1,741 research outputs found
Efficient Set Sharing Using ZBDDs
Set sharing is an abstract domain in which each concrete object is represented by the set of local variables from which it might be reachable. It is a useful abstraction to detect parallelism opportunities, since it contains definite information about which variables do not share in memory, i.e., about when the memory regions reachable from those variables are disjoint. Set sharing is a more precise alternative to pair sharing, in which each domain element is a set of all pairs of local variables from which a common object may be reachable. However, the exponential complexity of some set sharing operations has limited its wider application. This work introduces an efficient implementation of the set sharing domain using Zero-suppressed Binary Decision Diagrams (ZBDDs). Because ZBDDs were designed to represent sets of combinations (i.e., sets of sets), they naturally represent elements of the set sharing domain. We show how to synthesize the operations needed in the set sharing transfer functions from basic ZBDD operations. For some of the operations, we devise custom ZBDD algorithms that perform better in practice. We also compare our implementation of the abstract domain with an efficient, compact, bit set-based alternative, and show that the ZBDD version scales better in terms of both memory usage and running time
Implementing and reasoning about hash-consed data structures in Coq
We report on four different approaches to implementing hash-consing in Coq
programs. The use cases include execution inside Coq, or execution of the
extracted OCaml code. We explore the different trade-offs between faithful use
of pristine extracted code, and code that is fine-tuned to make use of OCaml
programming constructs not available in Coq. We discuss the possible
consequences in terms of performances and guarantees. We use the running
example of binary decision diagrams and then demonstrate the generality of our
solutions by applying them to other examples of hash-consed data structures
Lex-Partitioning: A New Option for BDD Search
For the exploration of large state spaces, symbolic search using binary
decision diagrams (BDDs) can save huge amounts of memory and computation time.
State sets are represented and modified by accessing and manipulating their
characteristic functions. BDD partitioning is used to compute the image as the
disjunction of smaller subimages.
In this paper, we propose a novel BDD partitioning option. The partitioning
is lexicographical in the binary representation of the states contained in the
set that is represented by a BDD and uniform with respect to the number of
states represented. The motivation of controlling the state set sizes in the
partitioning is to eventually bridge the gap between explicit and symbolic
search.
Let n be the size of the binary state vector. We propose an O(n) ranking and
unranking scheme that supports negated edges and operates on top of precomputed
satcount values. For the uniform split of a BDD, we then use unranking to
provide paths along which we partition the BDDs. In a shared BDD representation
the efforts are O(n). The algorithms are fully integrated in the CUDD library
and evaluated in strongly solving general game playing benchmarks.Comment: In Proceedings GRAPHITE 2012, arXiv:1210.611
CrocoPat 2.1 Introduction and Reference Manual
CrocoPat is an efficient, powerful and easy-to-use tool for manipulating
relations of arbitrary arity, including directed graphs. This manual provides
an introduction to and a reference for CrocoPat and its programming language
RML. It includes several application examples, in particular from the analysis
of structural models of software systems.Comment: 19 pages + cover, 2 eps figures, uses llncs.cls and
cs_techrpt_cover.sty, for downloading the source code, binaries, and RML
examples, see http://www.software-systemtechnik.de/CrocoPat
Quadtrees as an Abstract Domain
Quadtrees have proved popular in computer graphics and spatial databases as a way of representing regions in two dimensional space. This hierarchical data-structure is flexible enough to support non-convex and even disconnected regions, therefore it is natural to ask whether this datastructure can form the basis of an abstract domain. This paper explores this question and suggests that quadtrees offer a new approach to weakly relational domains whilst their hierarchical structure naturally lends itself to representation with boolean functions
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