Implementing and reasoning about hash-consed data structures in Coq

We report on four different approaches to implementing hash-consing in Coq programs. The use cases include execution inside Coq, or execution of the extracted OCaml code. We explore the different trade-offs between faithful use of pristine extracted code, and code that is fine-tuned to make use of OCaml programming constructs not available in Coq. We discuss the possible consequences in terms of performances and guarantees. We use the running example of binary decision diagrams and then demonstrate the generality of our solutions by applying them to other examples of hash-consed data structures

Finding The Lazy Programmer's Bugs

Traditionally developers and testers created huge numbers of explicit tests, enumerating interesting cases, perhaps biased by what they believe to be the current boundary conditions of the function being tested. Or at least, they were supposed to. A major step forward was the development of property testing. Property testing requires the user to write a few functional properties that are used to generate tests, and requires an external library or tool to create test data for the tests. As such many thousands of tests can be created for a single property. For the purely functional programming language Haskell there are several such libraries; for example QuickCheck [CH00], SmallCheck and Lazy SmallCheck [RNL08]. Unfortunately, property testing still requires the user to write explicit tests. Fortunately, we note there are already many implicit tests present in programs. Developers may throw assertion errors, or the compiler may silently insert runtime exceptions for incomplete pattern matches. We attempt to automate the testing process using these implicit tests. Our contributions are in four main areas: (1) We have developed algorithms to automatically infer appropriate constructors and functions needed to generate test data without requiring additional programmer work or annotations. (2) To combine the constructors and functions into test expressions we take advantage of Haskell's lazy evaluation semantics by applying the techniques of needed narrowing and lazy instantiation to guide generation. (3) We keep the type of test data at its most general, in order to prevent committing too early to monomorphic types that cause needless wasted tests. (4) We have developed novel ways of creating Haskell case expressions to inspect elements inside returned data structures, in order to discover exceptions that may be hidden by laziness, and to make our test data generation algorithm more expressive. In order to validate our claims, we have implemented these techniques in Irulan, a fully automatic tool for generating systematic black-box unit tests for Haskell library code. We have designed Irulan to generate high coverage test suites and detect common programming errors in the process

An abstract machine for parallel graph reduction

technical reportAn abstract machine for parallel graph reduction on a shared memory multiprocessor is described. This is intended primarily for normal order (lazy) evaluation of functional programs. It is absolutely essential in such a design to adapt an efficient sequential model since during execution under limited resources available, performance will be reduced in the limit to that of the sequential engine. Parallel evaluation of normal order functional languages performed naively can result in poor overall performance despite the availability of sufficient processing elements and parallelism in the application. Needless context switching, task migration and continuation building may occur when a sequential thread of control would have sufficed. Furthermore, the compiler using static information cannot be fully aware of the availability of resources and their optimal utilization at any moment in run time. Indeed this may vary between runs which further aggravates the job of the compiler writer in generating optimal and compact code for programs. The benefits derived from this model are: 1) it is based on the G-machine so that execution under limited resources will default to a performance close to that of the G-machine; 2) the additional instructions needed to control the complexities of parallel evaluation are extremely simple, almost trivializing the job of the compiler writer; 3) attempts are made where possible to avoid context switching and task migration by retaining a sequential thread of control (made more clear in the paper), and 4) the method has demonstrated good overall performance on a shared memory multiprocessor

A framework for efficient model transformations

The reported productivity gains while using models and model transformations to develop entire systems, after almost a decade of experience applying model-driven approaches for system development, are already undeniable benefits of this approach. However, the slowness of higher-level, rule based model transformation languages hinders the applicability of this approach to industrial scales. Lower-level, and efficient, languages can be used but productivity and easy maintenance seize to exist. The abstraction penalty problem is not new, it also exists for high-level, object oriented languages but everyone is using them now. Why is not everyone using rule based model transformation languages then? In this thesis, we propose a framework, comprised of a language and its respective environment, designed to tackle the most performance critical operation of high-level model transformation languages: the pattern matching. This framework shows that it is possible to mitigate the performance penalty while still using high-level model transformation languages

A survey of sequential and parallel implementation techniques for functional programming languages

This paper surveys sequential and parallel implementation techniques for functional programming languages, as well as optimizations that can improve their performance. Sequential implementations have evolved from simple interpreters to sophisticated super-combinator-based compilers, while most parallel implementations have explored a broad range of techniques. We analyze the purpose and function of each implementation technique and discuss the current state-of-the-art in functional language implementation