# Who is interested in algorithms and why?: lessons from the Stony Brook algorithms repository

@inproceedings{Skiena1999WhoII, title={Who is interested in algorithms and why?: lessons from the Stony Brook algorithms repository}, author={Steven Skiena}, booktitle={SIGA}, year={1999} }

We present "market research" for the field of combinatorial algorithms and algorithm engineering, attempting to determine which algorithmic problems are most in demand in applications. We analyze 1,503,135 WWW hits recorded on the Stony Brook Algorithms Repository (http://www.cs.sunysb.edu/~algorith), to determine the relative level of interest among 75 algorithmic problems and the extent to which publicly available algorithm implementations satisfy this demand.

## 42 Citations

What Do We Learn from Experimental Algorithmics?

- Computer ScienceMFCS
- 2000

This paper surveys some relevant contributions to the field of Experimental Algorithmics and discusses significant examples where the experimental approach helped in developing new ideas, in assessing heuristics and techniques, and in gaining a deeper insight about existing algorithms.

Algorithm Engineering: 3rd International Workshop, WAE’99 London, UK, July 19–21, 1999 Proceedings

- Computer ScienceLecture Notes in Computer Science
- 1999

Experiments with List Ranking for Explicit Multi-Threaded Instruction Parallelism and Evaluation of an Algorithm for the Transversal Hypergraph Problem.

A λ goVista — A Tool for Classifying Algorithmic Problems and Combinatorial Structures

- Computer Science

AλgoVista is a web-based search engine that assists programmers to classify algorithmic problems and combinatorial structures and requires users to provide input⇒output samples that give a rough description of the behavior of their needed algorithm.

The Algorithm Design Manual

- Computer ScienceTexts in Computer Science
- 2020

This newly expanded and updated second edition of the best-selling classic continues to take the "mystery" out of designing algorithms, and analyzing their efficacy and efficiency.

A theory repository on the Web: a proposal

- Computer ScienceSIGA
- 1999

An integrated set of sites, the Theory Web, is described, that in a manner similar to a site like Yahoo! or Excite! collects and classifies links to theoretical compute science.

Greedy algorithms for the minimization knapsack problem: Average behavior

- Computer Science
- 2008

A formal description of primal and dual greedy methods is given for a minimization version of the knapsack problem with Boolean variables and it is shown that for μ < t/3 primal andDual greedy methods have an asymptotical accuracy t.

An Approach for Automatic Construction of an Algorithmic Knowledge Graph from Textual Resources

- Computer ScienceArXiv
- 2022

An approach for automatically developing a knowledge graph (KG) for algorithmic problems from unstructured data because it captures information more clearly and extensively, an algorithm KG will give additional context and explainability to the algorithm metadata.

Average behavior of greedy algorithms for the minimization knapsack problem: General coefficient distributions

- Computer Science
- 2008

For the minimization knapsack problem with Boolean variables, primal and dual greedy algorithms are formally described. Their relations to the corresponding algorithms for the maximization knapsack…

Realistic Computer Models

- Computer ScienceAlgorithm Engineering
- 2010

This chapter focuses on realistic computation models that capture the running time of algorithms involving large data sets on modern computers better than the traditional RAM (and its parallel counterpart PRAM) model.

Algorithm engineering

- Computer ScienceCSUR
- 1999

Algorithm Engineering is concerned with the design, analysis, implementation, tuning, debugging and experimental evaluation of computer programs for solving algorithmic problems. It provides…

## References

SHOWING 1-8 OF 8 REFERENCES

Algorithms in C

- Computer Science
- 1990

Algorithms in C is a comprehensive repository of algorithms, complete with code, with extensive treatment of searching and advanced data structures, sorting, string processing, computational geometry, graph problems, and mathematical algorithms.

How to find the best approximation results – a follow-up to Garey and Johnson ∗

- Mathematics
- 1998

A compendium of NP optimization problems, containing the best approximation results known for each problem, is available on the world wide web at http://www.nada.kth.se/ ̃viggo/problemlist/ In this…

The algorithm design manual

- Computer Science
- 1980

This newly expanded and updated second edition of the best-selling classic continues to take the "mystery" out of designing algorithms, and analyzing their efficacy and efficiency.

LEDA: a platform for combinatorial and geometric computing

- Computer ScienceCACM
- 1995

There is no standard library of the data structures and algorithms of combinatorial and geometric computing, and there are, for example, packages in statistics (SPSS), numerical analysis (LINPACK), symbolic computation (MAPLE, MATHEMATICA), and linear programming (CPLEX).

Ranger: a tool for nearest neighbor search in high dimensions

- Computer ScienceSCG '93
- 1993

Ranger is a tool for visualizing and experimenting with nearest neighbor and orthogonal range queries in highdimensional data sets, using multidimensional search trees.

Implementing Discrete Mathematics

- Addison-Wesley, Redwood City, CA
- 1990

Who is Interested in Algorithms and Why?

- Who is Interested in Algorithms and Why?