Graph based event-driven computing

Abstract

A method for modeling and execution of event-driven software applications. Its main parts are the routing graph model, the run time engine and optionally a user interface and automatic configuration modules. The routing graph is comprised of routing and data-processing nodes. Routing nodes are enriched with node-type specific event routing logic. Data-processing nodes process specific types of events and produce output events. The run time engine executes the routing graph model, based on the routing nodes logic and the data-processing nodes processing functions. The user interface component is used to compose and manage the routing graph configuration. The automatic configuration modules combine and configure predefined routing sub-graphs into a resulting routing graph model.

Description

RELATED APPLICATIONS[0001]This application claims the benefit of priority of Israel Patent Application No. 279776 filed on Dec. 24, 2020, which claims the benefit of priority of U.S. patent application Ser. No. 16 / 950,928 filed on Nov. 18, 2020.[0002]This application is also a Continuation-in-Part (CIP) of U.S. patent application Ser. No. 16 / 950,928 filed on Nov. 18, 2020.[0003]The contents of the above applications are all incorporated by reference as if fully set forth herein in their entirety.FIELD AND BACKGROUND OF THE INVENTION[0004]Some embodiments described in the present disclosure relate to a computerized system for executing a software program and, specifically, but not exclusively, to an integrated development environment.[0005]As used herewithin, each of the terms “software program” and “computer program” is used to mean a collection of data and computer instructions instructing one or more hardware processors how to operate in order to perform one or more identified tas...

AI Technical Summary

Benefits of technology

This approach enhances clarity and ease of development, reducing costs and increasing accuracy and availability of software applications by modeling data flows as sequences of steps separate from specific data processing steps.

Problems solved by technology

Software programs are increasingly becoming more complex than before, and there exist software programs comprising hundreds, thousands, and hundreds of thousands of separate computation tasks.

The mere size of a software program makes it difficult for a software developer to understand how the software program operates, and consequently makes maintenance and further development of the software program more difficult and thus more expensive.

In addition, common code organization practices increase the difficulty of understanding and maintaining software programs.

The result is that a data-flow, which in general can be perceived as a sequence of processing steps that are needed to perform a specific task, is hard to discern from the code.

Applications that adhere to an event-driven architecture may be even harder to follow as the order of execution may depend on runtime order of processed events.

Not all man-made systems share such complexity related problems.

Current large scale software systems do not have a comparable organizing principle that helps in understanding and navigating their processes and code bases.

This results in high learning curves and lowers productivity of software teams responsible for developing and maintaining those systems.

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