8,765 research outputs found
TOY: A System for Experimenting with Cooperation of Constraint Domains
AbstractThis paper presents, from a user point-of-view, the mechanism of cooperation between constraint domains that is currently part of the system TOY, an implementation of a constraint functional logic programming scheme. This implementation follows a cooperative goal solving calculus based on lazy narrowing. It manages the invocation of solvers for each domain, and projection operations for converting constraints into mate domains via mediatorial constraints. We implemented the cooperation among Herbrand, real arithmetic (R), finite domain (FD) and set (S) domains. We provide two mediatorial constraints: The first one relates the numeric domains FD and R, and the second one relates FD and S
An Integrated Development Environment for Declarative Multi-Paradigm Programming
In this paper we present CIDER (Curry Integrated Development EnviRonment), an
analysis and programming environment for the declarative multi-paradigm
language Curry. CIDER is a graphical environment to support the development of
Curry programs by providing integrated tools for the analysis and visualization
of programs. CIDER is completely implemented in Curry using libraries for GUI
programming (based on Tcl/Tk) and meta-programming. An important aspect of our
environment is the possible adaptation of the development environment to other
declarative source languages (e.g., Prolog or Haskell) and the extensibility
w.r.t. new analysis methods. To support the latter feature, the lazy evaluation
strategy of the underlying implementation language Curry becomes quite useful.Comment: In A. Kusalik (ed), proceedings of the Eleventh International
Workshop on Logic Programming Environments (WLPE'01), December 1, 2001,
Paphos, Cyprus. cs.PL/011104
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
Independent AND-parallel implementation of narrowing
We present a parallel graph narrowing machine, which is
used to implement a functional logic language on a shared memory multiprocessor. It is an extensión of an abstract machine for a purely functional language. The result is a programmed graph reduction machine which integrates the mechanisms of unification, backtracking, and independent
and-parallelism. In the machine, the subexpressions of an expression can run in parallel. In the case of backtracking, the structure of an expression is used to avoid the reevaluation of subexpressions as far as possible. Deterministic computations are detected. Their results are maintained and need not be reevaluated after backtracking
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