115,127 research outputs found
Experiments with a Convex Polyhedral Analysis Tool for Logic Programs
Convex polyhedral abstractions of logic programs have been found very useful
in deriving numeric relationships between program arguments in order to prove
program properties and in other areas such as termination and complexity
analysis. We present a tool for constructing polyhedral analyses of
(constraint) logic programs. The aim of the tool is to make available, with a
convenient interface, state-of-the-art techniques for polyhedral analysis such
as delayed widening, narrowing, "widening up-to", and enhanced automatic
selection of widening points. The tool is accessible on the web, permits user
programs to be uploaded and analysed, and is integrated with related program
transformations such as size abstractions and query-answer transformation. We
then report some experiments using the tool, showing how it can be conveniently
used to analyse transition systems arising from models of embedded systems, and
an emulator for a PIC microcontroller which is used for example in wearable
computing systems. We discuss issues including scalability, tradeoffs of
precision and computation time, and other program transformations that can
enhance the results of analysis.Comment: Paper presented at the 17th Workshop on Logic-based Methods in
Programming Environments (WLPE2007
PURRS: Towards Computer Algebra Support for Fully Automatic Worst-Case Complexity Analysis
Fully automatic worst-case complexity analysis has a number of applications
in computer-assisted program manipulation. A classical and powerful approach to
complexity analysis consists in formally deriving, from the program syntax, a
set of constraints expressing bounds on the resources required by the program,
which are then solved, possibly applying safe approximations. In several
interesting cases, these constraints take the form of recurrence relations.
While techniques for solving recurrences are known and implemented in several
computer algebra systems, these do not completely fulfill the needs of fully
automatic complexity analysis: they only deal with a somewhat restricted class
of recurrence relations, or sometimes require user intervention, or they are
restricted to the computation of exact solutions that are often so complex to
be unmanageable, and thus useless in practice. In this paper we briefly
describe PURRS, a system and software library aimed at providing all the
computer algebra services needed by applications performing or exploiting the
results of worst-case complexity analyses. The capabilities of the system are
illustrated by means of examples derived from the analysis of programs written
in a domain-specific functional programming language for real-time embedded
systems.Comment: 6 page
Sciduction: Combining Induction, Deduction, and Structure for Verification and Synthesis
Even with impressive advances in automated formal methods, certain problems
in system verification and synthesis remain challenging. Examples include the
verification of quantitative properties of software involving constraints on
timing and energy consumption, and the automatic synthesis of systems from
specifications. The major challenges include environment modeling,
incompleteness in specifications, and the complexity of underlying decision
problems.
This position paper proposes sciduction, an approach to tackle these
challenges by integrating inductive inference, deductive reasoning, and
structure hypotheses. Deductive reasoning, which leads from general rules or
concepts to conclusions about specific problem instances, includes techniques
such as logical inference and constraint solving. Inductive inference, which
generalizes from specific instances to yield a concept, includes algorithmic
learning from examples. Structure hypotheses are used to define the class of
artifacts, such as invariants or program fragments, generated during
verification or synthesis. Sciduction constrains inductive and deductive
reasoning using structure hypotheses, and actively combines inductive and
deductive reasoning: for instance, deductive techniques generate examples for
learning, and inductive reasoning is used to guide the deductive engines.
We illustrate this approach with three applications: (i) timing analysis of
software; (ii) synthesis of loop-free programs, and (iii) controller synthesis
for hybrid systems. Some future applications are also discussed
Towards an Abstract Domain for Resource Analysis of Logic Programs Using Sized Types
We present a novel general resource analysis for logic programs based on
sized types.Sized types are representations that incorporate structural (shape)
information and allow expressing both lower and upper bounds on the size of a
set of terms and their subterms at any position and depth. They also allow
relating the sizes of terms and subterms occurring at different argument
positions in logic predicates. Using these sized types, the resource analysis
can infer both lower and upper bounds on the resources used by all the
procedures in a program as functions on input term (and subterm) sizes,
overcoming limitations of existing analyses and enhancing their precision. Our
new resource analysis has been developed within the abstract interpretation
framework, as an extension of the sized types abstract domain, and has been
integrated into the Ciao preprocessor, CiaoPP. The abstract domain operations
are integrated with the setting up and solving of recurrence equations for
both, inferring size and resource usage functions. We show that the analysis is
an improvement over the previous resource analysis present in CiaoPP and
compares well in power to state of the art systems.Comment: Part of WLPE 2013 proceedings (arXiv:1308.2055
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