| CPC G06F 11/3612 (2013.01) [G06F 11/3692 (2013.01)] | 18 Claims |
|
1. A method comprising:
obtaining a log regarding execution of a software application on a computing system;
obtaining indications of availabilities of resources related to the software application;
determining, from the log and the indications of availabilities of the resources, a workflow graph representing a workflow of software application activities, wherein the workflow graph includes a plurality of workflow states, transitions between workflow states in the plurality of workflow states, and transition probabilities associated with each of the transitions, wherein each workflow state corresponds to a node of the workflow graph, wherein each transition between workflow states corresponds to an edge of the workflow graph;
determining, from the log, the workflow graph, the transition probabilities, and the indications of availabilities of the resources, a training time series of the software application activities;
training a prediction engine comprising a long short-term memory (LSTM) machine learning model stored in a memory with the training time series of the software application activities using an LSTM trainer, wherein the LSTM trainer produces the LSTM machine learning model with a preconfigured number of cells based on the training time series of the software application activities, wherein the prediction engine as trained is configured to receive an input time series of further software application activities and generate an output time series that predicts additional software application activities;
obtaining an altered input time series of the software application activities, wherein the altered input time series of the software application activities represents an alteration to at least one of the software application activities, the workflow, the transition probabilities, or the resources; and
generating, using the prediction engine, a predicted output time series that predicts additional software application activities based on the altered input time series of the software application activities.
|