METHOD AND SYSTEM FOR LEARNING BASED DYNAMIC SOFTWARE SYSTEM ADAPTATION

The present disclosure provides a dynamic functional adaptation of software systems based on real time need, which is unaddressed by the conventional methods. Initially, the system receives an output generated by a software system under execution corresponding to a given input. Further, a deviation in the generated output is identified based on a comparison between the generated output and a corresponding expected output. Further, an optimal policy is identified based on the generated output and the identified deviation using a reward based Reinforcement Learning (RL) model. Further, an adaptation specification is generated based on the identified optimal policy using an Adaptation Specification Generation (ASG) technique, Further, a software code is generated dynamically for the identified optimal policy using an ASG based code generation technique. Finally, the software system under execution is updated dynamically by calling a method corresponding to the generated software code and executing the software system.