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Geometric Data Structures

(in German: Geometric Data Structures - )

Module-ID: FIN-INF-102206
Link: LSF
Responsibility: Prof. Dr. Stefan Schirra
Lecturer: Prof. Dr. Stefan Schirra
Classes:
  • Lecture Geometric Data Structures
  • Exercises Geometric Data Structures
 
Applicability in curriculum:

Abbreviation

GeomDS

Credit Points

6

Semester

Summer

Term

ab 1.

Duration

1 Semester

Language

english

Level

Master

Intended learning outcomes:
Students learn how to design, analyze and apply data structures for geometric problems.

Content:

  • heap data structures,
  • balanced binary search trees,
  • self-organizing data structures,
  • amortized analysis,
  • interval, range and segment trees,
  • augmented data structures,
  • quad-trees,
  • fractional cascading,
  • point location data structures,
  • persistent data structures,
  • making data structures dynamic.

Workload:
56h in presence + 124h self-study

Type of examination: Teaching method / lecture hours per week (SWS):

oral exam

  • Lecture (3SWS)
  • Exercises (1SWS)
Prerequisites according to examination regulations: Recommended prerequisites:

keine

Basics in algorithmics

Media: Literature:

  • Samet: Foundations of Multidimensional and Metric Data Structures.
  • Zachmann, Langetepe: Geometric Data Structures for Computer Graphics.
  • Mehta, Sahmi: Handbook of Data Structures and Applications
  • Morin: Open Data Structures: An Introduction

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