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ArticlePublished 7 Aug 20261 min readBy Kevin Jogindecision guidealgorithm selectionsummarypractical guidance
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Software, Tables and Sources

Choosing an Algorithm: Decision Guide

A consolidated decision guide across the main computational tasks in this collection.

Engineering / MathematicsSoftware, Tables and Sources2 min readKV-MATH-0679

This page consolidates the selection guidance distributed across the collection. Each branch links to the page treating that choice in full.

Integer arithmetic

Integer arithmetic selection
TaskChoice
MultiplicationSchoolbook at small sizes; Karatsuba above the measured crossover
Repeated modular arithmetic with a fixed modulusMontgomery reduction
GCDBinary GCD at small sizes; Lehmer above
Many inversions at onceSimultaneous inversion

Linear algebra and lattices

Linear algebra selection
TaskChoice
Integer matrix normal formHermite with a modular bound; LLL-based when growth is severe
Group structure from relationsSmith normal form
Short lattice vectorsLLL; enumeration when exactness is required
Large sparse system over a small fieldStructured elimination then an iterative method — see the linear algebra stage

Polynomials

  • Factoring a polynomial
  • Over a small finite fieldBerlekamp
  • Over a large finite fieldThe GCD pipeline
  • Over the integersZassenhaus with an LLL fallback
  • Over a number fieldNorm reduction

Number fields

Number field task selection
TaskChoice
Maximal orderRound 2, after polynomial reduction
Prime decomposition, p not dividing the indexSimple decomposition
Prime decomposition, index divisorBuchmann-Lenstra or Newton polygons
Class group, quadratic, small discriminantForm enumeration
Class group, general or largeBuchmann
Galois groupResolvents, after discriminant and cycle type tests

Primality and factoring

These are treated in full on their own pages: the primality landscape and the factoring comparison.

The general principles

Key point

Three rules cover most decisions. Run the cheap test first — trial division, a strong pseudoprime test, the Dedekind criterion. Normalise before working — reduce the polynomial, minimalise the curve, reduce the ideal. And measure crossovers rather than deriving them, because asymptotic constants are not practical constants.

Source. Henri Cohen, A Course in Computational Algebraic Number Theory, Springer GTM 138 — collection orientation material. Structural reference unverified: the source file was not available during authoring; chapter and section numbers are taken from the published edition and have not been checked against a physical copy.

Related pages

  • The Four Core Computational Tasks of Number Fields
  • Modern Factoring Methods Compared
  • Published Tables of Fields and Curves

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