A NICE way to test openflow applications

TLDR

OpenFlow‑capable switches enable powerful network functions but also expose the system to programming errors; although a centralized controller reduces bug likelihood, the inherently distributed, asynchronous nature and scalability challenges of diverse packets and event orderings increase the risk of unreliable communication. The study proposes efficient, systematic methods for testing unmodified OpenFlow controller programs, combining model checking with symbolic execution of event handlers to identify representative packets. The NICE tool uses model checking of the full controller‑switch‑host system, a simplified switch model, and symbolic execution to generate event interleavings, and is implemented as a prototype that tests Python applications on the NOX platform. Testing three real OpenFlow applications—MAC‑learning switch, in‑network load balancing, and energy‑efficient traffic engineering—revealed eleven bugs.

Abstract

The emergence of OpenFlow-capable switches enables exciting new network functionality, at the risk of programming errors that make communication less reliable. The centralized programming model, where a single controller program manages the network, seems to reduce the likelihood of bugs. However, the system is inherently distributed and asynchronous, with events happening at different switches and end hosts, and inevitable delays affecting communication with the controller. In this paper, we present efficient, systematic techniques for testing unmodified controller programs. Our NICE tool applies model checking to explore the state space of the entire system--the controller, the switches, and the hosts. Scalability is the main challenge, given the diversity of data packets, the large system state, and the many possible event orderings. To address this, we propose a novel way to augment model checking with symbolic execution of event handlers (to identify representative packets that exercise code paths on the controller). We also present a simplified OpenFlow switch model (to reduce the state space), and effective strategies for generating event interleavings likely to uncover bugs. Our prototype tests Python applications on the popular NOX platform. In testing three real applications--a MAC-learning switch, in-network server load balancing, and energy-efficient traffic engineering--we uncover eleven bugs.