Enhanced Playback of Automated Service Emulation Models Using Entropy Analysis

TL;DR

This paper introduces an entropy-based extension to the Needleman-Wunsch algorithm to improve response accuracy in automated service emulation models, facilitating more reliable service virtualization without requiring expert protocol knowledge.

Contribution

It presents a novel entropy-weighted matching method that enhances response selection in automated service models, reducing reliance on manual protocol expertise.

Findings

Entropy-weighted matching improves response accuracy

Effective across four enterprise protocols

Automates critical field detection in service responses

Abstract

Service virtualisation is a supporting tool for DevOps to generate interactive service models of dependency systems on which a system-under-test relies. These service models allow applications under development to be continuously tested against production-like conditions. Generating these virtual service models requires expert knowledge of the service protocol, which may not always be available. However, service models may be generated automatically from network traces. Previous work has used the Needleman-Wunsch algorithm to select a response from the service model to play back for a live request. We propose an extension of the Needleman-Wunsch algorithm, which uses entropy analysis to automatically detect the critical matching fields for selecting a response. Empirical tests against four enterprise protocols demonstrate that entropy weighted matching can improve response accuracy.