29,331 research outputs found
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
Principles and Implementation of Deductive Parsing
We present a system for generating parsers based directly on the metaphor of
parsing as deduction. Parsing algorithms can be represented directly as
deduction systems, and a single deduction engine can interpret such deduction
systems so as to implement the corresponding parser. The method generalizes
easily to parsers for augmented phrase structure formalisms, such as
definite-clause grammars and other logic grammar formalisms, and has been used
for rapid prototyping of parsing algorithms for a variety of formalisms
including variants of tree-adjoining grammars, categorial grammars, and
lexicalized context-free grammars.Comment: 69 pages, includes full Prolog cod
Invariant Synthesis for Incomplete Verification Engines
We propose a framework for synthesizing inductive invariants for incomplete
verification engines, which soundly reduce logical problems in undecidable
theories to decidable theories. Our framework is based on the counter-example
guided inductive synthesis principle (CEGIS) and allows verification engines to
communicate non-provability information to guide invariant synthesis. We show
precisely how the verification engine can compute such non-provability
information and how to build effective learning algorithms when invariants are
expressed as Boolean combinations of a fixed set of predicates. Moreover, we
evaluate our framework in two verification settings, one in which verification
engines need to handle quantified formulas and one in which verification
engines have to reason about heap properties expressed in an expressive but
undecidable separation logic. Our experiments show that our invariant synthesis
framework based on non-provability information can both effectively synthesize
inductive invariants and adequately strengthen contracts across a large suite
of programs
Upside-down Deduction
Over the recent years, several proposals were made to enhance database systems with automated reasoning. In this article we analyze two such enhancements based on meta-interpretation. We consider on the one hand the theorem prover Satchmo, on the other hand the Alexander and Magic Set methods. Although they achieve different goals and are based on distinct reasoning paradigms, Satchmo and the Alexander or Magic Set methods can be similarly described by upside-down meta-interpreters, i.e., meta-interpreters implementing one reasoning principle in terms of the other. Upside-down meta-interpretation gives rise to simple and efficient implementations, but has not been investigated in the past. This article is devoted to studying this technique. We show that it permits one to inherit a search strategy from an inference engine, instead of implementing it, and to combine bottom-up and top-down reasoning. These properties yield an explanation for the efficiency of Satchmo and a justification for the unconventional approach to top-down reasoning of the Alexander and Magic Set methods
Automatic Termination Analysis of Programs Containing Arithmetic Predicates
For logic programs with arithmetic predicates, showing termination is not
easy, since the usual order for the integers is not well-founded. A new method,
easily incorporated in the TermiLog system for automatic termination analysis,
is presented for showing termination in this case.
The method consists of the following steps: First, a finite abstract domain
for representing the range of integers is deduced automatically. Based on this
abstraction, abstract interpretation is applied to the program. The result is a
finite number of atoms abstracting answers to queries which are used to extend
the technique of query-mapping pairs. For each query-mapping pair that is
potentially non-terminating, a bounded (integer-valued) termination function is
guessed. If traversing the pair decreases the value of the termination
function, then termination is established. Simple functions often suffice for
each query-mapping pair, and that gives our approach an edge over the classical
approach of using a single termination function for all loops, which must
inevitably be more complicated and harder to guess automatically. It is worth
noting that the termination of McCarthy's 91 function can be shown
automatically using our method.
In summary, the proposed approach is based on combining a finite abstraction
of the integers with the technique of the query-mapping pairs, and is
essentially capable of dividing a termination proof into several cases, such
that a simple termination function suffices for each case. Consequently, the
whole process of proving termination can be done automatically in the framework
of TermiLog and similar systems.Comment: Appeared also in Electronic Notes in Computer Science vol. 3
Specifying Logic Programs in Controlled Natural Language
Writing specifications for computer programs is not easy since one has to
take into account the disparate conceptual worlds of the application domain and
of software development. To bridge this conceptual gap we propose controlled
natural language as a declarative and application-specific specification
language. Controlled natural language is a subset of natural language that can
be accurately and efficiently processed by a computer, but is expressive enough
to allow natural usage by non-specialists. Specifications in controlled natural
language are automatically translated into Prolog clauses, hence become formal
and executable. The translation uses a definite clause grammar (DCG) enhanced
by feature structures. Inter-text references of the specification, e.g.
anaphora, are resolved with the help of discourse representation theory (DRT).
The generated Prolog clauses are added to a knowledge base. We have implemented
a prototypical specification system that successfully processes the
specification of a simple automated teller machine.Comment: 16 pages, compressed, uuencoded Postscript, published in Proceedings
CLNLP 95, COMPULOGNET/ELSNET/EAGLES Workshop on Computational Logic for
Natural Language Processing, Edinburgh, April 3-5, 199
Knowledge Representation Concepts for Automated SLA Management
Outsourcing of complex IT infrastructure to IT service providers has
increased substantially during the past years. IT service providers must be
able to fulfil their service-quality commitments based upon predefined Service
Level Agreements (SLAs) with the service customer. They need to manage, execute
and maintain thousands of SLAs for different customers and different types of
services, which needs new levels of flexibility and automation not available
with the current technology. The complexity of contractual logic in SLAs
requires new forms of knowledge representation to automatically draw inferences
and execute contractual agreements. A logic-based approach provides several
advantages including automated rule chaining allowing for compact knowledge
representation as well as flexibility to adapt to rapidly changing business
requirements. We suggest adequate logical formalisms for representation and
enforcement of SLA rules and describe a proof-of-concept implementation. The
article describes selected formalisms of the ContractLog KR and their adequacy
for automated SLA management and presents results of experiments to demonstrate
flexibility and scalability of the approach.Comment: Paschke, A. and Bichler, M.: Knowledge Representation Concepts for
Automated SLA Management, Int. Journal of Decision Support Systems (DSS),
submitted 19th March 200
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