7,997 research outputs found
Logic Programming Applications: What Are the Abstractions and Implementations?
This article presents an overview of applications of logic programming,
classifying them based on the abstractions and implementations of logic
languages that support the applications. The three key abstractions are join,
recursion, and constraint. Their essential implementations are for-loops, fixed
points, and backtracking, respectively. The corresponding kinds of applications
are database queries, inductive analysis, and combinatorial search,
respectively. We also discuss language extensions and programming paradigms,
summarize example application problems by application areas, and touch on
example systems that support variants of the abstractions with different
implementations
Heap Abstractions for Static Analysis
Heap data is potentially unbounded and seemingly arbitrary. As a consequence,
unlike stack and static memory, heap memory cannot be abstracted directly in
terms of a fixed set of source variable names appearing in the program being
analysed. This makes it an interesting topic of study and there is an abundance
of literature employing heap abstractions. Although most studies have addressed
similar concerns, their formulations and formalisms often seem dissimilar and
some times even unrelated. Thus, the insights gained in one description of heap
abstraction may not directly carry over to some other description. This survey
is a result of our quest for a unifying theme in the existing descriptions of
heap abstractions. In particular, our interest lies in the abstractions and not
in the algorithms that construct them.
In our search of a unified theme, we view a heap abstraction as consisting of
two features: a heap model to represent the heap memory and a summarization
technique for bounding the heap representation. We classify the models as
storeless, store based, and hybrid. We describe various summarization
techniques based on k-limiting, allocation sites, patterns, variables, other
generic instrumentation predicates, and higher-order logics. This approach
allows us to compare the insights of a large number of seemingly dissimilar
heap abstractions and also paves way for creating new abstractions by
mix-and-match of models and summarization techniques.Comment: 49 pages, 20 figure
Applying Formal Methods to Networking: Theory, Techniques and Applications
Despite its great importance, modern network infrastructure is remarkable for
the lack of rigor in its engineering. The Internet which began as a research
experiment was never designed to handle the users and applications it hosts
today. The lack of formalization of the Internet architecture meant limited
abstractions and modularity, especially for the control and management planes,
thus requiring for every new need a new protocol built from scratch. This led
to an unwieldy ossified Internet architecture resistant to any attempts at
formal verification, and an Internet culture where expediency and pragmatism
are favored over formal correctness. Fortunately, recent work in the space of
clean slate Internet design---especially, the software defined networking (SDN)
paradigm---offers the Internet community another chance to develop the right
kind of architecture and abstractions. This has also led to a great resurgence
in interest of applying formal methods to specification, verification, and
synthesis of networking protocols and applications. In this paper, we present a
self-contained tutorial of the formidable amount of work that has been done in
formal methods, and present a survey of its applications to networking.Comment: 30 pages, submitted to IEEE Communications Surveys and Tutorial
Synthesizing Functional Reactive Programs
Functional Reactive Programming (FRP) is a paradigm that has simplified the
construction of reactive programs. There are many libraries that implement
incarnations of FRP, using abstractions such as Applicative, Monads, and
Arrows. However, finding a good control flow, that correctly manages state and
switches behaviors at the right times, still poses a major challenge to
developers. An attractive alternative is specifying the behavior instead of
programming it, as made possible by the recently developed logic: Temporal
Stream Logic (TSL). However, it has not been explored so far how Control Flow
Models (CFMs), as synthesized from TSL specifications, can be turned into
executable code that is compatible with libraries building on FRP. We bridge
this gap, by showing that CFMs are indeed a suitable formalism to be turned
into Applicative, Monadic, and Arrowized FRP. We demonstrate the effectiveness
of our translations on a real-world kitchen timer application, which we
translate to a desktop application using the Arrowized FRP library Yampa, a web
application using the Monadic threepenny-gui library, and to hardware using the
Applicative hardware description language ClaSH.Comment: arXiv admin note: text overlap with arXiv:1712.0024
Relating Nominal and Higher-order Abstract Syntax Specifications
Nominal abstract syntax and higher-order abstract syntax provide a means for
describing binding structure which is higher-level than traditional techniques.
These approaches have spawned two different communities which have developed
along similar lines but with subtle differences that make them difficult to
relate. The nominal abstract syntax community has devices like names,
freshness, name-abstractions with variable capture, and the new-quantifier,
whereas the higher-order abstract syntax community has devices like
lambda-binders, lambda-conversion, raising, and the nabla-quantifier. This
paper aims to unify these communities and provide a concrete correspondence
between their different devices. In particular, we develop a
semantics-preserving translation from alpha-Prolog, a nominal abstract syntax
based logic programming language, to G-, a higher-order abstract syntax based
logic programming language. We also discuss higher-order judgments, a common
and powerful tool for specifications with higher-order abstract syntax, and we
show how these can be incorporated into G-. This establishes G- as a language
with the power of higher-order abstract syntax, the fine-grained variable
control of nominal specifications, and the desirable properties of higher-order
judgments.Comment: To appear in PPDP 201
Collection analysis for Horn clause programs
We consider approximating data structures with collections of the items that
they contain. For examples, lists, binary trees, tuples, etc, can be
approximated by sets or multisets of the items within them. Such approximations
can be used to provide partial correctness properties of logic programs. For
example, one might wish to specify than whenever the atom is proved
then the two lists and contain the same multiset of items (that is,
is a permutation of ). If sorting removes duplicates, then one would like to
infer that the sets of items underlying and are the same. Such results
could be useful to have if they can be determined statically and automatically.
We present a scheme by which such collection analysis can be structured and
automated. Central to this scheme is the use of linear logic as a omputational
logic underlying the logic of Horn clauses
Probabilistic Program Abstractions
Abstraction is a fundamental tool for reasoning about complex systems.
Program abstraction has been utilized to great effect for analyzing
deterministic programs. At the heart of program abstraction is the relationship
between a concrete program, which is difficult to analyze, and an abstract
program, which is more tractable. Program abstractions, however, are typically
not probabilistic. We generalize non-deterministic program abstractions to
probabilistic program abstractions by explicitly quantifying the
non-deterministic choices. Our framework upgrades key definitions and
properties of abstractions to the probabilistic context. We also discuss
preliminary ideas for performing inference on probabilistic abstractions and
general probabilistic programs
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