Algorithm engineering and experimental algorithmics

This course offers a broad perspective on issues and challenges that software engineers face when working with algorithms. We delve into the field of algorithm engineering which focuses on bridging the gap between theory and practice in the development and implementation of efficient algorithms. Adhering to a pragmatic approach, our examination prioritizes practicality while building on theoretical results, placing an emphasis on issues such as problem modeling, algorithm design and optimization, implementation, and tuning based on experimentation.

Topics presented within the course:
    • An overview of the theory of algorithms and motivation for a more pragmatic approach such as algorithm engineering.
    • The process of algorithm engineering and its phases: modeling, design, analysis, implementation, experimentation.
    • Case study: Engineering Quicksort and array partitioning algorithms
    • Experimental algorithmics: designing experiments, benchmarks and time measurement, preparation of test inputs, analysis and visualization of test results, etc.
    • Selected topics from algorithmics such as exact exponential algorithms, beyond worst-case analysis, certifying algorithms, etc.
Student evaluation is based on a small problem set of exercises plus a presentation of a selected topic.