310 research outputs found
Foundations of Declarative Data Analysis Using Limit Datalog Programs
Motivated by applications in declarative data analysis, we study
---an extension of positive Datalog with
arithmetic functions over integers. This language is known to be undecidable,
so we propose two fragments. In
predicates are axiomatised to keep minimal/maximal numeric values, allowing us
to show that fact entailment is coNExpTime-complete in combined, and
coNP-complete in data complexity. Moreover, an additional
requirement causes the complexity to drop to ExpTime and PTime, respectively.
Finally, we show that stable can express many
useful data analysis tasks, and so our results provide a sound foundation for
the development of advanced information systems.Comment: 23 pages; full version of a paper accepted at IJCAI-17; v2 fixes some
typos and improves the acknowledgment
Proceedings of JAC 2010. Journées Automates Cellulaires
The second Symposium on Cellular Automata “Journ´ees Automates Cellulaires” (JAC 2010) took place in Turku, Finland, on December 15-17, 2010. The first two conference days were held in the Educarium building of the University of Turku, while the talks of the third day were given onboard passenger ferry boats in the beautiful Turku archipelago, along the route Turku–Mariehamn–Turku. The conference was organized by FUNDIM, the Fundamentals of Computing and Discrete Mathematics research center at the mathematics department of the University of Turku.
The program of the conference included 17 submitted papers that were selected by the international program committee, based on three peer reviews of each paper. These papers form the core of these proceedings. I want to thank the members of the program committee and the external referees for the excellent work that have done in choosing the papers to be presented in the conference. In addition to the submitted papers, the program of JAC 2010 included four distinguished invited speakers: Michel Coornaert (Universit´e de Strasbourg, France), Bruno Durand (Universit´e de Provence, Marseille, France), Dora Giammarresi (Universit` a di Roma Tor Vergata, Italy) and Martin Kutrib (Universit¨at Gie_en, Germany). I sincerely thank the invited speakers for accepting our invitation to come and give a plenary talk in the conference. The invited talk by Bruno Durand was eventually given by his co-author Alexander Shen, and I thank him for accepting to make the presentation with a short notice. Abstracts or extended abstracts of the invited presentations appear in the first part of this volume.
The program also included several informal presentations describing very recent developments and ongoing research projects. I wish to thank all the speakers for their contribution to the success of the symposium. I also would like to thank the sponsors and our collaborators: the Finnish Academy of Science and Letters, the French National Research Agency project EMC (ANR-09-BLAN-0164), Turku Centre for Computer Science, the University of Turku, and Centro Hotel. Finally, I sincerely thank the members of the local organizing committee for making the conference possible.
These proceedings are published both in an electronic format and in print. The electronic proceedings are available on the electronic repository HAL, managed by several French research agencies. The printed version is published in the general publications series of TUCS, Turku Centre for Computer Science. We thank both HAL and TUCS for accepting to publish the proceedings.Siirretty Doriast
Games on graphs with a public signal monitoring
We study pure Nash equilibria in games on graphs with an imperfect monitoring
based on a public signal. In such games, deviations and players responsible for
those deviations can be hard to detect and track. We propose a generic
epistemic game abstraction, which conveniently allows to represent the
knowledge of the players about these deviations, and give a characterization of
Nash equilibria in terms of winning strategies in the abstraction. We then use
the abstraction to develop algorithms for some payoff functions.Comment: 28 page
Sequential Relational Decomposition
The concept of decomposition in computer science and engineering is
considered a fundamental component of computational thinking and is prevalent
in design of algorithms, software construction, hardware design, and more. We
propose a simple and natural formalization of sequential decomposition, in
which a task is decomposed into two sequential sub-tasks, with the first
sub-task to be executed before the second sub-task is executed. These tasks are
specified by means of input/output relations. We define and study decomposition
problems, which is to decide whether a given specification can be sequentially
decomposed. Our main result is that decomposition itself is a difficult
computational problem. More specifically, we study decomposition problems in
three settings: where the input task is specified explicitly, by means of
Boolean circuits, and by means of automatic relations. We show that in the
first setting decomposition is NP-complete, in the second setting it is
NEXPTIME-complete, and in the third setting there is evidence to suggest that
it is undecidable. Our results indicate that the intuitive idea of
decomposition as a system-design approach requires further investigation. In
particular, we show that adding a human to the loop by asking for a
decomposition hint lowers the complexity of decomposition problems
considerably
Recommended from our members
Periodically specified satisfiability problems with applications: An alternative to domino problems
We characterize the complexities of several basic generalized CNF satisfiability problems SAT(S), when instances are specified using various kinds of 1- and 2-dimensional periodic specifications. We outline how this characterization can be used to prove a number of new hardness results for the complexity classes DSPACE(n), NSPACE(n), DEXPTIME, NEXPTIME, EXPSPACE etc. The hardness results presented significantly extend the known hardness results for periodically specified problems. Several advantages axe outlined of the use of periodically specified satisfiability problems over the use of domino problems in proving both hardness and easiness results. As one corollary, we show that a number of basic NP-hard problems become EXPSPACE hard when inputs axe represented using 1-dimensional infinite periodic wide specifications. This answers a long standing open question posed by Orlin
Parameterized Algorithms for Scalable Interprocedural Data-flow Analysis
Data-flow analysis is a general technique used to compute information of
interest at different points of a program and is considered to be a cornerstone
of static analysis. In this thesis, we consider interprocedural data-flow
analysis as formalized by the standard IFDS framework, which can express many
widely-used static analyses such as reaching definitions, live variables, and
null-pointer. We focus on the well-studied on-demand setting in which queries
arrive one-by-one in a stream and each query should be answered as fast as
possible. While the classical IFDS algorithm provides a polynomial-time
solution to this problem, it is not scalable in practice. Specifically, it
either requires a quadratic-time preprocessing phase or takes linear time per
query, both of which are untenable for modern huge codebases with hundreds of
thousands of lines. Previous works have already shown that parameterizing the
problem by the treewidth of the program's control-flow graph is promising and
can lead to significant gains in efficiency. Unfortunately, these results were
only applicable to the limited special case of same-context queries.
In this work, we obtain significant speedups for the general case of
on-demand IFDS with queries that are not necessarily same-context. This is
achieved by exploiting a new graph sparsity parameter, namely the treedepth of
the program's call graph. Our approach is the first to exploit the sparsity of
control-flow graphs and call graphs at the same time and parameterize by both
treewidth and treedepth. We obtain an algorithm with a linear preprocessing
phase that can answer each query in constant time with respect to the input
size. Finally, we show experimental results demonstrating that our approach
significantly outperforms the classical IFDS and its on-demand variant
- …