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GuidePublished 7 Aug 2026Updated 13 Aug 20268 min readBy Kevin Jogin
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Engineering  /  Mathematics  — Integer Algorithms

The Extended Euclidean Algorithm

Computing Bezout coefficients alongside the gcd, the recurrence for the coefficient sequences, and the size bounds that make it practical.

Page KV-MATH-0327Reading time 3 minReviewed 2026-08-07Author Kevin Jogin

Executive summary

The extended algorithm tracks, at every step, how the current remainder is expressed as an integer combination of the original inputs. When the algorithm terminates, that expression is Bezout's identity for the gcd.

It is the workhorse behind modular inversion, linear congruence solving, the Chinese remainder theorem and rational reconstruction.

Learning objectives

  1. State the coefficient recurrences and their initial conditions.
  2. Bound the size of the coefficients produced.
  3. Apply the result to compute modular inverses.

01The algorithm

Algorithm

Extended Euclidean algorithm

Inputintegers a, b
Outputd = gcd(a,b) and s, t with as + bt = d
  1. Set (r₀, s₀, t₀) = (a, 1, 0) and (r₁, s₁, t₁) = (b, 0, 1).
  2. While r₁ ≠ 0:
  3.   Compute q = r₀ div r₁.
  4.   Set (r₀, r₁) = (r₁, r₀ − q r₁).
  5.   Set (s₀, s₁) = (s₁, s₀ − q s₁).
  6.   Set (t₀, t₁) = (t₁, t₀ − q t₁).
  7. Return (r₀, s₀, t₀) with r₀ = gcd(a,b) and a s₀ + b t₀ = r₀.
Cost  O(len(a) · len(b)) bit operations

The invariant a sᵢ + b tᵢ = rᵢ holds at every step, by induction: it holds initially, and the update applies the same linear combination to all three sequences simultaneously.

02Coefficient size

Theorem

Coefficient bounds

The coefficients returned satisfy |s| ≤ b/(2d) and |t| ≤ a/(2d) where d = gcd(a,b), for inputs not in degenerate cases.

This bound is what makes the algorithm practical. The coefficients never grow beyond the size of the inputs, so no intermediate expression explosion occurs and the whole computation stays within the same order of magnitude as the inputs.

Note
The coefficient sequences alternate in sign and grow monotonically in absolute value, which gives a cheap internal consistency check: any implementation producing a coefficient exceeding the input magnitude has a bug.

03Modular inversion

The primary application. To invert a modulo n, run the extended algorithm on (a, n). If the gcd is 1, the coefficient of a reduced modulo n is the inverse.

Algorithm

Modular inverse

Inputa, n with n > 1
Outputa⁻¹ mod n, or a report that a is not invertible
  1. Run extended Euclid on (a, n) to obtain d, s, t with as + nt = d.
  2. If d ≠ 1, report that no inverse exists and stop.
  3. Return s mod n.
Cost  O(len(n)²) bit operations
Caution
The returned s may be negative and must be normalised into [0, n). Skipping the normalisation produces a value that is mathematically correct as a residue class but breaks any subsequent comparison or serialisation that assumes canonical representatives.

A binary extended variant avoids division entirely, mirroring the binary gcd. It is preferred on hardware where division is disproportionately expensive, and it is easier to make constant-time.

04Frequently asked questions

Is only one coefficient ever needed?

For modular inversion, yes — the coefficient of a. Implementations often omit the t sequence entirely, halving the bookkeeping, and recover t from the identity if it is ever required.

Why do the coefficients stay small?

Because they are built from the quotient sequence, and the product of all quotients is bounded by the input. Large quotients mean fast termination, so the two effects offset each other exactly.

Can this be made constant-time?

Not straightforwardly, because both the iteration count and the quotients depend on the inputs. Constant-time modular inversion in cryptographic libraries typically uses Fermat exponentiation or a fixed-iteration binary variant instead.

Related pages

  • Solving Linear Congruences
  • Euclid's Algorithm for Integer GCD
  • Modular Inverses and Chinese Remaindering

Sources and method

Structural reference: Victor Shoup, A Computational Introduction to Number Theory and Algebra, Version 1, Cambridge University Press, 2005 — book pages 58-62.

This page carries the durable method layer only: definitions, constructions, algorithms, complexity results and selection criteria, authored originally for KEVOS. No text is transcribed or paraphrased from the source, and no numeric tables or benchmark data are reproduced — these are routed to live authoritative sources instead.

Author: Kevin Jogin. Last reviewed 2026-08-07.

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 The Extended Euclidean Algorithm. 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 The Extended Euclidean Algorithm as a network of definitions and implications, not as a list of formulas. The working vocabulary on this page—algorithm, extended, euclidean, coefficient, size—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 The Extended Euclidean Algorithm?

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 algorithm 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.

  • MIT OpenCourseWare — Number Theory I — Massachusetts Institute of Technology. Used for algebraic and analytic number theory. Accessed 2026-08-13.
  • MIT OpenCourseWare — Algebra I — Massachusetts Institute of Technology. Used for groups, vector spaces, linear transformations and linear groups. Accessed 2026-08-13.

Continue learning

Euclid's Algorithm for Integer GCDGuide · Engineering MathematicsNEXT LESSON →Modular Inverses and Chinese RemainderingGuide · Engineering MathematicsFaster Integer Arithmetic: Karatsuba and BeyondGuide · Engineering MathematicsSpeeding Up Algorithms via Modular ComputationGuide · Engineering Mathematics
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