Keywords and Synonyms
Experimental algorithmics; Empirical algorithmics; Empirical analysis of algorithms; Algorithm engineering
Problem Definition
Experimental analysis of algorithms describes not a specific algorithmic problem, but rather an approach to algorithm design and analysis. It complements, and forms a bridge between, traditional theoretical analysis, and the application‐driven methodology used in empirical analysis.
The traditional theoretical approach to algorithm analysis defines algorithm efficiency in terms of counts of dominant operations, under some abstract model of computation such as a RAM; the input model is typically either worst-case or average-case. Theoretical results are usually expressed in terms of asymptotic bounds on the function relating input size to number of dominant operations performed.
This contrasts with the tradition of empirical analysis that has developed primarily in fields such as operations research, scientific computing, and artificial...
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Recommended Reading
ACM Journal of Experimental Algorithmics. Launched in 1996, this journal publishes contributed articles as well as special sections containing selected papers from ALENEX and WEA. Visit www.jea.acm.org, or visit portal.acm.org and click on ACM Digital Library/Journals/Journal of Experimental Algorithmics
ALENEX. Beginning in 1999, the annual workshop on Algorithm Engineering and Experimentation is sponsored by SIAM and ACM. It is co-located with SODA, the SIAM Symposium on Data Structures and Algorithms. Workshop proceedings are published in the Springer LNCS series. Visit www.siam.org/meetings/ for more information
Barr, R.S., Golden, B.L., Kelly, J.P., Resende, M.G.C., Stewart, W.R.: Designing and reporting on computational experiments with heuristic methods. J. Heuristic 1(1), 9–32 (1995)
Cohen, P.R.: Empirical Methods for Artificial Intelligence. MIT Press, Cambridge (1995)
DIMACS Implementation Challenges. Each DIMACS Implementation Challenge is a year-long cooperative research event in which researchers cooperate to find the most efficient algorithms and strategies for selected algorithmic problems. The DIMACS Challenges since 1991 have targeted a variety of optimization problems on graphs; advanced data structures; and scientific application areas involving computational biology and parallel computation. The DIMACS Challenge proceedings are published by AMS as part of the DIMACS Series in Discrete Mathematics and Theoretical Computer Science. Visit dimacs.rutgers.edu/Challenges for more information
Johnson, D.S.: A theoretician's guide to the experimental analysis of algorithms. In: Goodrich, M.H., Johnson, D.S., McGeoch, C.C. (eds.) Data Structures, Near Neighbors Searches, and Methodology: Fifth and Sixth DIMACS Implementation Challenges, DIMACS Series in Discrete Mathematics and Theoretical Computer Science, vol. 59. American Mathematical Society, Providence (2002)
McGeoch, C.C.: Toward an experimental method for algorithm simulation. INFORMS J. Comp. 1(1), 1–15 (1996)
WEA. Beginning in 2001, the annual Workshop on Experimental and Efficient Algorithms is sponsored by EATCS. Workshop proceedings are published in the Springer LNCS series
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McGeoch, C. (2008). Experimental Methods for Algorithm Analysis. In: Kao, MY. (eds) Encyclopedia of Algorithms. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-30162-4_135
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DOI: https://doi.org/10.1007/978-0-387-30162-4_135
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