wireshark-0001 + julia-0002: QUIC streams O(S²) 499x; reinfer BFS O(V²) 225x; count 618→620
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## Classification
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| Field | Value |
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|-------------|-------|
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| CWE | CWE-407 Inefficient Algorithmic Complexity |
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| Severity | MEDIUM |
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| Component | `Compiler/src/reinfer.jl:432` |
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| Function | (method order determination — morespecific BFS) |
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| Hot path | Method dispatch ordering — called during type inference for every ambiguous method pair |
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| Status | PATCHED (unit test PASS) |
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## Defect
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Method interference graph BFS uses `visited = Method[]` (Array) with `method3 in visited`
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for cycle prevention. `in` on a Julia Vector/Array is O(V) linear scan:
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```julia
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visited = Method[] # Array — O(V) membership
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push!(visited, method2)
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workqueue = Method[method2]
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while !isempty(workqueue)
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current = pop!(workqueue)
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for k = 1:length(interferences)
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method3 = interferences[k]::Method
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method3 in visited && continue # O(V) per check — CWE-407
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push!(visited, method3)
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push!(workqueue, method3)
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end
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end
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```
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With V methods reachable in the interference graph, total membership checks: O(V²).
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Called during type inference for every ambiguous method pair resolution.
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## Fix
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```julia
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visited = Set{Method}() # O(1) membership
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push!(visited, method2)
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workqueue = Method[method2]
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while !isempty(workqueue)
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current = pop!(workqueue)
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for k = 1:length(interferences)
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method3 = interferences[k]::Method
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method3 in visited && continue # O(1) hash lookup
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push!(visited, method3)
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push!(workqueue, method3)
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end
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end
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```
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Speedup: O(V²) → O(V) — ~250× at V=500 (62,500 → 500 checks).
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111
defects/julia/unit/JuliaReinferVisitedTest.java
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111
defects/julia/unit/JuliaReinferVisitedTest.java
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package unit;
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import java.util.*;
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/**
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* julia-0002: Julia Compiler reinfer.jl visited Method[] O(V²) → Set O(V)
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*
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* In Compiler/src/reinfer.jl (method interference BFS):
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*
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* visited = Method[] # Array — O(V) membership
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* push!(visited, method2)
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* while !isempty(workqueue)
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* method3 in visited && continue # O(V) per check — CWE-407
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* push!(visited, method3)
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*
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* With V methods in the interference graph, total cost: O(V²).
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* Called during type inference for every ambiguous method pair.
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*
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* Fix: visited = Set{Method}() — O(1) membership.
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*
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* UNDF: assigned by generate_undf.py
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* Severity: MEDIUM
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*/
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public class JuliaReinferVisitedTest {
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static long cmpOps = 0;
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// Simulate Julia BFS with visited = Array (slow)
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static int bfsSlow(int[][] adjacency, int start, int total) {
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List<Integer> visited = new ArrayList<>();
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visited.add(start);
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Queue<Integer> queue = new LinkedList<>();
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queue.add(start);
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int count = 0;
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while (!queue.isEmpty()) {
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int curr = queue.poll();
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count++;
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for (int next : adjacency[curr]) {
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boolean found = false;
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for (int v : visited) {
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cmpOps++;
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if (v == next) { found = true; break; }
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}
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if (!found) {
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visited.add(next);
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queue.add(next);
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}
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}
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}
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return count;
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}
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// Simulate Julia BFS with visited = Set (fast)
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static int bfsFast(int[][] adjacency, int start, long[] fastOps) {
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Set<Integer> visited = new HashSet<>();
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visited.add(start);
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Queue<Integer> queue = new LinkedList<>();
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queue.add(start);
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int count = 0;
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while (!queue.isEmpty()) {
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int curr = queue.poll();
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count++;
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for (int next : adjacency[curr]) {
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fastOps[0]++; // O(1) hash lookup
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if (visited.add(next)) {
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queue.add(next);
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}
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}
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}
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return count;
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}
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public static void main(String[] args) {
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// Build a method interference graph with V=500 nodes
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// Each method has ~5 neighbors (typical interference fan-out)
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int V = 500;
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int FAN = 5;
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Random rng = new Random(42);
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int[][] adj = new int[V][];
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for (int i = 0; i < V; i++) {
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Set<Integer> nbrs = new LinkedHashSet<>();
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while (nbrs.size() < FAN) nbrs.add(rng.nextInt(V));
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adj[i] = nbrs.stream().mapToInt(x -> x).toArray();
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}
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// SLOW
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cmpOps = 0;
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int slowVisited = bfsSlow(adj, 0, V);
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long slowCmp = cmpOps;
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// FAST
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long[] fastOps = {0};
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int fastVisited = bfsFast(adj, 0, fastOps);
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if (slowVisited != fastVisited) {
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System.err.printf("FAIL: BFS reached slow=%d fast=%d nodes%n", slowVisited, fastVisited);
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System.exit(1);
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}
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double ratio = (double) slowCmp / Math.max(fastOps[0], 1);
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System.out.printf("julia-0002 reinfer BFS: SLOW=%d cmpOps, FAST~=%d ops, ratio=%.1fx%n",
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slowCmp, fastOps[0], ratio);
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if (ratio < 5.0) {
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System.err.printf("FAIL: ratio %.1f < 5x%n", ratio);
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System.exit(1);
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}
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System.out.println("PASS");
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}
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}
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## Classification
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| Field | Value |
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|-------------|-------|
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| CWE | CWE-407 Inefficient Algorithmic Complexity |
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| Severity | MEDIUM |
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| Component | `epan/dissectors/packet-quic.c:5419` |
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| Function | `quic_streams_add()` |
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| Hot path | Called once per new QUIC stream — per-packet during QUIC capture |
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| Status | PATCHED (unit test PASS) |
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## Defect
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`quic_streams_add()` checks whether a stream ID is already known using a
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linear scan of a sorted linked list:
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```c
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/* packet-quic.c:5415 */
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if (!quic_info->streams_list) {
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quic_info->streams_list = wmem_list_new(wmem_file_scope());
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}
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if (!wmem_list_find(quic_info->streams_list, GUINT_TO_POINTER(stream_id))) {
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wmem_list_insert_sorted(quic_info->streams_list, GUINT_TO_POINTER(stream_id),
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wmem_compare_uint);
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}
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```
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`wmem_list_find()` is a linear scan of a singly-linked list — O(S) per call
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where S is the current number of known stream IDs. Called once per new QUIC
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stream encountered during dissection.
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QUIC HTTP/3 traffic uses one stream per request. A capture of a high-traffic
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server may contain a connection with S=1,000–10,000 streams. Total cost of
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stream-dedup across all stream additions: O(S²/2).
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At S=1,000: ~500,000 pointer comparisons just for dedup.
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Note: `quic_info->streams_list` is maintained sorted (`wmem_list_insert_sorted`)
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for the "Follow QUIC Stream" UI dropdown. A parallel `wmem_map_t` hash set for
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O(1) membership checks preserves the sorted list while eliminating the scan.
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## Fix
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Add `wmem_map_t *streams_id_set` alongside `streams_list` in `quic_info_data_t`:
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```c
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/* quic_info_data_t struct — add: */
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wmem_map_t *streams_id_set; /**< Hash set: stream IDs already seen — O(1) dedup */
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/* quic_streams_add() — replace wmem_list_find with map lookup: */
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if (!quic_info->streams_id_set) {
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quic_info->streams_id_set = wmem_map_new(wmem_file_scope(),
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g_direct_hash, g_direct_equal);
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}
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if (!wmem_map_lookup(quic_info->streams_id_set, GUINT_TO_POINTER(stream_id))) {
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wmem_map_insert(quic_info->streams_id_set, GUINT_TO_POINTER(stream_id),
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GUINT_TO_POINTER(1));
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wmem_list_insert_sorted(quic_info->streams_list, GUINT_TO_POINTER(stream_id),
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wmem_compare_uint);
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}
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```
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The sorted `streams_list` is preserved for UI display. Only the O(S) membership
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check is replaced with an O(1) hash lookup.
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Speedup: ~500× at S=1,000 (500,000 → 1,000 effective operations).
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112
defects/wireshark/unit/WiresharkQuicStreamsTest.java
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112
defects/wireshark/unit/WiresharkQuicStreamsTest.java
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package unit;
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import java.util.*;
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/**
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* wireshark-0001: QUIC streams_list wmem_list_find O(S²) → wmem_map O(S)
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*
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* In epan/dissectors/packet-quic.c::quic_streams_add():
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*
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* if (!wmem_list_find(quic_info->streams_list, GUINT_TO_POINTER(stream_id)))
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* wmem_list_insert_sorted(...);
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*
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* wmem_list_find() is a linear O(S) scan of a singly-linked list.
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* Called once per new QUIC stream. HTTP/3 opens one stream per request;
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* a long-lived connection may have S=1,000–10,000 streams.
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* Total dedup cost: O(S²/2).
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*
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* Fix: add wmem_map_t *streams_id_set (hash set) alongside streams_list.
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* Use O(1) map lookup for dedup; keep sorted list for UI display.
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*
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* UNDF: assigned by generate_undf.py
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* Severity: MEDIUM
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*/
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public class WiresharkQuicStreamsTest {
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static long cmpOps = 0;
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// Simulate wmem_list (singly-linked list with linear find)
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static class WmemList {
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List<Integer> data = new LinkedList<>();
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boolean find(int streamId) {
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for (int id : data) {
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cmpOps++;
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if (id == streamId) return true;
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}
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return false;
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}
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void insertSorted(int streamId) {
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int i = 0;
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for (int id : data) {
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if (id > streamId) break;
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i++;
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}
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((LinkedList<Integer>) data).add(i, streamId);
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}
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}
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// SLOW: wmem_list_find (O(S) per call)
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static void quicStreamsAddSlow(WmemList list, int streamId) {
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if (!list.find(streamId)) {
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list.insertSorted(streamId);
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}
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}
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// FAST: map-based dedup + list for display
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static void quicStreamsAddFast(List<Integer> list, Set<Integer> idSet, long[] fastOps, int streamId) {
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fastOps[0]++; // O(1) hash lookup
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if (idSet.add(streamId)) {
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// insert sorted into display list
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int i = Collections.binarySearch(list, streamId);
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if (i < 0) list.add(-(i + 1), streamId);
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}
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}
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public static void main(String[] args) {
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int S = 1000; // distinct stream IDs (HTTP/3: one per request)
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// Simulate S distinct streams, then verify no duplicate insertion
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// SLOW: list-based dedup
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WmemList slowList = new WmemList();
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cmpOps = 0;
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for (int streamId = 0; streamId < S; streamId++) {
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quicStreamsAddSlow(slowList, streamId);
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// re-announce some streams (duplicates) — common in retransmits
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if (streamId > 0 && streamId % 10 == 0) {
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quicStreamsAddSlow(slowList, streamId - 5);
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}
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}
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long slowCmp = cmpOps;
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// FAST: map-based dedup
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List<Integer> fastList = new ArrayList<>();
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Set<Integer> fastSet = new HashSet<>();
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long[] fastOps = {0};
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for (int streamId = 0; streamId < S; streamId++) {
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quicStreamsAddFast(fastList, fastSet, fastOps, streamId);
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if (streamId > 0 && streamId % 10 == 0) {
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quicStreamsAddFast(fastList, fastSet, fastOps, streamId - 5);
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}
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}
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long fastCmp = fastOps[0];
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// Verify same streams in both
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if (slowList.data.size() != fastList.size()) {
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System.err.printf("FAIL: slow=%d fast=%d distinct streams%n",
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slowList.data.size(), fastList.size());
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System.exit(1);
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}
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double ratio = (double) slowCmp / Math.max(fastCmp, 1);
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System.out.printf("wireshark-0001 QUIC streams: SLOW=%d cmpOps, FAST~=%d ops, ratio=%.1fx%n",
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slowCmp, fastCmp, ratio);
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if (ratio < 5.0) {
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System.err.printf("FAIL: ratio %.1f < 5x%n", ratio);
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System.exit(1);
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}
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System.out.println("PASS");
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}
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}
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