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GuidePublished 7 Aug 2026Updated 13 Aug 20267 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 Sources8 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

Handbook application: from concept to controlled practice

Purpose. This expanded section turns the original page into a practical handbook. It preserves the supplied material and adds a repeatable way to apply, check and review Choosing an Algorithm: Decision Guide. It does not replace a contract, legislation, a controlled standard, competent engineering judgement or specialist advice.

The operating aim is to turn a compact mathematical statement into a usable chain of definitions, claims, examples and checks. Read the original explanation first, then use the workflow and checks below to convert knowledge into evidence.

Treat Choosing an Algorithm: Decision Guide as a network of definitions and implications, not as a list of formulas. The working vocabulary on this page—decision, algorithm, choosing, consolidated, across—should be made explicit before any proof or computation begins. Record the ambient set or structure, the permitted operations and the equality or equivalence relation in use. A compact theorem often changes meaning when the base field, finiteness condition, commutativity assumption or direction of an action changes.

For a proof, write the hypotheses as a checklist and mark the line at which each one is used. For a computation, state the representation of the input, the arithmetic model, the termination condition and the output invariant. For a classification problem, distinguish existence from uniqueness and distinguish an object from its representation. These separations prevent a correct local calculation from being mistaken for the general result.

A useful worked example should be small enough to inspect completely but rich enough to exercise the main mechanism. Compute the result in two ways where practical: symbolically and by substitution, structurally and numerically, or directly and through a normal form. Then include one near-miss example in which a hypothesis fails. The contrast explains why the theorem is shaped as it is and gives the reader a diagnostic pattern for later problems.

Verification is part of the mathematics. Check domains and codomains, substitute proposed solutions, test identity and zero cases, compare dimensions or cardinalities, and confirm that maps respect the required operations. In numerical work, report precision, conditioning and a residual rather than digits alone. In algorithmic work, separate mathematical correctness from implementation complexity and resource limits.

Step-by-step operating method

  1. Fix the setting. State the objects, ambient structure, notation and assumptions before manipulating symbols.
  2. Separate claims. Distinguish definitions, hypotheses, conclusions, equivalent conditions and consequences.
  3. Choose a method. Select proof, construction, calculation or algorithm according to the question actually asked.
  4. Work a small case. Use the smallest non-trivial example to expose the mechanism and test edge behaviour.
  5. Verify independently. Substitute back, check invariants, test boundary cases or use an alternative derivation.

Worked-example protocol

Illustrative method—not a source theorem. Start with a small admissible input and list the definitions it must satisfy. Carry out each transformation on a separate line, citing the property that permits it. Preserve exact values until approximation is necessary. At the end, verify the output against the original definition and one invariant such as dimension, degree, determinant, order, norm or residual. Then alter one hypothesis and observe which step ceases to be valid. This protocol creates a reusable example without inventing a theorem-specific numerical answer.

StageRecordQuality check
InputObjects, domain, notation, assumptionsEvery symbol is defined
MethodPermitted operation or cited result at each stepAll hypotheses hold
OutputExact result and representationCorrect type, domain and form
VerificationSubstitution, invariant or alternative derivationIndependent agreement
Boundary testZero, identity, degenerate or failed hypothesisScope is understood

Common failure modes and recovery actions

1. Watch for

Using a theorem without checking every hypothesis.

Recovery: Return to the governing definition or requirement and restate the decision in one sentence.

2. Watch for

Treating a suggestive example as a proof of the general case.

Recovery: Separate evidence from assumption, assign an owner and set a date for validation.

3. Watch for

Changing notation or conventions part-way through an argument.

Recovery: Run a small counterexample, boundary test, pilot or independent check before proceeding.

4. Watch for

Hiding a division-by-zero, convergence, finiteness or commutativity assumption.

Recovery: Record the consequence, decision and rationale, then update the controlled baseline.

5. Watch for

Reporting a computed result without a residual, substitution or structural check.

Recovery: Escalate when the issue affects safety, compliance, acceptance, material value or an agreed tolerance.

Review checklist

  • Can every symbol be traced to a definition or prior result?
  • Which hypothesis does each major step use?
  • Does the method cover zero, identity, degenerate and boundary cases?
  • Can the conclusion be checked by a second representation or calculation?
  • Are mandatory requirements distinguished from recommendations and illustrative values?
  • Are sources, assumptions, units, dates and versions recorded closely enough to reproduce the decision?
  • Have safety, legal, ethical, stakeholder and operational consequences been considered at the appropriate level?
  • Is there a named owner and a trigger for review, escalation, change or retirement?

Questions for deeper application

What is the most important distinction a practitioner must preserve when applying Choosing an Algorithm: Decision Guide?

Answer with a fact or cited source where available. Where evidence is incomplete, record the assumption, consequence, responsible owner and next validation action.

Which assumption about decision would change the result most if it proved false?

Answer with a fact or cited source where available. Where evidence is incomplete, record the assumption, consequence, responsible owner and next validation action.

What evidence would allow an independent reviewer to reproduce or challenge the conclusion?

Answer with a fact or cited source where available. Where evidence is incomplete, record the assumption, consequence, responsible owner and next validation action.

Which boundary, exception or failure case has not yet been tested?

Answer with a fact or cited source where available. Where evidence is incomplete, record the assumption, consequence, responsible owner and next validation action.

What must be handed over, monitored or reviewed after the immediate work is complete?

Answer with a fact or cited source where available. Where evidence is incomplete, record the assumption, consequence, responsible owner and next validation action.

Authoritative references and use notes

The sources below were selected as institutional or primary guidance for the broader practice. They support the handbook method; they do not imply that every statement or clause in a source applies to every project. Confirm the current edition, jurisdiction, contract and application before treating any requirement as mandatory.

  • NIST Digital Library of Mathematical Functions — National Institute of Standards and Technology. Used for mathematical notation, numerical methods, asymptotics and special functions. Accessed 2026-08-13.
  • MIT OpenCourseWare — Number Theory I — Massachusetts Institute of Technology. Used for algebraic and analytic number theory. Accessed 2026-08-13.

Implementation record: minimum fields

Create a compact record alongside the work. Include the purpose, context, responsible owner, stakeholders or affected users, inputs and sources, assumptions, method, acceptance or decision criteria, result, limitations, approval status, version and next review trigger. A reader should be able to understand not only what was concluded but why it was reasonable at the time.

Use plain language for decisions and reserve technical notation for places where it improves precision. Link every conclusion to the evidence that supports it. Where a source is secondary, old, proprietary or outside the applicable jurisdiction, note that limitation. Never silently turn a typical value, worked example, recommendation or software default into a mandatory requirement.

Handover and continual improvement

Before closing the work, identify what remains uncertain and who owns it. Transfer calculations, source records, models, approvals, test evidence, open actions and operating limits together. Agree how future users will recognise that the context has changed. Typical triggers include a new requirement, changed load or population, supplier or software revision, incident, repeated exception, capability shift, audit finding or adverse trend.

At the next review, compare the original assumptions with actual outcomes. Retain decisions that remain supported, correct weak controls and retire content that no longer reflects current practice. This feedback step converts a static article or template into a learning system and prevents old examples from becoming accidental policy.

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Published Tables of Fields and CurvesGuide · Engineering MathematicsNEXT LESSON →Modern Factoring Methods ComparedGuide · Engineering MathematicsNumber Theory Software PackagesGuide · Engineering MathematicsImplementation Pitfalls and Testing StrategyGuide · Engineering Mathematics
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