28,436 research outputs found
A Strategy Language for Testing Register Transfer Level Logic
The development of modern ICs requires a huge investment in RTL verification.
This is a reflection of brisk release schedules and the complexity of
contemporary chip designs. A major bottleneck to reaching verification closure
in such designs is the disproportionate effort expended in crafting directed
tests; which is necessary to reach those behaviors that other, more automated
testing methods fail to cover. This paper defines a novel language that can be
used to generate targeted stimuli for RTL logic and which mitigates the
complexities of writing directed tests. The main idea is to treat directed
testing as a meta-reasoning problem about simulation. Our language is both
formalized and prototyped as a proof-search strategy language in rewriting
logic. We illustrate its novel features and practical use with several
examples.published or submitted for publicatio
Relational Symbolic Execution
Symbolic execution is a classical program analysis technique used to show
that programs satisfy or violate given specifications. In this work we
generalize symbolic execution to support program analysis for relational
specifications in the form of relational properties - these are properties
about two runs of two programs on related inputs, or about two executions of a
single program on related inputs. Relational properties are useful to formalize
notions in security and privacy, and to reason about program optimizations. We
design a relational symbolic execution engine, named RelSym which supports
interactive refutation, as well as proving of relational properties for
programs written in a language with arrays and for-like loops
Probabilistic Programming Concepts
A multitude of different probabilistic programming languages exists today,
all extending a traditional programming language with primitives to support
modeling of complex, structured probability distributions. Each of these
languages employs its own probabilistic primitives, and comes with a particular
syntax, semantics and inference procedure. This makes it hard to understand the
underlying programming concepts and appreciate the differences between the
different languages. To obtain a better understanding of probabilistic
programming, we identify a number of core programming concepts underlying the
primitives used by various probabilistic languages, discuss the execution
mechanisms that they require and use these to position state-of-the-art
probabilistic languages and their implementation. While doing so, we focus on
probabilistic extensions of logic programming languages such as Prolog, which
have been developed since more than 20 years
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
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