system includes at least one application. A set of multiple software images is generated, where the multiple software images are generated such that they divide the functionality of at least one application among the respective containers. In generating the set of multiple software images, settings of the at least one application are identified based on the configuration data in the archive, a subset of the settings is selected for each of the software images, and the selected subsets of settings are converted into converted subsets of settings for the respective software images.

Abstract: A software model specification for a software package can be associated with representation of a software downgrade definition. The software model specification can include a publisher of the software package, an application title of the software package, and the version of the software package. One or more entitlements for the software package can be obtained. Based on the software downgrade definition being associated with the software model specification, the software downgrade definition can be associated with the entitlement(s). Compliance of the installations of the software package with the entitlement(s) can be calculated, where the software downgrade definition can cause each of the entitlement(s) to be applicable to the installations of the version of the software package or one or more earlier versions of the software package.

Abstract: A computerized system and method for generating an application structure for an application in a computerized organization having a plurality of components. An implementation includes generating the application structure for the application by including, in the application structure, applicative components and connections between applicative components identified using a first entry point. In an implementation, the identification of the applicative components and the connections between applicative components includes applying a first set of patterns against a first component associated with the first entry point to identify a first applicative component of the applicative components and a first connection of the connections, the first connection including a second entry point. The applicative components and the connections between applicative components can be recursively identified.

Abstract: A method and system of evaluating a user experience (UX) design are provided. A UX design is received. All objects that are identified to be part of a background of the input UI screen are removed to create a filtered input UI screen. The input UI screen is assigned to a cluster. A target UI screen of the input screen is determined and its background removed, to create a filtered target UI cluster. The target UI screen is assigned to a cluster. The filtered input UI screen is used as an input to a deep learning model to predict a target UI cluster. The predicted target UI cluster is compared to the filtered target UI cluster based on the clustering. Upon determining that the filtered target UI cluster is similar to the target UI screen, the UX design is classified as being successful.