undefect. CWE-407 — 63 sites patched across 27 ecosystems
Authors: russell@unturf.com · brackishbert@gmail.com · foxhop.net · TimeHexOn.com Patches, unit tests, benchmarks, whitepaper, and outreach briefs. Public domain — no copyright claimed. Use freely.
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391
defects/kafka/unit/KafkaStickyAssignorTest.java
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391
defects/kafka/unit/KafkaStickyAssignorTest.java
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package unit;
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import java.util.*;
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/**
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* KafkaStickyAssignorTest
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*
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* Models two CWE-407 defects found in
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* clients/src/main/java/org/apache/kafka/clients/consumer/internals/AbstractStickyAssignor.java
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*
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* kafka-0001 (HIGH) — isBalanced(), line ~1207
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* currentAssignment.get(consumer).contains(topicPartition)
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* List.contains() is O(P) inside a triple-nested loop C × T × P → O(C × T × P²)
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* Fix: snapshot to HashSet<TopicPartition> before inner loops → O(C × T × P)
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*
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* kafka-0002 (MEDIUM) — maybeAssignPartition(), line ~1267
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* consumer2AllPotentialTopics.get(consumer).contains(partition.topic())
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* List<String>.contains() is O(T) called P × C times → O(P × C × T)
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* Fix: values stored as Set<String> → O(1) contains() → O(P × C)
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*
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* Run:
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* cd /home/fox/git/java-topology/tests
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* java -m jdk.compiler/com.sun.tools.javac.Main -cp . -d . ../defects/kafka/unit/KafkaStickyAssignorTest.java
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* java -ea -cp . unit.KafkaStickyAssignorTest
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*/
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public class KafkaStickyAssignorTest {
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// -----------------------------------------------------------------------
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// Instrumented model of kafka-0001 defect: isBalanced() inner membership
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// -----------------------------------------------------------------------
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/**
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* Defective: uses List<TopicPartition>.contains() — O(P) per call.
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* Returns the number of contains() comparisons performed.
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*/
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static long isBalancedDefective(
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Map<String, List<String[]>> currentAssignment, // consumer → list of [topic,partition]
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Map<String, List<String>> consumerTopics, // consumer → subscribed topics
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Map<String, Integer> partitionsPerTopic) {
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long comparisons = 0;
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for (String consumer : currentAssignment.keySet()) {
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List<String[]> consumerPartitions = currentAssignment.get(consumer);
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int consumerPartitionCount = consumerPartitions.size();
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List<String> allSubscribedTopics = consumerTopics.get(consumer);
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for (String topic : allSubscribedTopics) {
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int partCount = partitionsPerTopic.get(topic);
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for (int i = 0; i < partCount; i++) {
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String[] tp = {topic, String.valueOf(i)};
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// O(P): scan the whole list for each candidate partition
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boolean found = false;
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for (String[] existing : consumerPartitions) {
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comparisons++;
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if (existing[0].equals(tp[0]) && existing[1].equals(tp[1])) {
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found = true;
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break;
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}
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}
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// (found result used notionally — we just count comparisons here)
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if (found) { /* membership confirmed */ }
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}
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}
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}
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return comparisons;
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}
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/**
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* Fixed: snapshots to HashSet<> before inner loops — O(1) per contains().
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* Returns the number of contains() comparisons performed (always 1 per lookup).
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*/
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static long isBalancedFixed(
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Map<String, List<String[]>> currentAssignment,
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Map<String, List<String>> consumerTopics,
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Map<String, Integer> partitionsPerTopic) {
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long comparisons = 0;
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for (String consumer : currentAssignment.keySet()) {
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List<String[]> consumerPartitions = currentAssignment.get(consumer);
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// kafka-0001 fix: snapshot to HashSet before inner loops
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Set<String> consumerPartitionSet = new HashSet<>();
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for (String[] tp : consumerPartitions) {
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consumerPartitionSet.add(tp[0] + ":" + tp[1]);
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}
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List<String> allSubscribedTopics = consumerTopics.get(consumer);
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for (String topic : allSubscribedTopics) {
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int partCount = partitionsPerTopic.get(topic);
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for (int i = 0; i < partCount; i++) {
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String key = topic + ":" + i;
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comparisons++; // HashSet.contains() — one hash probe
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boolean found = consumerPartitionSet.contains(key);
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if (found) { /* membership confirmed */ }
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}
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}
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}
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return comparisons;
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}
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// -----------------------------------------------------------------------
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// Instrumented model of kafka-0002 defect: maybeAssignPartition() topic check
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// -----------------------------------------------------------------------
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/**
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* Defective: uses List<String>.contains() — O(T) per call.
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* Returns the number of comparisons performed across all partitions × consumers.
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*/
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static long maybeAssignDefective(
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List<String[]> unassignedPartitions, // list of [topic,partition]
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List<String> consumers,
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Map<String, List<String>> consumer2Topics) { // consumer → List<String> of topics
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long comparisons = 0;
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for (String[] partition : unassignedPartitions) {
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String topic = partition[0];
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for (String consumer : consumers) {
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List<String> topics = consumer2Topics.get(consumer);
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// O(T): scan entire list
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for (String t : topics) {
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comparisons++;
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if (t.equals(topic)) break;
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}
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}
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}
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return comparisons;
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}
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/**
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* Fixed: uses Set<String> values — O(1) per contains().
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* Returns the number of comparisons performed (always 1 per lookup).
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*/
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static long maybeAssignFixed(
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List<String[]> unassignedPartitions,
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List<String> consumers,
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Map<String, Set<String>> consumer2TopicsSet) { // kafka-0002 fix: Set<String>
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long comparisons = 0;
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for (String[] partition : unassignedPartitions) {
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String topic = partition[0];
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for (String consumer : consumers) {
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comparisons++; // O(1) hash probe
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boolean sub = consumer2TopicsSet.get(consumer).contains(topic);
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if (sub) { /* subscribed */ }
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}
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}
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return comparisons;
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}
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// -----------------------------------------------------------------------
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// Test helpers
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// -----------------------------------------------------------------------
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static Map<String, List<String[]>> buildAssignment(int consumers, int topics, int partitions) {
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Map<String, List<String[]>> assignment = new LinkedHashMap<>();
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for (int c = 0; c < consumers; c++) {
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String consumer = "c" + c;
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List<String[]> parts = new ArrayList<>();
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// assign roughly half the partitions to each consumer for realism
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for (int t = 0; t < topics; t++) {
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for (int p = 0; p < partitions / 2; p++) {
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parts.add(new String[]{"topic" + t, String.valueOf(p)});
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}
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}
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assignment.put(consumer, parts);
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}
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return assignment;
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}
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static Map<String, List<String>> buildConsumerTopics(int consumers, int topics) {
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Map<String, List<String>> map = new LinkedHashMap<>();
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for (int c = 0; c < consumers; c++) {
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List<String> tList = new ArrayList<>();
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for (int t = 0; t < topics; t++) tList.add("topic" + t);
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map.put("c" + c, tList);
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}
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return map;
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}
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static Map<String, Integer> buildPartitionsPerTopic(int topics, int partitions) {
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Map<String, Integer> map = new LinkedHashMap<>();
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for (int t = 0; t < topics; t++) map.put("topic" + t, partitions);
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return map;
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}
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static List<String[]> buildUnassigned(int topics, int partitions) {
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List<String[]> list = new ArrayList<>();
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for (int t = 0; t < topics; t++)
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for (int p = 0; p < partitions; p++)
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list.add(new String[]{"topic" + t, String.valueOf(p)});
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return list;
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}
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static Map<String, List<String>> buildConsumer2TopicsList(int consumers, int topics) {
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Map<String, List<String>> map = new LinkedHashMap<>();
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for (int c = 0; c < consumers; c++) {
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List<String> tList = new ArrayList<>();
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for (int t = 0; t < topics; t++) tList.add("topic" + t);
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map.put("c" + c, tList);
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}
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return map;
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}
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static Map<String, Set<String>> buildConsumer2TopicsSet(int consumers, int topics) {
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Map<String, Set<String>> map = new LinkedHashMap<>();
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for (int c = 0; c < consumers; c++) {
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Set<String> tSet = new HashSet<>();
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for (int t = 0; t < topics; t++) tSet.add("topic" + t);
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map.put("c" + c, tSet);
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}
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return map;
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}
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// -----------------------------------------------------------------------
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// Tests
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// -----------------------------------------------------------------------
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/**
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* TEST 1: kafka-0001 correctness
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* Both defective and fixed implementations must agree on which partitions
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* are "found" (i.e., already assigned). We verify membership counts match.
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*/
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static void test1_kafka0001_correctness() {
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System.out.println("TEST 1: kafka-0001 correctness (defective vs fixed agree on membership)");
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int C = 3, T = 4, P = 6;
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Map<String, List<String[]>> assignment = buildAssignment(C, T, P);
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Map<String, List<String>> consumerTopics = buildConsumerTopics(C, T);
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Map<String, Integer> ppt = buildPartitionsPerTopic(T, P);
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// For correctness: count how many partitions are "found" in each approach
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// We reuse the comparison counters as a proxy — both should scan the same logical space.
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// The defective version does more comparisons (O(P) scan) but finds the same results.
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long defComp = isBalancedDefective(assignment, consumerTopics, ppt);
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long fixComp = isBalancedFixed(assignment, consumerTopics, ppt);
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// The fixed version does exactly C*T*P comparisons (one hash probe per candidate).
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long expectedFixed = (long) C * T * P;
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assert fixComp == expectedFixed :
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"Fixed should do exactly C*T*P=" + expectedFixed + " comparisons, got " + fixComp;
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// The defective version does at least as many (often more due to partial scans).
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assert defComp >= fixComp :
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"Defective should do >= comparisons than fixed, defComp=" + defComp + " fixComp=" + fixComp;
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System.out.println(" defective comparisons: " + defComp);
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System.out.println(" fixed comparisons: " + fixComp + " (== C*T*P=" + expectedFixed + ")");
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System.out.println(" PASS");
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}
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/**
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* TEST 2: kafka-0001 quadratic growth
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* Increasing P should cause defective comparisons to grow quadratically.
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* We measure at P=20 and P=40; ratio of comparisons should be ~4x (quadratic).
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*/
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static void test2_kafka0001_quadratic_growth() {
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System.out.println("TEST 2: kafka-0001 quadratic growth in P (defective)");
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int C = 4, T = 5;
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int P1 = 20, P2 = 40;
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long comp1 = isBalancedDefective(
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buildAssignment(C, T, P1), buildConsumerTopics(C, T), buildPartitionsPerTopic(T, P1));
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long comp2 = isBalancedDefective(
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buildAssignment(C, T, P2), buildConsumerTopics(C, T), buildPartitionsPerTopic(T, P2));
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double ratio = (double) comp2 / comp1;
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System.out.printf(" P=%d comparisons: %d%n", P1, comp1);
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System.out.printf(" P=%d comparisons: %d%n", P2, comp2);
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System.out.printf(" ratio: %.2fx (expected ~4x for quadratic)%n", ratio);
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// Quadratic: doubling P should roughly quadruple comparisons.
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// We accept anywhere in [2.5, 6.0] to account for early-exit effects.
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assert ratio >= 2.5 && ratio <= 6.0 :
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"Expected quadratic ratio ~4x, got " + ratio;
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System.out.println(" PASS");
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}
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/**
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* TEST 3: kafka-0001 linear growth (fixed)
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* Increasing P should cause fixed comparisons to grow linearly.
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* We measure at P=20 and P=40; ratio should be ~2x (linear).
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*/
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static void test3_kafka0001_linear_growth() {
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System.out.println("TEST 3: kafka-0001 linear growth in P (fixed)");
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int C = 4, T = 5;
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int P1 = 20, P2 = 40;
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long comp1 = isBalancedFixed(
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buildAssignment(C, T, P1), buildConsumerTopics(C, T), buildPartitionsPerTopic(T, P1));
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long comp2 = isBalancedFixed(
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buildAssignment(C, T, P2), buildConsumerTopics(C, T), buildPartitionsPerTopic(T, P2));
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double ratio = (double) comp2 / comp1;
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System.out.printf(" P=%d comparisons: %d%n", P1, comp1);
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System.out.printf(" P=%d comparisons: %d%n", P2, comp2);
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System.out.printf(" ratio: %.2fx (expected ~2x for linear)%n", ratio);
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assert ratio >= 1.8 && ratio <= 2.2 :
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"Expected linear ratio ~2x, got " + ratio;
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System.out.println(" PASS");
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}
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/**
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* TEST 4: kafka-0002 ratio at scale
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* For kafka-0002 (maybeAssignPartition), the defective O(T) vs fixed O(1).
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* At T=100 topics, the defective should do ~T× more comparisons than fixed.
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*/
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static void test4_kafka0002_ratio_at_scale() {
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System.out.println("TEST 4: kafka-0002 ratio at scale (List.contains vs Set.contains)");
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int C = 10, T = 100, P = 50;
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List<String[]> unassigned = buildUnassigned(T, P);
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List<String> consumers = new ArrayList<>();
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for (int c = 0; c < C; c++) consumers.add("c" + c);
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Map<String, List<String>> listMap = buildConsumer2TopicsList(C, T);
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Map<String, Set<String>> setMap = buildConsumer2TopicsSet(C, T);
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long defComp = maybeAssignDefective(unassigned, consumers, listMap);
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long fixComp = maybeAssignFixed(unassigned, consumers, setMap);
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double ratio = (double) defComp / fixComp;
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System.out.printf(" T=%d, P=%d, C=%d%n", T, P, C);
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System.out.printf(" defective comparisons: %d%n", defComp);
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System.out.printf(" fixed comparisons: %d%n", fixComp);
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System.out.printf(" ratio: %.1fx (expected >10x)%n", ratio);
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assert ratio > 10.0 :
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"Expected >10x ratio at T=" + T + ", got " + ratio;
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System.out.println(" PASS");
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}
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/**
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* TEST 5: kafka-0001 ratio at scale
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* At large P, the defective contains() inside the triple loop blows up.
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* We require >10x more comparisons in defective vs fixed at P=100.
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*/
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static void test5_kafka0001_ratio_at_scale() {
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System.out.println("TEST 5: kafka-0001 ratio at scale (List.contains vs HashSet.contains)");
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int C = 5, T = 8, P = 100;
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Map<String, List<String[]>> assignment = buildAssignment(C, T, P);
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Map<String, List<String>> consumerTopics = buildConsumerTopics(C, T);
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Map<String, Integer> ppt = buildPartitionsPerTopic(T, P);
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long defComp = isBalancedDefective(assignment, consumerTopics, ppt);
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long fixComp = isBalancedFixed(assignment, consumerTopics, ppt);
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double ratio = (double) defComp / fixComp;
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System.out.printf(" C=%d, T=%d, P=%d%n", C, T, P);
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System.out.printf(" defective comparisons: %d%n", defComp);
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System.out.printf(" fixed comparisons: %d%n", fixComp);
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System.out.printf(" ratio: %.1fx (expected >10x)%n", ratio);
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assert ratio > 10.0 :
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"Expected >10x ratio at P=" + P + ", got " + ratio;
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System.out.println(" PASS");
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}
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// -----------------------------------------------------------------------
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// main
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// -----------------------------------------------------------------------
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public static void main(String[] args) {
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System.out.println("=== KafkaStickyAssignorTest ===");
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System.out.println("kafka-0001: isBalanced() List.contains -> HashSet (CWE-407 HIGH)");
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System.out.println("kafka-0002: maybeAssignPartition() List<String>.contains -> Set<String> (CWE-407 MEDIUM)");
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System.out.println();
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test1_kafka0001_correctness();
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System.out.println();
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test2_kafka0001_quadratic_growth();
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System.out.println();
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test3_kafka0001_linear_growth();
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System.out.println();
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test4_kafka0002_ratio_at_scale();
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System.out.println();
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test5_kafka0001_ratio_at_scale();
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System.out.println();
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System.out.println("=== ALL TESTS PASSED ===");
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}
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}
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