Logo of Humboldt-Universität zu BerlinLogo of Humboldt-Universität zu Berlin
edoc-Server
Open-Access-Publikationsserver der Humboldt-Universität
de|en
Header image: facade of Humboldt-Universität zu Berlin
View Item 
  • edoc-Server Home
  • Artikel und Monographien
  • Zweitveröffentlichungen
  • View Item
  • edoc-Server Home
  • Artikel und Monographien
  • Zweitveröffentlichungen
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.
All of edoc-ServerCommunity & CollectionTitleAuthorSubjectThis CollectionTitleAuthorSubject
PublishLoginRegisterHelp
StatisticsView Usage Statistics
All of edoc-ServerCommunity & CollectionTitleAuthorSubjectThis CollectionTitleAuthorSubject
PublishLoginRegisterHelp
StatisticsView Usage Statistics
View Item 
  • edoc-Server Home
  • Artikel und Monographien
  • Zweitveröffentlichungen
  • View Item
  • edoc-Server Home
  • Artikel und Monographien
  • Zweitveröffentlichungen
  • View Item
2019-06-26Zeitschriftenartikel DOI: 10.3390/a12070127
Guidelines for Experimental Algorithmics: A Case Study in Network Analysis
Angriman, Eugenio
van der Grinten, Alexander cc
von Looz, Moritz
Meyerhenke, Henning cc
Nöllenburg, Martin cc
Predari, Maria cc
Tzovas, Charilaos
Mathematisch-Naturwissenschaftliche Fakultät
The field of network science is a highly interdisciplinary area; for the empirical analysis of network data, it draws algorithmic methodologies from several research fields. Hence, research procedures and descriptions of the technical results often differ, sometimes widely. In this paper we focus on methodologies for the experimental part of algorithm engineering for network analysis—an important ingredient for a research area with empirical focus. More precisely, we unify and adapt existing recommendations from different fields and propose universal guidelines—including statistical analyses—for the systematic evaluation of network analysis algorithms. This way, the behavior of newly proposed algorithms can be properly assessed and comparisons to existing solutions become meaningful. Moreover, as the main technical contribution, we provide SimexPal, a highly automated tool to perform and analyze experiments following our guidelines. To illustrate the merits of SimexPal and our guidelines, we apply them in a case study: we design, perform, visualize and evaluate experiments of a recent algorithm for approximating betweenness centrality, an important problem in network analysis. In summary, both our guidelines and SimexPal shall modernize and complement previous efforts in experimental algorithmics; they are not only useful for network analysis, but also in related contexts.
Files in this item
Thumbnail
algorithms-12-00127-v3.pdf — Adobe PDF — 657.0 Kb
MD5: 5d026d744f7ba21870af26e75969344d
Cite
BibTeX
EndNote
RIS
(CC BY 4.0) Attribution 4.0 International(CC BY 4.0) Attribution 4.0 International
Details
DINI-Zertifikat 2019OpenAIRE validatedORCID Consortium
Imprint Policy Contact Data Privacy Statement
A service of University Library and Computer and Media Service
© Humboldt-Universität zu Berlin
 
DOI
10.3390/a12070127
Permanent URL
https://doi.org/10.3390/a12070127
HTML
<a href="https://doi.org/10.3390/a12070127">https://doi.org/10.3390/a12070127</a>