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公开(公告)号：US20240168757A1
公开(公告)日：2024-05-23
申请号：US18551466
申请日：2022-03-10
Inventor： Alistair MCCORMICK , Adam ZIOLKOWSKI , Emmanuel FERREYRA OLIVARES , Johannes NOPPEN
Abstract: A computer implemented method to generate a software service from software code for a software component, the method including converting the code to a model representation, the model including elements corresponding to functional components in the code and relationships between elements corresponding to one or more of functional links and data relationships between the functional components; applying a clustering method to the model to define a plurality of clusters of elements of the model, each cluster of elements representing a set of functional components in the code corresponding to the elements in the cluster; monitoring the software code in execution to identify a set of functional components in the code corresponding to a cluster of elements in which the set of functional components is collectively stateless between executions of any of the functional components in the set; and generating a software service as an executable software component comprising the identified set of functional components.
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公开(公告)号：US20240177066A1
公开(公告)日：2024-05-30
申请号：US18551481
申请日：2022-03-10
Inventor： Adam ZIOLKOWSKI , Alistair MCCORMICK , Emmanuel FERREYRA OLIVARES , Johannes NOPPEN
IPC: G06N20/00
CPC classification number: G06N20/00
Abstract: A computer implemented method of deploying an artificial intelligence (AI) algorithm to model a function can include defining a verification test for verifying that the AI algorithm models the function, the fitness test being defined based on a set of input/output pairs each indicating the required output of the function for an input; defining a machine learning component having a machine learning algorithm and a configuration, the machine learning algorithm being trained based on training data to model the function; iteratively adapting the machine learning component over a plurality of generations, wherein each generation of the component is adapted by modifying the configuration of the component, and wherein the adaptation for a generation is selected from a set of candidate adaptations based on a determination of a fitness of the component so adapted, the fitness being determined by the verification test, wherein the iteration ceases in response to a stopping condition such that, on cessation, a latest generation of the machine learning component is selected to constitute the AI algorithm modelling the function.
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公开(公告)号：US20240176615A1
公开(公告)日：2024-05-30
申请号：US18551486
申请日：2022-03-10
Inventor： Adam ZIOLKOWSKI , Alistair MCCORMICK , Emmanuel FERREYRA OLIVARES , Johannes NOPPEN
IPC: G06F8/72
CPC classification number: G06F8/72
Abstract: A computer implemented method of generating a software service for providing required software functionality can include accessing a software component having functionality including and exceeding the required functionality; defining verification test for verifying that the software component includes the required functionality; applying a genetic algorithm to the software component to iteratively adapt the software component over a plurality of generations, wherein each generation of the software component is adapted by removal of one or more portions of the software component of a preceding generation, wherein the adaptation for a generation is selected from a set of candidate adaptations based on a determination of a fitness of the component so adapted, the fitness being determined by the verification test, wherein the iteration of the genetic algorithm ceases in response to a stopping condition such that, on cessation, the latest generation of the software component constitutes the software service.
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