Computer networks are hard to manage. Given a set of highlevel requirements (e.g., reachability, security), operators have to manually figure out the individual configuration of potentially hundreds of devices running complex distributed protocols so that they, collectively, compute a compatible forwarding state. Not surprisingly, operators often make mistakes which lead to downtimes. To address this problem, we present a novel synthesis approach that automatically computes correct network configurations that comply with the operator's requirements. We capture the behavior of existing routers along with the distributed protocols they run in stratified Datalog. Our key insight is to reduce the problem of finding correct input configurations to the task of synthesizing inputs for a stratified Datalog program. To solve this synthesis task, we introduce a new algorithm that synthesizes inputs for stratified Datalog programs. This algorithm is applicable beyond the domain of networks. We leverage our synthesis algorithm to construct the first network-wide configuration synthesis system, called SyNET, that support multiple interacting routing protocols (OSPF and BGP) and static routes. We show that our system is practical and can infer correct input configurations, in a reasonable amount time, for networks of realistic size (> 50 routers) that forward packets for multiple traffic classes.

Software bugs are inevitable in software-defined networking control software, and troubleshooting is a tedious, time-consuming task. In this thesis we discuss how to improve control software troubleshooting by presenting a technique for automatically identifying a minimal sequence of inputs responsible for triggering a given bug, without making assumptions about the language or instrumentation of the software under test. We apply our technique to five open source SDN control platforms-Floodlight, NOX, POX, Pyretic, ONOS-and illustrate how the minimal causal sequences our system found aided the troubleshooting process. AcknowledgmentsMany thanks to the STS team for making this thesis possible:

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Software bugs are inevitable in software-defined networking control software, and troubleshooting is a tedious, time-consuming task. In this thesis we discuss how to improve control software troubleshooting by presenting a technique for automatically identifying a minimal sequence of inputs responsible for triggering a given bug, without making assumptions about the language or instrumentation of the software under test. We apply our technique to five open source SDN control platforms-Floodlight, NOX, POX, Pyretic, ONOS-and illustrate how the minimal causal sequences our system found aided the troubleshooting process. AcknowledgmentsMany thanks to the STS team for making this thesis possible:

A holistic view of the network is key to the successful operation of many distributed, cloud-based, and service-oriented computing architectures. Supporting networkaware applications and application-driven networks requires a detailed representation of network resources, including multilayer topologies, associated measurement data, and in-thenetwork service location and availability information. The rapid development of increasingly configurable and dynamic networks has increased the demand for information services that can accurately and efficiently store and expose the state of the network. This work introduces our Unified Network Information Service (UNIS), designed to represent physical and virtual networks and services. We describe the UNIS network data model and its RESTful interface, which provide a common interface to topology, service, and measurement resources. In addition, we describe the security mechanisms built into the UNIS framework. Our analysis of the UNIS implementation shows significant performance and scalability gains over an existing and widely-deployed topology, service registration, and lookup information service architecture.