A Fast Compiler for NetKAT

High-level programming languages play a key role in a growing number of networking platforms, streamlining application development and enabling precise formal reasoning about network behavior. Unfortunately, current compilers only handle "local" programs that specify behavior in terms of hop-by-hop forwarding behavior, or modest extensions such as simple paths. To encode richer "global" behaviors, programmers must add extra state -- something that is tricky to get right and makes programs harder to write and maintain. Making matters worse, existing compilers can take tens of minutes to generate the forwarding state for the network, even on relatively small inputs. This forces programmers to waste time working around performance issues or even revert to using hardware-level APIs. This paper presents a new compiler for the NetKAT language that handles rich features including regular paths and virtual networks, and yet is several orders of magnitude faster than previous compilers. The compiler uses symbolic automata to calculate the extra state needed to implement "global" programs, and an intermediate representation based on binary decision diagrams to dramatically improve performance. We describe the design and implementation of three essential compiler stages: from virtual programs (which specify behavior in terms of virtual topologies) to global programs (which specify network-wide behavior in terms of physical topologies), from global programs to local programs (which specify behavior in terms of single-switch behavior), and from local programs to hardware-level forwarding tables. We present results from experiments on real-world benchmarks that quantify performance in terms of compilation time and forwarding table size

Aspects of functional programming

This thesis explores the application of functional programming in new areas and its implementation using new technologies. We show how functional languages can be used to implement solutions to problems in fuzzy logic using a number of languages: Haskell, Ginger and Aladin. A compiler for the weakly-typed, lazy language Ginger is developed using Java byte-code as its target code. This is used as the inspiration for an implementation of Aladin, a simple functional language which has two novel features: its primitives are designed to be written in any language, and evaluation is controlled by declaring the strictness of all functions. Efficient denotational and operational semantics are given for this machine and an implementation is devel- oped using these semantics. We then show that by using the advantages of Aladin (simplicity and strictness control) we can employ partial evaluation to achieve con- siderable speed-ups in the running times of Aladin programs

Lazy Programs Leak Secrets

To preserve confidentiality, information-flow control (IFC) restricts how untrusted code handles secret data. While promising, IFC systems are not perfect; they can still leak sensitive information via covert channels. In this work, we describe a novel exploit of lazy evaluation to reveal secrets in IFC systems. Specifically, we show that lazy evaluation might transport information through the internal timing covert channel, a channel present in systems with concurrency and shared resources. We illustrate our claim with an attack for LIO, a concurrent IFC system for Haskell. We propose a countermeasure based on restricting the implicit sharing caused by lazy evaluation

On the performance and programming of reversible molecular computers

If the 20th century was known for the computational revolution, what will the 21st be known for? Perhaps the recent strides in the nascent fields of molecular programming and biological computation will help bring about the ‘Coming Era of Nanotechnology’ promised in Drexler’s ‘Engines of Creation’. Though there is still far to go, there is much reason for optimism. This thesis examines the underlying principles needed to realise the computational aspects of such ‘engines’ in a performant way. Its main body focusses on the ways in which thermodynamics constrains the operation and design of such systems, and it ends with the proposal of a model of computation appropriate for exploiting these constraints. These thermodynamic constraints are approached from three different directions. The first considers the maximum possible aggregate performance of a system of computers of given volume, V, with a given supply of free energy. From this perspective, reversible computing is imperative in order to circumvent the Landauer limit. A result of Frank is refined and strengthened, showing that the adiabatic regime reversible computer performance is the best possible for any computer—quantum or classical. This therefore shows a universal scaling law governing the performance of compact computers of ~V^(5/6), compared to ~V^(2/3) for conventional computers. For the case of molecular computers, it is shown how to attain this bound. The second direction extends this performance analysis to the case where individual computational particles or sub-units can interact with one another. The third extends it to interactions with shared, non-computational parts of the system. It is found that accommodating these interactions in molecular computers imposes a performance penalty that undermines the earlier scaling result. Nonetheless, scaling superior to that of irreversible computers can be preserved, and appropriate mitigations and considerations are discussed. These analyses are framed in a context of molecular computation, but where possible more general computational systems are considered. The proposed model, the א-calculus, is appropriate for programming reversible molecular computers taking into account these constraints. A variety of examples and mathematical analyses accompany it. Moreover, abstract sketches of potential molecular implementations are provided. Developing these into viable schemes suitable for experimental validation will be a focus of future work

The Best of Both Worlds:Linear Functional Programming without Compromise

We present a linear functional calculus with both the safety guarantees expressible with linear types and the rich language of combinators and composition provided by functional programming. Unlike previous combinations of linear typing and functional programming, we compromise neither the linear side (for example, our linear values are first-class citizens of the language) nor the functional side (for example, we do not require duplicate definitions of compositions for linear and unrestricted functions). To do so, we must generalize abstraction and application to encompass both linear and unrestricted functions. We capture the typing of the generalized constructs with a novel use of qualified types. Our system maintains the metatheoretic properties of the theory of qualified types, including principal types and decidable type inference. Finally, we give a formal basis for our claims of expressiveness, by showing that evaluation respects linearity, and that our language is a conservative extension of existing functional calculi.Comment: Extended versio

Composing graphical user interfaces in a purely functional language

This thesis is about building interactive graphical user interfaces in a compositional manner. Graphical user interface application hold out the promise of providing users with an interactive, graphical medium by which they can carry out tasks more effectively and conveniently. The application aids the user to solve some task. Conceptually, the user is in charge of the graphical medium, controlling the order and the rate at which individual actions are performed. This user-centred nature of graphical user interfaces has considerable ramifications for how software is structured. Since the application now services the user rather than the other way around, it has to be capable of responding to the user's actions when and in whatever order they might occur. This transfer of overall control towards the user places heavy burden on programming systems, a burden that many systems don't support too well. Why? Because the application now has to be structured so that it is responsive to whatever action the user may perform at any time. The main contribution of this thesis is to present a compositional approach to constructing graphical user interface applications in a purely functional programming language The thesis is concerned with the software techniques used to program graphical user interface applications, and not directly with their design. A starting point for the work presented here was to examine whether an approach based on functional programming could improve how graphical user interfaces are built. Functional programming languages, and Haskell in particular, contain a number of distinctive features such as higher-order functions, polymorphic type systems, lazy evaluation, and systematic overloading, that together pack quite a punch, at least according to proponents of these languages. A secondary contribution of this thesis is to present a compositional user interface framework called Haggis, which makes good use of current functional programming techniques. The thesis evaluates the properties of this framework by comparing it to existing systems

A Verified Information-Flow Architecture

SAFE is a clean-slate design for a highly secure computer system, with pervasive mechanisms for tracking and limiting information flows. At the lowest level, the SAFE hardware supports fine-grained programmable tags, with efficient and flexible propagation and combination of tags as instructions are executed. The operating system virtualizes these generic facilities to present an information-flow abstract machine that allows user programs to label sensitive data with rich confidentiality policies. We present a formal, machine-checked model of the key hardware and software mechanisms used to dynamically control information flow in SAFE and an end-to-end proof of noninterference for this model. We use a refinement proof methodology to propagate the noninterference property of the abstract machine down to the concrete machine level. We use an intermediate layer in the refinement chain that factors out the details of the information-flow control policy and devise a code generator for compiling such information-flow policies into low-level monitor code. Finally, we verify the correctness of this generator using a dedicated Hoare logic that abstracts from low-level machine instructions into a reusable set of verified structured code generators

Data-Oblivious Stream Productivity

We are concerned with demonstrating productivity of specifications of infinite streams of data, based on orthogonal rewrite rules. In general, this property is undecidable, but for restricted formats computable sufficient conditions can be obtained. The usual analysis disregards the identity of data, thus leading to approaches that we call data-oblivious. We present a method that is provably optimal among all such data-oblivious approaches. This means that in order to improve on the algorithm in this paper one has to proceed in a data-aware fashion

Bidirectional Programming and its Applications

Many problems in programming involve pairs of computations that cancel out each other’s effects; some examples include parsing/printing, embed- ding/projection, marshalling/unmarshalling, compressing/de-compressing etc. To avoid duplication of effort, the paradigm of bidirectional programming aims at to allow the programmer to write a single program that expresses both computations. Despite being a promising idea, existing studies mainly focus on the view-update problem in databases and its variants; and the impact of bidirectional programming has not reached the wider community. The goal of this thesis is to demonstrate, through concrete language designs and case studies, the relevance of bidirectional programming, in areas of computer science that have not been previously explored. In this thesis, we will argue for the importance of bidirectional programming in programming language design and compiler implementation. As evidence for this, we will propose a technique for incremental refactoring, which relies for its correctness on a bidirectional language and its properties, and devise a framework for implementing program transformations, with bidirectional properties that allow program analyses to be carried out in the transformed program, and have the results reported in the source program. Our applications of bidirectional programming to new areas bring up fresh challenges. This thesis also reflects on the challenges, and studies their impact to the design of bidirectional systems. We will review various design goals, including expressiveness, robustness, updatability, efficiency and easy of use, and show how certain choices, especially regarding updatability, can have significant influence on the effectiveness of bidirectional systems