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Informational 19 Bitcoin

Use cluster linearization for transaction relay sort order

Public commit record

What the developer wrote

Authored by Suhas Daftuar

95/100 · Strong
Use cluster linearization for transaction relay sort order

Previously, transaction batches were first sorted by ancestor count and then
feerate, to ensure transactions are announced in a topologically valid order,
while prioritizing higher feerate transactions. Ancestor count is a crude
topological sort criteria, so replace this with linearization order so that the
highest feerate transactions (as would be observed by the mining algorithm) are
relayed before lower feerate ones, in a topologically valid way.

This also fixes a test that only worked due to the ancestor-count-based sort
order.
✓ Specific, descriptive subject✓ Names a concrete action or component✓ Provides detailed explanatory context✓ Explains rationale or failure mode✓ Mentions testing or verification
The short version

What changed, and why it matters

This commit changes the order in which Bitcoin nodes announce pending transactions to peers. Previously, transactions were announced based on how many ancestor transactions they had, then by fee rate. Now they are announced using the same 'cluster linearization' order the mining code uses, so higher-fee transactions are relayed first while still respecting dependency order. The change also updates a test that depended on the old ordering. There is no indication this fixes a security vulnerability; it is a behavior refinement.

Recommended action

No security action required. Treat as a normal protocol/behavior optimization. Reviewers may want to confirm that CompareMainOrder is deterministic and that the relay comparator remains transitive under all mempool states.

Security signals we found

01

No security-relevant signals in commit message or diff

02

Behavior change in P2P relay ordering only

03

No memory safety, cryptographic, consensus, or authorization changes

Risk score

Why this scored 19/100

Our methodology →
Potential impact 2/30
Exploitability 1/25
Stealth signal 1/15
Affected reach 3/15
Confidence 8/10
Evidence quality 4/5
Human-validated context

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