cpp-systems: tor CLEAN.md updated to note existing patches tor-0001/0002/0003

Scanned bitcoin/dragonfly/tor/transmission/nmap/ceph/allegro5 for additional
CWE-407 defects. All repos found CLEAN beyond previously recorded patches.
Updated tor/CLEAN.md to correctly reference existing tor-0001 through tor-0003.
This commit is contained in:
russell@unturf.com 2026-03-29 19:54:59 -04:00
parent df8daceb3c
commit 068ebbd29f
21 changed files with 1069 additions and 46 deletions

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# UNDF: UNDF-2026-000000234
# UNDF: (pending)
# artemis-0002: FileConfigurationParser.parseSecurityRoles — O(N×R) multiple ArrayList.contains in role loop
## CWE-407 — Algorithmic Complexity: Unnecessary Quadratic Complexity (List membership inside loop)
| Field | Value |
|-------|-------|
| ID | artemis-0002 |
| Severity | MEDIUM |
| Ecosystem | activemq-artemis |
| Package | org.apache.activemq.artemis.core.deployers.impl |
| File | `artemis-server/src/main/java/org/apache/activemq/artemis/core/deployers/impl/FileConfigurationParser.java` |
| Lines | 12121275 |
| Complexity | O(N×R) |
| Hot path | broker startup / configuration reload |
## Defect
`FileConfigurationParser` parses broker security roles from XML configuration.
It builds per-permission `ArrayList<String>` collections (send, consume,
createDurableQueue, deleteDurableQueue, createNonDurableQueue, deleteNonDurableQueue,
manageRoles, browseRoles, createAddressRoles, deleteAddressRoles, viewRoles,
editRoles), then for each role in `allRoles` (N roles) it calls `.contains(role)`
on up to 12 of these lists. Each call is O(R) where R is the maximum number of
roles in any single permission list. Total cost: O(N × 12 × R) = O(N²) in the
degenerate case where all roles have all permissions.
Additionally, `allRoles` itself is populated using `!allRoles.contains(role.trim())`
which is O(N) per insertion — another O(N²) scan.
```java
// FileConfigurationParser.java lines 1212-1275
List<String> send = new ArrayList<>();
List<String> consume = new ArrayList<>();
// ... 10 more ArrayList<String> ...
List<String> allRoles = new ArrayList<>();
// ... XML parsing loop populates the lists ...
if (!allRoles.contains(role.trim())) { // O(N) per role — O(N²) total
allRoles.add(role.trim());
}
for (String role : allRoles) {
securityRoles.add(new Role(role,
send.contains(role), // O(R) × 12 per role
consume.contains(role),
createDurableQueue.contains(role),
deleteDurableQueue.contains(role),
createNonDurableQueue.contains(role),
deleteNonDurableQueue.contains(role),
manageRoles.contains(role),
browseRoles.contains(role),
createAddressRoles.contains(role),
deleteAddressRoles.contains(role),
viewRoles.contains(role),
editRoles.contains(role)));
}
```
## Fix
Use `HashSet<String>` (or `LinkedHashSet<String>` to preserve order) for all the
permission lists, and for `allRoles`:
```java
Set<String> send = new LinkedHashSet<>();
Set<String> consume = new LinkedHashSet<>();
Set<String> createDurableQueue = new LinkedHashSet<>();
Set<String> deleteDurableQueue = new LinkedHashSet<>();
Set<String> createNonDurableQueue = new LinkedHashSet<>();
Set<String> deleteNonDurableQueue = new LinkedHashSet<>();
Set<String> manageRoles = new LinkedHashSet<>();
Set<String> browseRoles = new LinkedHashSet<>();
Set<String> createAddressRoles = new LinkedHashSet<>();
Set<String> deleteAddressRoles = new LinkedHashSet<>();
Set<String> viewRoles = new LinkedHashSet<>();
Set<String> editRoles = new LinkedHashSet<>();
Set<String> allRoles = new LinkedHashSet<>();
// allRoles population: add() already deduplicates in a Set — no contains() check needed
allRoles.add(role.trim()); // replaces the !allRoles.contains() guard
// Role construction loop unchanged — Set.contains() is O(1)
for (String role : allRoles) {
securityRoles.add(new Role(role,
send.contains(role), consume.contains(role), ...));
}
```
## Speedup
| N (roles) | R (roles per permission) | Before (ops) | After (ops) | Speedup |
|-----------|--------------------------|-------------|-------------|---------|
| 50 | 50 | ~30,000 | ~600 | 50× |
| 200 | 200 | ~480,000 | ~2,400 | 200× |
| 1,000 | 1,000 | ~12,000,000 | ~12,000 | 1,000× |
Most Artemis deployments have modest role counts (1050) but enterprise LDAP-backed
configurations with fine-grained per-address permissions can have hundreds of roles.
The defect is hit on every broker startup and every live configuration reload.

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# UNDF: UNDF-2026-000000015
# UNDF: UNDF-2026-000000235
--- a/src/broad_phase.h
+++ b/src/broad_phase.h
@@ -30,8 +30,9 @@ typedef struct b2BroadPhase

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# UNDF: UNDF-2026-000000289
# UNDF: (pending)
# doris-0002: PlanNode.addConjunct — ArrayList.contains() O(C²) dedup

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# UNDF: UNDF-2026-000000054
# UNDF: UNDF-2026-000000314
--- a/Source/Dry/UI/ListView.h
+++ b/Source/Dry/UI/ListView.h
@@ -... ListView class members

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# UNDF: UNDF-2026-000000055
# UNDF: UNDF-2026-000000316
--- a/Source/Dry/Core/Object.cpp
+++ b/Source/Dry/Core/Object.cpp
@@ -269,12 +269,16 @@ void Object::UnsubscribeFromAllEventsExcept(const PODVector<StringHash>& exceptions, bool onlyUserData)

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# CLEAN — gRPC (multi-language)
Scanned 2026-03-29 for CWE-407.
# CLEAN — gRPC
Scanned 2026-03-29 for CWE-407 (algorithmic complexity).
## Scope
- Java source: `examples/android/helloworld/` only (no Java RPC core in this clone)
- C++ core: `core/lib/`, `src/core/` — service resolution, call handling
The cloned `~/git/grpc` repository is the gRPC C/C++ core repo, not the Java
implementation (`grpc-java`). No Java source files were found in `src/` beyond
Android example activities.
## Findings
- No Java main-path source files present in this clone.
- gRPC Java (`io.grpc:grpc-*`) ships as a separate Maven/Gradle repository
(`grpc/grpc-java` on GitHub) which was not cloned.
gRPC's Java implementation in this repository is limited to example code. The core RPC runtime is implemented in C++ and uses protobuf-generated descriptors with flat-array or hash-map lookups for service and method resolution. No quadratic list-membership pattern was found in:
- Method descriptor building (protobuf ServiceDescriptor uses array indexing)
- Service type resolution (registry uses hash map)
- Call filter/interceptor chains (fixed-size arrays assembled at startup)
**Result: No actionable CWE-407 defects.**
## Result
**CLEAN (N/A). No Java CWE-407 defects findable in this clone — wrong repo flavor.**
**Action: clone `grpc/grpc-java` for a proper Java scan if needed.**

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# CLEAN — Google Guice
Scanned 2026-03-29 for CWE-407 (algorithmic complexity).
## Scope
Module scanned: core/src (binding processor, injection point resolution, type listener store,
provision listener store, cycle-detecting lock, annotations).
## Findings
### MembersInjectorStore — alreadySeenListeners.contains()
`alreadySeenListeners` is declared `Set<TypeListener> alreadySeenListeners = Sets.newHashSet()`.
O(1) membership checks. Clean.
### BindingSourceRestriction — currentModulePermits.contains()
`currentModulePermits` is `ImmutableSet<Class<? extends Annotation>>`. O(1). Clean.
### AbstractBindingProcessor — FORBIDDEN_TYPES.contains()
`FORBIDDEN_TYPES` is an `ImmutableSet`. O(1). Clean.
### ProvisionListenerCallbackStore — INTERNAL_BINDINGS.contains()
`INTERNAL_BINDINGS` is an `ImmutableSet<Key<?>>`. O(1). Clean.
### InjectorJitBindingData — failedJitBindings.contains(), bannedKeys.contains()
Both fields are `Set` implementations. Clean.
## Result
**CLEAN. No actionable CWE-407 defects found in Google Guice.**

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# CLEAN — Hibernate ORM
Scanned 2026-03-29 for CWE-407 (algorithmic complexity).
## Scope
hibernate-core/src/main/java — SqmUtil, ActionQueue, BulkOperationCleanupAction,
LoadQueryInfluencers, StatefulPersistenceContext, ToOneAttributeMapping,
ManyToManyCollectionPart, BaseSqmToSqlAstConverter, GeneratedValuesProcessor.
## Findings
### ActionQueue — tableSpaces.contains()
Parameter `Set<? extends Serializable> tableSpaces` — O(1). Clean.
### BulkOperationCleanupAction — affectedTableSpaces.contains()
Parameter is `Set<?>` — O(1). Clean.
### LoadQueryInfluencers — enabledFetchProfileNames.contains()
`enabledFetchProfileNames` is `HashSet<String>` — O(1). Clean.
### ToOneAttributeMapping — targetKeyPropertyNames.contains()
`targetKeyPropertyNames` is `Set<String>` backed by `HashSet` — O(1). Clean.
### StatefulPersistenceContext — nullAssociations.contains(), insertedEntityIds.contains()
Both backed by `HashSet` implementations — O(1). Clean.
### BaseSqmToSqlAstConverter — visitedAssociationKeys.contains(), excludedEntityNames.contains()
Both are `Set` or `HashSet` fields — O(1). Clean.
## Result
**CLEAN. No actionable CWE-407 defects found in Hibernate ORM.**

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# UNDF: UNDF-2026-000000134
# UNDF: (pending)
# kotlin-0001: NonExpansiveInheritanceRestrictionChecker.collectReachable — O(E×V) list scan on reachability result
## CWE-407 — Algorithmic Complexity: Inefficient Algorithmic Complexity
| Field | Value |
|-------|-------|
| ID | kotlin-0001 |
| Severity | HIGH |
| Ecosystem | kotlin |
| Package | org.jetbrains.kotlin.resolve |
| File | `compiler/frontend/src/org/jetbrains/kotlin/resolve/NonExpansiveInheritanceRestrictionChecker.kt` |
| Lines | 150169 |
| Complexity | O(E × V) — was O(V) list scan per edge in cycle check |
| Hot path | Type-checking of generic class declarations with complex supertype bounds |
## Defect
`collectReachable` builds the set of type-parameter nodes reachable from a given start node
during the expansive-inheritance check (SLS §4.5 / KLS §11.2). The original implementation
returns a `List<T>` via `DFS.NodeHandlerWithListResult`. The result is immediately consumed
in `isEdgeInCycle`:
```kotlin
private fun <T> Graph<T>.isEdgeInCycle(edge: ExpansiveEdge<T>) =
edge.from in collectReachable(edge.to)
private fun <T> Graph<T>.collectReachable(from: T): List<T> { // BUG: List
val handler = object : DFS.NodeHandlerWithListResult<T, T>() {
override fun afterChildren(current: T?) {
result.add(current)
}
}
val neighbors = object : DFS.Neighbors<T> {
override fun getNeighbors(current: T): Iterable<T> =
this@collectReachable.getNeighbors(current)
}
DFS.dfs(listOf(from), neighbors, handler)
return handler.result()
}
```
`edge.from in collectReachable(edge.to)` uses Kotlin's `in` operator on a `List<T>`, which
compiles to `List.contains()` — a linear O(V) scan. The check is performed once per
expansive edge, so with E expansive edges and V type-parameter nodes the total cost is
**O(E × V)**. For a deeply layered generic hierarchy (e.g. a sealed-trait diamond with
many type parameters), E and V grow together, making this O(V²) in the worst case.
## Fix
Accumulate the reachable nodes into a `HashSet<T>` directly and return `Set<T>`, so the
`in` membership test at the call site becomes O(1):
```kotlin
private fun <T> Graph<T>.isEdgeInCycle(edge: ExpansiveEdge<T>) =
edge.from in collectReachable(edge.to) // unchanged — but now O(1)
// Return Set<T> so `in` is O(1) hash lookup instead of O(V) list scan
private fun <T> Graph<T>.collectReachable(from: T): Set<T> {
val reachable = hashSetOf<T>()
val handler = object : DFS.NodeHandlerWithListResult<T, T>() {
override fun afterChildren(current: T?) {
if (current != null) reachable.add(current)
}
}
val neighbors = object : DFS.Neighbors<T> {
override fun getNeighbors(current: T): Iterable<T> =
this@collectReachable.getNeighbors(current)
}
DFS.dfs(listOf(from), neighbors, handler)
return reachable
}
```
`TypeParameterDescriptor` already implements `equals`/`hashCode` (identity by object),
so storing it in a `HashSet` is correct and safe.
## Speedup
| V (type params) | E (expansive edges) | Before (ops) | After (ops) | Speedup |
|-----------------|---------------------|-------------|-------------|---------|
| 10 | 10 | 100 | 10 | 10× |
| 50 | 50 | 2,500 | 50 | 50× |
| 100 | 100 | 10,000 | 100 | 100× |
| 200 | 200 | 40,000 | 200 | 200× |
Real-world Kotlin classes rarely exceed V=20 type parameters, but annotation-heavy
codebases (frameworks using typeclasses / phantom types) can push higher. The patch
removes an entire complexity class regardless of input size.
## Affected Versions
All Kotlin compiler versions that include `NonExpansiveInheritanceRestrictionChecker`
(introduced circa Kotlin 1.0; still present in Kotlin 2.x frontend compatibility layer).
## References
- JetBrains YouTrack (none filed)
- Upstream source: `compiler/frontend/src/org/jetbrains/kotlin/resolve/NonExpansiveInheritanceRestrictionChecker.kt`
- CWE-407: https://cwe.mitre.org/data/definitions/407.html

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# UNDF: UNDF-2026-000000135
# UNDF: (pending)
# kotlin-0002: ConstraintSystemBuilderImpl.addBound — O(B) ArrayList scan per constraint during type inference
## CWE-407 — Algorithmic Complexity: Inefficient Algorithmic Complexity
| Field | Value |
|-------|-------|
| ID | kotlin-0002 |
| Severity | MEDIUM |
| Ecosystem | kotlin |
| Package | org.jetbrains.kotlin.resolve.calls.inference |
| File | `compiler/frontend/src/org/jetbrains/kotlin/resolve/calls/inference/ConstraintSystemBuilderImpl.kt` |
| Lines | 266279 |
| Complexity | O(B) duplicate-check per addBound call; O(B²) total per type variable during constraint incorporation |
| Hot path | Type inference for every generic call site |
## Defect
`ConstraintSystemBuilderImpl.addBound()` deduplicates bounds before adding them to prevent
the constraint incorporation loop from diverging. The dedup check uses `ArrayList.contains()`:
```kotlin
// TypeBoundsImpl.kt:31
override val bounds = ArrayList<Bound>() // BUG: ArrayList
// ConstraintSystemBuilderImpl.kt:277
val typeBounds = getTypeBounds(typeVariable)
if (typeBounds.bounds.contains(bound)) return // O(B) linear scan per call
typeBounds.addBound(bound)
```
`TypeBounds.Bound` defines `equals()` and `hashCode()` (comparing `typeVariable`,
`constrainingType`, `kind`, and `position.isStrong()`), making it fully eligible for
storage in a hash-based collection.
During constraint incorporation (`constraintIncorporation.kt`), `incorporateBound()` is
called once per new bound and may call `addBound` O(B) times as it cross-multiplies with
existing bounds. Each `addBound` performs an O(B) `contains` scan, yielding **O(B²)
total** duplicate-check work per type variable per incorporation round. For functions with
many type parameters and complex bounds (e.g. higher-kinded types, SAM conversions with
many overloads), B can reach 3050 during a single call resolution.
## Fix
Change `TypeBoundsImpl.bounds` from `ArrayList<Bound>` to `LinkedHashSet<Bound>` to
provide O(1) `contains` and maintain insertion order for deterministic value computation:
```kotlin
// TypeBoundsImpl.kt — change bounds to LinkedHashSet
class TypeBoundsImpl(override val typeVariable: TypeVariable) : TypeBounds {
override val bounds: MutableSet<Bound> = LinkedHashSet() // was: ArrayList<Bound>()
fun addBound(bound: Bound) {
resultValues = null
assert(bound.typeVariable == typeVariable) { ... }
bounds.add(bound)
}
// ... rest unchanged
}
```
The `TypeBounds` interface declares `bounds: Collection<Bound>`, so changing the concrete
type to `LinkedHashSet` is a compatible implementation change. All iteration patterns
(`bounds.indices`, `bounds.filter`, `bounds.any`, `bounds.flatMap`) work identically on
`Set` as on `List`.
The dedup guard in `ConstraintSystemBuilderImpl.addBound()` can then rely on
`LinkedHashSet.add()` returning `false` on duplicate, or retain the explicit check — both
become O(1).
## Speedup
| B (bounds per type var) | Before (contains ops) | After (contains ops) | Speedup |
|-------------------------|-----------------------|----------------------|---------|
| 10 | 100 | 10 | 10× |
| 30 | 900 | 30 | 30× |
| 50 | 2,500 | 50 | 50× |
Typical Kotlin inference sessions for moderate generics see B ≈ 515; complex higher-kinded
scenarios can reach B = 3050. The patch provides consistent O(1) dedup across all cases.
## Affected Versions
All Kotlin compiler versions with `ConstraintSystemBuilderImpl` / `TypeBoundsImpl`
(Kotlin 1.0+; still present in K1 frontend used by kotlinc and IntelliJ IDEA K1 mode).
## References
- JetBrains YouTrack (none filed)
- Upstream source: `compiler/frontend/src/org/jetbrains/kotlin/resolve/calls/inference/`
- CWE-407: https://cwe.mitre.org/data/definitions/407.html

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# CLEAN — Netty
Scanned 2026-03-29 for CWE-407 (algorithmic complexity).
## Scope
Modules scanned: common, handler (SSL/TLS), codec-http, codec-http2, transport.
## Findings
### handler/ssl/JdkBaseApplicationProtocolNegotiator — NoFailProtocolSelector.select()
`for (String p : supportedProtocols)` iterates a `Set<String>` (field declared as
`Set<String> supportedProtocols`) and calls `protocols.contains(p)` on a `List<String>`.
The outer set is O(S) where S = supported ALPN protocol count (typically 13); inner
list scan is O(P) where P = negotiated protocol count (also typically 13). Total O(S×P)
but bounded to small constants — not actionable.
### handler/ssl/JdkBaseApplicationProtocolNegotiator — NoFailProtocolSelectionListener.selected()
`supportedProtocols.contains(protocol)` — single call, not in a loop. Not a CWE-407 issue.
### handler/ssl/SslUtils.addIfSupported()
`supported.contains(n)``supported` is declared `Set<String>`. O(1). Clean.
### codec-http2/HttpConversionUtil — HTTP_TO_HTTP2_HEADER_BLACKLIST.contains()
Both `HTTP_TO_HTTP2_HEADER_BLACKLIST` and `connectionBlacklist` are `Set<AsciiString>` — O(1). Clean.
### transport/NioChannelOption — supportedOptions().contains()
Returns `Set<SocketOption<?>>` from the JDK. Clean.
## Result
**CLEAN. No actionable CWE-407 defects found in Netty.**

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# UNDF: UNDF-2026-000000472
# UNDF: (pending)
# nifi-0001: StandardParameterContext.verifyNoCycles — O(D²) Stack.contains on DFS path
## CWE-407 — Algorithmic Complexity
| Field | Value |
|-------|-------|
| ID | nifi-0001 |
| Severity | MEDIUM |
| Ecosystem | nifi |
| Package | nifi-framework-components |
| File | `nifi-framework-bundle/nifi-framework/nifi-framework-components/src/main/java/org/apache/nifi/parameter/StandardParameterContext.java` |
| Lines | 532556 |
| Complexity | O(D²) |
| Hot path | Called on every ParameterContext inheritance update |
## Defect
`verifyNoCycles` uses a `Stack<String>` (which extends `Vector<String>`) to track the DFS
path and calls `traversedIds.contains(id)` to detect back-edges. `Stack.contains()` is an
O(D) linear scan, called once per node at each recursion level, giving O(D²) total where D is
the depth of the ParameterContext inheritance chain.
```java
private void verifyNoCycles(final Stack<String> traversedIds,
final List<ParameterContext> parameterContexts) {
for (final ParameterContext parameterContext : parameterContexts) {
final String id = parameterContext.getIdentifier();
if (traversedIds.contains(id)) { // O(D) linear scan
throw new IllegalStateException(...);
}
traversedIds.push(id);
verifyNoCycles(traversedIds, parameterContext.getInheritedParameterContexts());
traversedIds.pop();
}
}
```
## Fix
Replace `Stack<String>` with a `HashSet<String>` for the visited-in-current-path set. Since
`Stack` is used as a DFS path tracker, we need O(1) membership checks. Use a `Set<String>` for
the cycle check and a separate `Deque<String>` only if ordering is needed (it is not here).
```java
private void verifyNoCycles(final List<ParameterContext> parameterContexts) {
final Set<String> traversedIds = new HashSet<>();
traversedIds.add(id);
verifyNoCycles(traversedIds, parameterContexts);
}
private void verifyNoCycles(final Set<String> traversedIds,
final List<ParameterContext> parameterContexts) {
for (final ParameterContext parameterContext : parameterContexts) {
final String id = parameterContext.getIdentifier();
if (traversedIds.contains(id)) { // O(1) hash lookup
throw new IllegalStateException(
String.format("Circular references in Parameter Contexts not allowed. "
+ "[%s] was detected in a cycle.", parameterContext.getName()));
}
traversedIds.add(id);
verifyNoCycles(traversedIds, parameterContext.getInheritedParameterContexts());
traversedIds.remove(id);
}
}
```
## Speedup
| D (chain depth) | Before (ops) | After (ops) | Speedup |
|-----------------|-------------|-------------|---------|
| 10 | 100 | 10 | 10× |
| 50 | 2,500 | 50 | 50× |
| 100 | 10,000 | 100 | 100× |
| 500 | 250,000 | 500 | 500× |

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# CLEAN — Protocol Buffers (Java)
Scanned 2026-03-29 for CWE-407 (algorithmic complexity).
## Scope
Java library: java/core/src/main and java/util/src/main — Descriptors, DynamicMessage,
MessageLiteToString, JsonFormat, SchemaUtil, DescriptorMessageInfoFactory.
## Findings
### MessageLiteToString — setters.contains()
`setters` is `Set<String> setters = new HashSet<>()`. O(1). Clean.
### JsonFormat — includingDefaultValueFields.contains()
`includingDefaultValueFields` is `Set<FieldDescriptor>`. O(1). Clean.
### DescriptorMessageInfoFactory — specialFieldNames.contains()
`specialFieldNames` is a static `Set<String>`. O(1). Clean.
## Result
**CLEAN. No actionable CWE-407 defects found in Protocol Buffers Java library.**

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# UNDF: UNDF-2026-000000271
# UNDF: (pending)
# scala3-0001: Namer.addWildcardForwarders — O(M×S) List[TermName] seen-scan for Given export forwarders
## CWE-407 — Algorithmic Complexity: Inefficient Algorithmic Complexity
| Field | Value |
|-------|-------|
| ID | scala3-0001 |
| Severity | MEDIUM |
| Ecosystem | scala3 |
| Package | dotty.tools.dotc.typer |
| File | `compiler/src/dotty/tools/dotc/typer/Namer.scala` |
| Lines | 14181448 |
| Complexity | O(M × S) — O(S) list scan per member for Given exports |
| Hot path | `export` clause compilation — executed once per export statement |
## Defect
`Namer.addWildcardForwarders` is called when an `export path.*` wildcard clause is
compiled. It receives `seen: List[TermName]` — the names of explicitly-listed selectors
that precede the wildcard in the same export clause (built by prepending in
`addForwarders`).
For **non-Given** members the code correctly materializes `seen` into a `mutable.HashSet`
at the top of the function (`nonContextual`). But for **Given** members, it falls back to
the raw `List.contains()` O(S) scan on every member:
```scala
def addWildcardForwarders(seen: List[TermName], span: Span): Unit =
val nonContextual = mutable.HashSet(seen*) // O(S) one-time copy — OK for non-Given branch
...
for mbr <- pathType.membersBasedOnFlags(...) do
...
val alias = mbr.name.toTermName
if mbr.symbol.is(Given) then
if !seen.contains(alias) && mbr.matchesImportBound(givenBound) then // BUG: O(S) per member
addForwarder(alias, mbr, span)
else if !nonContextual.contains(alias) ... // OK: O(1)
```
With M members in `pathType` and S explicit selectors in `seen`, the Given branch
performs **O(M × S)** comparisons. The non-Given branch already pays this cost to
construct `nonContextual`, but does it only once (O(S)) then O(1) per lookup.
The Given branch neglects to reuse `nonContextual` and re-scans the original list
per member.
`TermName` is a value type with a stable `hashCode`, making it safe in `HashSet`.
## Fix
Reuse `nonContextual` (which already contains all names from `seen`) for the Given branch
lookup. Both branches then pay O(1) per member:
```scala
def addWildcardForwarders(seen: List[TermName], span: Span): Unit =
val nonContextual = mutable.HashSet(seen*) // covers both Given and non-Given
...
for mbr <- pathType.membersBasedOnFlags(...) do
...
val alias = mbr.name.toTermName
if mbr.symbol.is(Given) then
if !nonContextual.contains(alias) && mbr.matchesImportBound(givenBound) then // FIX: O(1)
addForwarder(alias, mbr, span)
else if !nonContextual.contains(alias) && mbr.matchesImportBound(wildcardBound) then
nonContextual += alias
addWildcardForwardersNamed(alias, span)
```
The semantics are identical: `seen` contains the names of all explicit selectors, and
`nonContextual` is initialized to exactly `seen*`, so `nonContextual.contains(alias)` is
equivalent to `seen.contains(alias)` but O(1) instead of O(S).
## Speedup
| M (members) | S (selectors) | Before (Given ops) | After (Given ops) | Speedup |
|-------------|---------------|-------------------|-------------------|---------|
| 50 | 10 | 500 | 50 | 10× |
| 200 | 20 | 4,000 | 200 | 20× |
| 500 | 50 | 25,000 | 500 | 50× |
Typical Scala 3 `export` clauses target trait-rich objects with O(100500) members
and O(530) explicit selectors. The pathological case is a large typeclass object
with many given instances and a long list of explicit `export` selectors.
## Affected Versions
Scala 3.x (dotty) — `addWildcardForwarders` present since `export` was introduced
in Scala 3.0; affects all versions through current main branch.
## References
- Scala 3 issue tracker (none filed)
- Upstream source: `compiler/src/dotty/tools/dotc/typer/Namer.scala`
- CWE-407: https://cwe.mitre.org/data/definitions/407.html

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# UNDF: UNDF-2026-000000295
# UNDF: (pending)
# spring-0001: BeanFactoryUtils.mergeNamesWithParent — O(P×R) ArrayList.contains inside loop
## CWE-407 — Algorithmic Complexity: Unnecessary Quadratic Complexity (List membership inside loop)
| Field | Value |
|-------|-------|
| ID | spring-0001 |
| Severity | MEDIUM |
| Ecosystem | spring-framework |
| Package | org.springframework.beans.factory |
| File | `spring-beans/src/main/java/org/springframework/beans/factory/BeanFactoryUtils.java` |
| Lines | 525532 |
| Complexity | O(P×R) |
| Hot path | bean type resolution with hierarchical ApplicationContext |
## Defect
`BeanFactoryUtils.mergeNamesWithParent()` is called by
`beanNamesForTypeIncludingAncestors()` and related methods to merge bean name
lists from parent and child application contexts. The `merged` variable is an
`ArrayList<String>`. For each of the P entries in `parentResult`, the code calls
`merged.contains(beanName)` — an O(R) linear scan where R is the number of
already-added names. Total cost O(P×R).
```java
// BeanFactoryUtils.java line 521-532
private static String[] mergeNamesWithParent(String[] result, String[] parentResult,
HierarchicalBeanFactory hbf) {
if (parentResult.length == 0) {
return result;
}
List<String> merged = new ArrayList<>(result.length + parentResult.length);
merged.addAll(Arrays.asList(result));
for (String beanName : parentResult) {
if (!merged.contains(beanName) && !hbf.containsLocalBean(beanName)) {
// ^^^^^^^^ O(R) per iteration → O(P×R) total
merged.add(beanName);
}
}
return StringUtils.toStringArray(merged);
}
```
This method is called from `getBeanNamesForType()`, `beanNamesForAnnotationIncludingAncestors()`,
and similar utility methods which can be called at runtime (e.g., during dependency injection,
AOP proxy creation, and Spring Boot auto-configuration) with deep ApplicationContext hierarchies.
## Fix
Use a `LinkedHashSet` to preserve insertion order while providing O(1) membership tests,
or build a `HashSet` for the dedup check:
```java
private static String[] mergeNamesWithParent(String[] result, String[] parentResult,
HierarchicalBeanFactory hbf) {
if (parentResult.length == 0) {
return result;
}
Set<String> seen = new HashSet<>(Arrays.asList(result));
List<String> merged = new ArrayList<>(result.length + parentResult.length);
merged.addAll(Arrays.asList(result));
for (String beanName : parentResult) {
if (!seen.contains(beanName) && !hbf.containsLocalBean(beanName)) {
seen.add(beanName);
merged.add(beanName);
}
}
return StringUtils.toStringArray(merged);
}
```
Alternatively, use `LinkedHashSet` directly:
```java
private static String[] mergeNamesWithParent(String[] result, String[] parentResult,
HierarchicalBeanFactory hbf) {
if (parentResult.length == 0) {
return result;
}
Set<String> merged = new LinkedHashSet<>(Arrays.asList(result));
for (String beanName : parentResult) {
if (!merged.contains(beanName) && !hbf.containsLocalBean(beanName)) {
merged.add(beanName);
}
}
return StringUtils.toStringArray(merged);
}
```
## Speedup
| R (result count) | P (parentResult count) | Before (ops) | After (ops) | Speedup |
|-----------------|------------------------|-------------|-------------|---------|
| 100 | 100 | 10,000 | 100 | 100× |
| 500 | 500 | 250,000 | 500 | 500× |
| 1,000 | 1,000 | 1,000,000 | 1,000 | 1,000× |
Applications with large numbers of beans and deep ApplicationContext hierarchies
(common in Spring Boot multi-module applications and OSGi container deployments)
are most affected.

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# UNDF: UNDF-2026-000000317
# UNDF: (pending)
# spring-0002: DefaultListableBeanFactory.getBeanNamesForAnnotation — O(B×M) ArrayList.contains inside loop
## CWE-407 — Algorithmic Complexity: Unnecessary Quadratic Complexity (List membership inside loop)
| Field | Value |
|-------|-------|
| ID | spring-0002 |
| Severity | MEDIUM |
| Ecosystem | spring-framework |
| Package | org.springframework.beans.factory.support |
| File | `spring-beans/src/main/java/org/springframework/beans/factory/support/DefaultListableBeanFactory.java` |
| Lines | 770784 |
| Complexity | O(B×M) |
| Hot path | `getBeanNamesForAnnotation()` — called during startup and annotation-driven wiring |
## Defect
`DefaultListableBeanFactory.getBeanNamesForAnnotation()` builds a result list from
two sources: `beanDefinitionNames` and `manualSingletonNames`. For each of the M
entries in `manualSingletonNames` it calls `result.contains(beanName)` where `result`
is an `ArrayList<String>` that has already been populated with up to B entries from
`beanDefinitionNames`. This is O(B×M) — quadratic in total bean count.
```java
// DefaultListableBeanFactory.java line 770-784
public String[] getBeanNamesForAnnotation(Class<? extends Annotation> annotationType) {
List<String> result = new ArrayList<>();
for (String beanName : this.beanDefinitionNames) {
BeanDefinition bd = this.beanDefinitionMap.get(beanName);
if (bd != null && !bd.isAbstract() && findAnnotationOnBean(beanName, annotationType) != null) {
result.add(beanName);
}
}
for (String beanName : this.manualSingletonNames) {
if (!result.contains(beanName) && findAnnotationOnBean(beanName, annotationType) != null) {
// ^^^^^^^^ O(B) per iteration → O(B×M) total
result.add(beanName);
}
}
return StringUtils.toStringArray(result);
}
```
`findAnnotationOnBean()` involves reflection and is itself expensive — but it is only called
after `result.contains()` succeeds (for the negative branch), so the list scan overhead is
paid on every iteration including those that ultimately do nothing.
## Fix
Build a `HashSet` shadow alongside `result` to provide O(1) dedup:
```java
public String[] getBeanNamesForAnnotation(Class<? extends Annotation> annotationType) {
List<String> result = new ArrayList<>();
Set<String> seen = new HashSet<>();
for (String beanName : this.beanDefinitionNames) {
BeanDefinition bd = this.beanDefinitionMap.get(beanName);
if (bd != null && !bd.isAbstract() && findAnnotationOnBean(beanName, annotationType) != null) {
result.add(beanName);
seen.add(beanName);
}
}
for (String beanName : this.manualSingletonNames) {
if (!seen.contains(beanName) && findAnnotationOnBean(beanName, annotationType) != null) {
result.add(beanName);
}
}
return StringUtils.toStringArray(result);
}
```
## Speedup
| B (bean definitions) | M (manual singletons) | Before (ops) | After (ops) | Speedup |
|---------------------|-----------------------|-------------|-------------|---------|
| 500 | 100 | 50,000 | 600 | 83× |
| 1,000 | 500 | 500,000 | 1,500 | 333× |
| 5,000 | 1,000 | 5,000,000 | 6,000 | 833× |
Large Spring Boot applications with hundreds of beans annotated with `@Service`,
`@Component`, `@Controller` etc. will benefit most. `getBeanNamesForAnnotation()`
is called by `getBeansWithAnnotation()`, event publisher detection, and various
Spring Boot auto-configuration processors.

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# UNDF: UNDF-2026-000000296
# UNDF: (pending)
# spring-0003: AnnotationTypeMapping.processAliases — O(A²×D×L) ArrayList.contains in nested annotation attribute loop
## CWE-407 — Algorithmic Complexity: Unnecessary Quadratic Complexity (List membership inside nested loop)
| Field | Value |
|-------|-------|
| ID | spring-0003 |
| Severity | MEDIUM |
| Ecosystem | spring-framework |
| Package | org.springframework.core.annotation |
| File | `spring-core/src/main/java/org/springframework/core/annotation/AnnotationTypeMapping.java` |
| Lines | 197258, 556573 |
| Complexity | O(A²×D×L) |
| Hot path | annotation type mapping initialization (startup + first use per annotation type) |
## Defect
`AnnotationTypeMapping.processAliases()` resolves `@AliasFor` relationships across
meta-annotation hierarchies. It is called once per annotation type during mapping
construction (cached afterwards). The `aliases` local variable is an `ArrayList<Method>`.
For each annotation attribute (A attributes), `processAliases(i, aliases)` is called.
Inside that method, for each level in the meta-annotation chain (D levels), it iterates
over all attributes (A) and calls `aliases.contains(mapping.attributes.get(i))` — an O(L)
scan where L is the current aliases list size. The same pattern appears in
`getFirstRootAttributeIndex()` and `MirrorSets.updateFrom()`.
```java
// processAliases(int attributeIndex, List<Method> aliases) — lines 223-248
AnnotationTypeMapping mapping = this;
while (mapping != null) { // D iterations (meta-annotation depth)
if (rootAttributeIndex != -1 && mapping != this.root) {
for (int i = 0; i < mapping.attributes.size(); i++) { // A iterations
if (aliases.contains(mapping.attributes.get(i))) { // O(L) scan
mapping.aliasMappings[i] = rootAttributeIndex;
}
}
}
mapping.mirrorSets.updateFrom(aliases); // updateFrom also calls aliases.contains()
...
mapping = mapping.source;
}
// MirrorSets.updateFrom(Collection<Method> aliases) — lines 556-573
for (int i = 0; i < attributes.size(); i++) { // A iterations
Method attribute = attributes.get(i);
if (aliases.contains(attribute)) { // O(L) scan
...
}
}
```
Total cost per annotation type: O(A × D × A × L) = O(A²×D×L).
For complex composed annotations (e.g., `@SpringBootTest`, `@Transactional`, framework
stereotypes with `@AliasFor` chains), A can be 1030, D can be 510, L can be 510,
yielding up to ~90,000 operations per annotation type initialization.
## Fix
Replace `List<Method>` with `LinkedHashSet<Method>` for `aliases` to make `.contains()`
O(1) while preserving insertion order (order matters for alias resolution):
```java
private void processAliases() {
Set<Method> aliases = new LinkedHashSet<>(); // was: List<Method> aliases = new ArrayList<>();
for (int i = 0; i < this.attributes.size(); i++) {
aliases.clear();
aliases.add(this.attributes.get(i));
collectAliases(aliases);
if (aliases.size() > 1) {
processAliases(i, aliases);
}
}
}
```
The `processAliases(int, List<Method>)` signature must also accept `Collection<Method>`
or `Set<Method>` (or keep `List<Method>` and pass `new ArrayList<>(aliases)`).
Similarly update `getFirstRootAttributeIndex()` and `MirrorSets.updateFrom()` parameter
types to accept `Collection<Method>`.
## Speedup
| A (attributes) | D (depth) | L (alias list) | Before (ops) | After (ops) | Speedup |
|---------------|-----------|---------------|-------------|-------------|---------|
| 10 | 5 | 5 | 2,500 | 500 | 5× |
| 20 | 8 | 10 | 32,000 | 4,000 | 8× |
| 30 | 10 | 15 | 135,000 | 9,000 | 15× |
Annotation types are cached after first construction, so this is a startup / first-use
cost rather than per-request. Applications with many composed annotations (Spring Boot,
Spring Security, Spring Data) construct many such mappings during startup.

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@ -1,20 +1,19 @@
# CLEAN — Apache Thrift
Scanned 2026-03-29 for CWE-407.
# CLEAN — Apache Thrift (Java)
Scanned 2026-03-29 for CWE-407 (algorithmic complexity).
## Scope
- `lib/java/src/main/java` — Java runtime library (PartialThriftComparer, TBase implementations)
- `compiler/cpp/src/thrift/parse/` — C++ IDL compiler (t_scope.h, t_program.h, t_const_value.h)
Library: lib/java/src — TBinaryProtocol, TCompactProtocol, TJSONProtocol, partial Thrift
comparer, service processor infrastructure.
## Findings
| Location | Pattern | Type | Result |
|----------|---------|------|--------|
| `PartialThriftComparer.areEqual` (Set path) | `s2.contains(e1)` in loop over s1 | `s2` is `Set<Object>` (Java Set semantics per Thrift spec) | CLEAN |
| `t_scope.h` | `types_.find`, `services_.find`, `constants_.find` | `std::map` — O(log N) | CLEAN |
| `t_program.h` | namespace lookups | `std::map` | CLEAN |
| `contrib/thrift-maven-plugin` | `thriftPathElements.contains` | Called once per directory during classpath building, not in hot loop | LOW |
### partial/PartialThriftComparer — s2.contains()
`s2` is cast from parameter `Object o2` and the cast target is `Set<Object>`:
```java
Set<Object> s2 = (Set<Object>) o2;
if (!s2.contains(e1)) { ... }
```
O(1) set membership. Clean.
The Java library is minimal and the C++ compiler uses `std::map` (ordered map, O(log N) find). No quadratic list-membership pattern exists in the production hot path.
**Result: No actionable CWE-407 defects.**
## Result
**CLEAN. No actionable CWE-407 defects found in Apache Thrift (Java library).**

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# CLEAN — Tor Anonymity Network
Scanned 2026-03-29 for CWE-407 (algorithmic complexity: O(N²) linear membership tests, O(2^D) diamond recursion).
# CLEAN — Tor Anonymity Network (beyond tor-0001/0002/0003)
Scanned 2026-03-29 for additional CWE-407 defects beyond existing patches.
## Scope
- `src/feature/client/entrynodes.c` — guard node selection, sampled/confirmed guard lists
- `src/feature/client/circpathbias.c` — circuit path bias tracking
- `src/feature/nodelist/node_select.c` — node selection with exclusion lists
- `src/feature/nodelist/nodelist.c` — family membership, `nodes_have_common_family_id`
- `src/feature/nodelist/routerlist.c` — router descriptor ingestion
- `src/feature/hs/hs_service.c` — hidden service hsdir tracking
- `src/feature/relay/dns.c` — DNS wildcard detection
## Existing Defects (already patched)
- `tor-0001``router_load_routers_from_string` requested_fingerprints smartlist O(R²) → digestmap
- `tor-0002``nodes_have_common_family_id` family ID string scan → strmap
- `tor-0003` — KIST scheduler re-add heap index O(N) → O(1)
## Additional Areas Scanned
- `src/feature/client/entrynodes.c` — guard selection, sampled/confirmed guard lists
- `src/feature/nodelist/node_select.c` — node exclusion via bitarray (already O(N))
- `src/feature/hs/hs_service.c` — previous_hsdirs tracking (bounded ≤6 entries)
- `src/feature/relay/dns.c` — dns_wildcard_list scan (bounded ≤10 entries)
- `src/feature/client/circpathbias.c` — circuit list scan (one-off at circuit close)
## Findings
- **`nodelist_subtract`** (`node_select.c:890`) — explicitly noted in comments as "delivers linear performance when smartlist_subtract would be quadratic." Uses `bitarray_t` indexed by `node->nodelist_idx`. O(N+M). CLEAN.
- **`nodes_have_common_family_id`** (`nodelist.c:2190`) — O(|ids_a| × |ids_b|) nested loop over family certificate IDs. Both lists are tiny (typically 13 IDs per relay). Outer loop in `nodelist_add_node_and_family` iterates all ~7000 relays but inner product is O(F²) where F≪1. Not a scalable O(N²). CLEAN.
- **`entrynodes.c` guard lists** — `smartlist_contains` on `primary_entry_guards` and `confirmed_entry_guards`: bounded by `MAX_SAMPLE_THRESHOLD` (dozens), called in setup/error paths (BUG assertions), not hot per-circuit. CLEAN.
- **`hs_service.c` `previous_hsdirs`** — `smartlist_contains_string` on a list bounded by `REND_NUMBER_OF_CONSECUTIVE_REPLICAS` (6). CLEAN.
- **`dns.c` `dns_wildcard_list`** — linear scan on a list of hijacked IPs. In practice contains 010 entries; called once per DNS response. CLEAN.
- **Router descriptor ingestion**`requested_fingerprints` shrinks as each router is processed (O(N) total). CLEAN.
- **`nodelist_subtract`** — already uses `bitarray_t` for O(N) subtraction. CLEAN.
- **`entrynodes.c` guard BUG-checks** — constant-bounded (MAX_SAMPLE_THRESHOLD dozens). CLEAN.
- **`hs_service.c` previous_hsdirs** — bounded by `REND_NUMBER_OF_CONSECUTIVE_REPLICAS` (6). CLEAN.
- **`dns.c` wildcard list** — bounded to ~10 hijacked IPs. CLEAN.
**Result: No actionable CWE-407 defects. Tor's hot node-selection paths use bitarray-indexed O(N) exclusion; all family/guard list scans operate on constant-bounded collections.**
**Result: No additional CWE-407 defects beyond existing patches.**

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# UNDF: UNDF-2026-000000560
# UNDF: (pending)
# trino-0001: StatementAnalyzer JOIN USING — O(C×J) ArrayList.contains for field dedup
## CWE-407 — Algorithmic Complexity
| Field | Value |
|-------|-------|
| ID | trino-0001 |
| Severity | MEDIUM |
| Ecosystem | trino |
| Package | trino-main |
| File | `core/trino-main/src/main/java/io/trino/sql/analyzer/StatementAnalyzer.java` |
| Lines | 39754030 |
| Complexity | O(C×J) |
| Hot path | Called for every SQL JOIN ... USING (...) query during analysis |
## Defect
When analyzing a `JOIN ... USING (col1, col2, ...)` clause, two `ArrayList<Integer>` lists
(`leftJoinFields`, `rightJoinFields`) are built from the USING column indices, then used as
membership test targets in loops over all fields of the left and right relation types:
```java
List<Integer> leftJoinFields = new ArrayList<>();
List<Integer> rightJoinFields = new ArrayList<>();
// build phase: O(J)
for (Identifier column : columns) {
leftJoinFields.add(leftField.getRelationFieldIndex());
rightJoinFields.add(rightField.getRelationFieldIndex());
}
// output phase: O(C × J) -- for each field, scan the list
for (int i = 0; i < left.getRelationType().getAllFieldCount(); i++) {
if (!leftJoinFields.contains(i)) { // O(J) linear scan per field
outputs.add(...); leftFields.add(i);
}
}
for (int i = 0; i < right.getRelationType().getAllFieldCount(); i++) {
if (!rightJoinFields.contains(i)) { // O(J) linear scan per field
outputs.add(...); rightFields.add(i);
}
}
```
Where C = total column count across both sides, J = number of USING columns. For wide tables
(C large) with many join keys (J large), this degrades to O(C²) in the worst case.
## Fix
Replace `ArrayList<Integer>` with `HashSet<Integer>` for O(1) membership lookup. The lists are
only used for contains checks in the output phase; the ordering is not required for that.
```java
Set<Integer> leftJoinFields = new HashSet<>();
Set<Integer> rightJoinFields = new HashSet<>();
// build phase
for (Identifier column : columns) {
leftJoinFields.add(leftField.getRelationFieldIndex());
rightJoinFields.add(rightField.getRelationFieldIndex());
joinFields.add(Field.newUnqualified(column.getValue(), type.get()));
// ... other logic unchanged
}
// output phase: O(C) total
for (int i = 0; i < left.getRelationType().getAllFieldCount(); i++) {
if (!leftJoinFields.contains(i)) { // O(1) hash lookup
outputs.add(left.getRelationType().getFieldByIndex(i));
leftFields.add(i);
}
}
for (int i = 0; i < right.getRelationType().getAllFieldCount(); i++) {
if (!rightJoinFields.contains(i)) { // O(1) hash lookup
outputs.add(right.getRelationType().getFieldByIndex(i));
rightFields.add(i);
}
}
// Pass sets to JoinUsingAnalysis (also accepts Collection<Integer>)
analysis.setJoinUsing(node, new Analysis.JoinUsingAnalysis(
ImmutableList.copyOf(leftJoinFields), ImmutableList.copyOf(rightJoinFields),
leftFields.build(), rightFields.build()));
```
## Speedup
| C (columns) | J (join keys) | Before (ops) | After (ops) | Speedup |
|-------------|--------------|-------------|-------------|---------|
| 50 | 5 | 250 | 50 | 5× |
| 200 | 20 | 4,000 | 200 | 20× |
| 500 | 50 | 25,000 | 500 | 50× |
| 1,000 | 100 | 100,000 | 1,000 | 100× |

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# UNDF: UNDF-2026-000000233
# UNDF: (pending)
# vertx-core-0001: HAManager.nodeLeft — O(N×M) nodes List.contains inside clusterMap loop
## CWE-407 — Algorithmic Complexity: Unnecessary Quadratic Complexity (List membership inside loop)
| Field | Value |
|-------|-------|
| ID | vertx-core-0001 |
| Severity | HIGH |
| Ecosystem | vertx-core |
| Package | io.vertx.core.impl |
| File | `vertx-core/src/main/java/io/vertx/core/impl/HAManager.java` |
| Lines | 307314 |
| Complexity | O(N×M) |
| Hot path | every cluster node departure event |
## Defect
`HAManager.nodeLeft()` is called whenever a node leaves a Vert.x cluster. It
resumes any prior failed failovers by scanning `clusterMap` for entries not in
the current live node list. The live node list is obtained from
`clusterManager.getNodes()` which returns a `List<String>`. For each of the N
entries in `clusterMap`, it calls `nodes.contains(entry.getKey())` — an O(M)
linear scan of the node list. With N cluster-map entries and M live nodes the
total cost is O(N×M) per node-departure event.
```java
// HAManager.java line 307-314
List<String> nodes = clusterManager.getNodes(); // returns List<String>
for (Map.Entry<String, String> entry: clusterMap.entrySet()) {
if (!leftNodeID.equals(entry.getKey()) && !nodes.contains(entry.getKey())) {
// ^^^^^^^^ O(M) per iteration
JsonObject haInfo = new JsonObject(entry.getValue());
checkFailover(entry.getKey(), haInfo);
}
}
```
The same pattern appears in `addHaInfoIfLost()` (line 319):
```java
if (clusterManager.getNodes().contains(nodeID) && ...) // O(M) single call, low risk
```
## Fix
Convert the node list to a `HashSet` before the loop so membership checks are O(1).
```java
Set<String> nodesSet = new HashSet<>(clusterManager.getNodes());
for (Map.Entry<String, String> entry: clusterMap.entrySet()) {
if (!leftNodeID.equals(entry.getKey()) && !nodesSet.contains(entry.getKey())) {
JsonObject haInfo = new JsonObject(entry.getValue());
checkFailover(entry.getKey(), haInfo);
}
}
```
For `addHaInfoIfLost()` the single call is not in a loop so is low risk — but can be converted similarly if consistency is desired.
## Speedup
| N (clusterMap entries) | M (nodes) | Before (ops) | After (ops) | Speedup |
|------------------------|-----------|-------------|-------------|---------|
| 100 | 100 | 10,000 | 100 | 100× |
| 500 | 500 | 250,000 | 500 | 500× |
| 1,000 | 1,000 | 1,000,000 | 1,000 | 1,000× |
In large Vert.x HA clusters with many concurrent deployments the quadratic
cost is paid on every node failure event — exactly when latency matters most
for failover speed.