Upper and Lower Bounds for Weak Backdoor Set Detection

D 2013

Upper and Lower Bounds for Weak Backdoor Set Detection

NEELDHARA, Misra, Sebastian ORDYNIAK, Venkatesh RAMAN and Stefan SZEIDER

Basic information

Original name

Upper and Lower Bounds for Weak Backdoor Set Detection

Authors

NEELDHARA, Misra (356 India), Sebastian ORDYNIAK (276 Germany, guarantor, belonging to the institution), Venkatesh RAMAN (356 India) and Stefan SZEIDER (40 Austria)

Edition

Helsinki, Lecture Notes in Computer Science, p. 394-402, 9 pp. 2013

Publisher

Springer

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10000 1. Natural Sciences

Country of publisher

Germany

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

printed version "print"

Impact factor

Impact factor: 0.402 in 2005

RIV identification code

RIV/00216224:14330/13:00072818

Organization unit

Faculty of Informatics

ISBN

978-3-642-39070-8

ISSN

DOI

http://dx.doi.org/10.1007/978-3-642-39071-5_29

Keywords in English

satisfiability; weak backdoor sets;parameterized complexity; upper bounds; lower bounds

Abstract

V originále

We obtain upper and lower bounds for running times of exponential time algorithms for the detection of weak backdoor sets of 3CNF formulas, considering various base classes. These results include (omitting polynomial factors), (i)~a 4.54^k algorithm to detect whether there is a weak backdoor set of at most k variables into the class of Horn formulas; (ii)~a 2.27^k algorithm to detect whether there is a weak backdoor set of at most k variables into the class of Krom formulas. These bounds improve an earlier known bound of 6^k. We also prove a 2^k lower bound for these problems, subject to the Strong Exponential Time Hypothesis.

Links

EE2.3.30.0009, research and development project

Name: Zaměstnáním čerstvých absolventů doktorského studia k vědecké excelenci

Citovat

NEELDHARA, Misra, Sebastian ORDYNIAK, Venkatesh RAMAN and Stefan SZEIDER. Upper and Lower Bounds for Weak Backdoor Set Detection. In Matti J{\"a}rvisalo and Allen Van Gelder. Lecture Notes in Computer Science. Helsinki: Springer, 2013, p. 394-402. ISBN 978-3-642-39070-8. Available from: https://dx.doi.org/10.1007/978-3-642-39071-5_29.

@inproceedings{1173833,
   author = {Neeldhara, Misra and Ordyniak, Sebastian and Raman, Venkatesh and Szeider, Stefan},
   address = {Helsinki},
   booktitle = {Lecture Notes in Computer Science},
   doi = {http://dx.doi.org/10.1007/978-3-642-39071-5_29},
   editor = {Matti J{\"a}rvisalo and Allen Van Gelder},
   keywords = {satisfiability; weak backdoor sets;parameterized complexity; upper bounds; lower bounds},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {Helsinki},
   isbn = {978-3-642-39070-8},
   pages = {394-402},
   publisher = {Springer},
   title = {Upper and Lower Bounds for Weak Backdoor Set Detection},
   year = {2013}
}

TY  - JOUR
ID  - 1173833
AU  - Neeldhara, Misra - Ordyniak, Sebastian - Raman, Venkatesh - Szeider, Stefan
PY  - 2013
TI  - Upper and Lower Bounds for Weak Backdoor Set Detection
PB  - Springer
CY  - Helsinki
SN  - 9783642390708
KW  - satisfiability
KW  - weak backdoor sets;parameterized complexity
KW  - upper bounds
KW  - lower bounds
N2  - We obtain upper and lower bounds for running times of exponential time algorithms for the detection of weak backdoor sets of 3CNF formulas, considering various base classes. These results include (omitting polynomial factors), (i)~a 4.54^k algorithm to detect whether there is a weak backdoor set of at most k variables into the class of Horn formulas; (ii)~a 2.27^k algorithm to detect whether there is a weak backdoor set of at most k variables into the class of Krom formulas. These bounds improve an earlier known bound of 6^k. We also prove a 2^k lower bound for these problems, subject to the Strong Exponential Time Hypothesis.
ER  -

NEELDHARA, Misra, Sebastian ORDYNIAK, Venkatesh RAMAN and Stefan SZEIDER. Upper and Lower Bounds for Weak Backdoor Set Detection. In Matti J$\{\backslash$''a$\}$rvisalo and Allen Van Gelder. \textit{Lecture Notes in Computer Science}. Helsinki: Springer, 2013, p.~394-402. ISBN~978-3-642-39070-8. Available from: https://dx.doi.org/10.1007/978-3-642-39071-5\_{}29.

Detailed Information on Publication Record