A system and method includes receiving a first context update for an application. The method determines whether one or more of multiple rules has been satisfied in view of the first context update. The multiple rules include a multiple conditions and are associated with multiple contextual situations. The determining includes minimizing a number of the multiple conditions to be evaluated to determine whether a particular rule of the multiple rules has been satisfied. The method responsive to determining a first rule of the multiple rules has been satisfied, identifies a first contextual situation of the multiple contextual situations that is associated with the first rule. The method also determines at least one action that is associated with the first contextual situation.

A hardware environment-based data quantization method includes: parsing a model file under a current deep learning framework to obtain intermediate computational graph data and weight data that are independent of a hardware environment; performing calculation on image data in an input data set through a process indicated by an intermediate computational graph to obtain feature map data; separately performing uniform quantization on the weight data and the feature map data of each layer according to a preset linear quantization method, and calculating a weight quantization factor and a feature map quantization factor (S103); combining the weight quantization factor and the feature map quantization factor to obtain a quantization parameter that makes hardware use shift instead of division; and finally, writing the quantization parameter and the quantized weight data to a bin file according to a hardware requirement so as to generate quantized file data (S105).

A method, computer system, and a computer program product for project development in a collaborative platform is provided. The present invention may include identifying one or more features of an open source project. The present invention may include analyzing the one or more features of the open source project and assigning a sentiment to each of the one or more features. The present invention may include generating a requirement mapping for the open source project, wherein the requirement mapping is a series of the one or more features.

A method, computer system, and a computer program product for project development in a collaborative platform is provided. The present invention may include identifying one or more features of an open source project. The present invention may include analyzing the one or more features of the open source project and assigning a sentiment to each of the one or more features. The present invention may include generating a requirement mapping for the open source project, wherein the requirement mapping is a series of the one or more features.

The embodiments of the present disclosure relate to a method, apparatus and device for generating a microservice, and a storage medium. The method includes: determining a service set of a microservice according to a first user requirement; determining a deployment mode of devices controlled by the microservice; determining parameter information of the microservice according to a second user requirement; and generating the microservice according to the service set, the deployment mode and the running parameters.

Some embodiments of the teachings herein include a computer-implemented method for automatic derivation of attributes of software engineering artifacts arising from technical boundary condition of product or service development segments comprise: deducing technical requirements using an automated software-based process based on classifications of the technical boundary conditions; mapping the deduced technical requirements of the artifacts to engineering disciplines and concerns using an automated software-based process; mapping the calculated engineering artifacts to responsibilities; adapting the classification of the technical boundary conditions based on the evaluation results in iterations; and processing an executable performing a distribution calculation of the classification space, wherein the distribution calculation of the classification space is at least based on a distribution and quartiles. The process of the executable comprises: calculating combination vectors at system start; reading mapping data and calculation probabilistic distribution and quartiles; and publishing new distribution to engineering goal calculation.

Some embodiments of the teachings herein include a computer-implemented method for automatic derivation of attributes of software engineering artifacts arising from technical boundary condition of product or service development segments comprise: deducing technical requirements using an automated software-based process based on classifications of the technical boundary conditions; mapping the deduced technical requirements of the artifacts to engineering disciplines and concerns using an automated software-based process; mapping the calculated engineering artifacts to responsibilities; adapting the classification of the technical boundary conditions based on the evaluation results in iterations; and processing an executable performing a distribution calculation of the classification space, wherein the distribution calculation of the classification space is at least based on a distribution and quartiles. The process of the executable comprises: calculating combination vectors at system start; reading mapping data and calculation probabilistic distribution and quartiles; and publishing new distribution to engineering goal calculation.

Methods and systems are provided for modifying an application provided by a cloud-based computing system. The application is used by end users of an organization that is part of the cloud-based computing system. A clickstream monitoring module monitors a clickstream generated by each end user as that end user interacts with the application to generate a set of clickstream data for that particular end user. Each set of clickstream data indicates a path of interaction with features of the application by a particular end user. The sets of clickstream data can then be processed at an analytics engine to extract usage patterns that indicate how end users interact with different features of the application during usage of the application. The extracted usage patterns indicate which features the end users interact with and in what order. An artificial intelligence engine can then generate, based on the extracted usage patterns, at least one recommendation for modifying one or more features of the application to tailor the application for use by the end users in view of the extracted usage patterns.

A method, system, and computer program product for implementing automated system capacity optimization is provided. The method includes retrieving from plug-in components running on a plurality of hardware and software sources, metrics data associated with the plug-in components. The metrics data is cross-referenced with respect to operational sizing recommendations for each plug-in component based on aggregated disparate sizing guidelines and resulting software code modules are generated. Software and hardware requirements for enabling target computing components are determined based on results of executing the software code modules and operational functionality of the target computing components are enabled in accordance with the software and hardware requirements.

A method, system, and computer program product for implementing automated system capacity optimization is provided. The method includes retrieving from plug-in components running on a plurality of hardware and software sources, metrics data associated with the plug-in components. The metrics data is cross-referenced with respect to operational sizing recommendations for each plug-in component based on aggregated disparate sizing guidelines and resulting software code modules are generated. Software and hardware requirements for enabling target computing components are determined based on results of executing the software code modules and operational functionality of the target computing components are enabled in accordance with the software and hardware requirements.