G06F8/10

Systems and methods for validation of configurations and/or dependencies associated with software, software components, microservices, functions and the like

Aspects of the subject disclosure may include, for example, receiving instructions to validate a configuration associated with an application under test, the instructions identifying the application under test that exists in a first particular software environment that is selected from among a plurality of software environments; receiving dependency data, the dependency data identifying a dependency application that exists in a second particular software environment that is selected from among the plurality of software environments; performing a first process to determine whether the application under test that exists in the first particular software environment can be instantiated as a first running application, the first process resulting in a first determination; responsive to the first determination being that the application under test that exists in the first particular software environment can be instantiated as the first running application, automatically performing with no user interaction a second process to determine whether the dependency application that exists in the second particular software environment can be instantiated as a second running application, the second process resulting in a second determination; and automatically outputting with no user interaction a report indicating the first determination and the second determination. Other embodiments are disclosed.

Systems and methods for validation of configurations and/or dependencies associated with software, software components, microservices, functions and the like

Aspects of the subject disclosure may include, for example, receiving instructions to validate a configuration associated with an application under test, the instructions identifying the application under test that exists in a first particular software environment that is selected from among a plurality of software environments; receiving dependency data, the dependency data identifying a dependency application that exists in a second particular software environment that is selected from among the plurality of software environments; performing a first process to determine whether the application under test that exists in the first particular software environment can be instantiated as a first running application, the first process resulting in a first determination; responsive to the first determination being that the application under test that exists in the first particular software environment can be instantiated as the first running application, automatically performing with no user interaction a second process to determine whether the dependency application that exists in the second particular software environment can be instantiated as a second running application, the second process resulting in a second determination; and automatically outputting with no user interaction a report indicating the first determination and the second determination. Other embodiments are disclosed.

RISK EVALUATION SYSTEM AND RISK EVALUATION METHOD

A risk evaluation system includes a processor unit and a storage unit. In the risk evaluation system, the storage unit stores: demand information indicating a demand for software to be developed in a software development project that is a risk evaluation target; past demand information indicating a demand for software developed in a past software development project; and a source code change history in the past software development project, and the processor unit is configured to: calculate a similarity between the demand information and the past demand information; extract a change history of a source code corresponding to the past demand information based on the past demand information and the source code change history; and evaluate a risk in software development for realizing the demand information based on the similarity and the change history of the source code corresponding to the past demand information.

DOCUMENT CREATION SUPPORT APPARATUS, DOCUMENT CREATION SUPPORT METHOD AND DOCUMENT CREATION SUPPORT PROGRAM

A document creation assistance apparatus includes a tree structure generation unit configured to analyze a learning document for system development and generate a tree structure representing separate sections of the learning document, a frequency calculation unit configured to calculate, per leaf node of the tree structure, a frequency vector of a word that appears, a question extraction unit configured to extract, according to the frequency vector, a word about which a user is to be questioned, a question presentation unit configured to present a question about the extracted word to the user and receive an answer, and a document generation unit configured to generate a document with the extracted word and the answer set in a section of the separate sections of the leaf node according to the separate sections of the tree structure.

Platforms for developing data models with machine learning model

A platform for developing data models includes a repository for kernel images, a data store of data sets and a development environment. The kernel images include a data model and configurable development code for developing the data model. The development of the data model is configurable according to development parameters for the development code. The kernel images specify the development parameters in a standardized syntax for the platform and specify the input data using standardized data types for the platform, preferably via a standardized API. The development environment is used to run sessions to develop the data models. Each session runs one of the kernel images, according to a configuration of the development parameters for the kernel image, and using one of the data sets in the data store as input data.

Platforms for developing data models with machine learning model

A platform for developing data models includes a repository for kernel images, a data store of data sets and a development environment. The kernel images include a data model and configurable development code for developing the data model. The development of the data model is configurable according to development parameters for the development code. The kernel images specify the development parameters in a standardized syntax for the platform and specify the input data using standardized data types for the platform, preferably via a standardized API. The development environment is used to run sessions to develop the data models. Each session runs one of the kernel images, according to a configuration of the development parameters for the kernel image, and using one of the data sets in the data store as input data.

COMPILED SHADER PROGRAM CACHES IN A CLOUD COMPUTING ENVIRONMENT

Apparatuses, systems, and techniques for a compiled shader program caches in a cloud computing environment.

COMPILED SHADER PROGRAM CACHES IN A CLOUD COMPUTING ENVIRONMENT

Apparatuses, systems, and techniques for a compiled shader program caches in a cloud computing environment.

Dynamically creating source code comments

An approach for dynamically generating comments associated with software source code. The identifies a user accessing the software source code. The approach retrieves data associated with the software source code, e.g., server logs, requirements documents, etc. The approach identifies skills associated with the user. The approach, using artificial intelligence (AI), predicts the reason the user is accessing the software source code. The approach identifies navigation patterns based on the user access. The approach, using AI, dynamically generates comments for the user. The approach overlays the comments on the software sour code under review and displays the combination to the user.

Dynamically creating source code comments

An approach for dynamically generating comments associated with software source code. The identifies a user accessing the software source code. The approach retrieves data associated with the software source code, e.g., server logs, requirements documents, etc. The approach identifies skills associated with the user. The approach, using artificial intelligence (AI), predicts the reason the user is accessing the software source code. The approach identifies navigation patterns based on the user access. The approach, using AI, dynamically generates comments for the user. The approach overlays the comments on the software sour code under review and displays the combination to the user.