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Learn open addressing in C: linear probing, quadratic probing, and double hashing. Master collision handling, tombstones, rehashing, and performance.

Open Addressing in Hashing in C: Complete Guide

Open Addressing Collision Handling Technique in Hashing in C: A Comprehensive Tutorial

Open Addressing is a collision handling technique where all elements are stored directly in the hash table itself. When a collision occurs, the algorithm probes for the next available slot in the table. Unlike chaining, no linked lists or extra nodes are used—everything lives in one contiguous array, giving excellent cache performance.

This tutorial provides an in-depth exploration of Open Addressing in C: fundamental concepts, three probing strategies (linear, quadratic, double hashing), full implementations, comparison with chaining, complexity analysis, common pitfalls, and best practices.


Conceptual Introduction & Fundamentals

What is Open Addressing?

Open Addressing (also called closed hashing) stores all elements in the hash table itself. When a collision occurs, we probe for the next slot using a probe sequence.

Key properties:

  • Table size m must be ≥ number of keys n.
  • No pointers or linked lists—everything in the table.
  • Probing finds alternate slots on collision.
  • Requires tombstones for deletion.

Why Open Addressing?

  • Cache-friendly: Everything stored contiguously.
  • Memory efficient: No pointer overhead.
  • Simple deletion: With tombstones.
  • Good for known workloads: When number of keys is predictable.

Core Operations

OperationDescription
Insert(k)Probe until an empty slot is found; insert.
Search(k)Probe until key found or empty slot reached.
Delete(k)Mark slot as DELETED (tombstone); search continues past it.

Probe Function Types

ProbingProbe SequenceClustering
Linear Probing(h(k) + i) % mPrimary
Quadratic Probing(h(k) + i²) % mSecondary
Double Hashing(h(k) + i × h2(k)) % mMinimal

Linear Probing

Sequential probing: (h(k) + 1) % m, (h(k) + 2) % m, …

  • Best cache performance.
  • Suffers from primary clustering: long contiguous runs of occupied slots.

Quadratic Probing

Probes: (h(k) + 1²) % m, (h(k) + 2²) % m, …

  • Reduces primary clustering.
  • Retains secondary clustering: keys with same initial hash follow identical probes.

Double Hashing

Probes: (h(k) + 1 × h2(k)) % m, (h(k) + 2 × h2(k)) % m, …

  • Best distribution — reduces both primary and secondary clustering.
  • Poor cache performance — jumps unpredictable.
  • Requires a second hash function that never returns 0.

Performance Analysis

For load factor α = n / m (α < 1):

OperationExpected Time
Search< 1 / (1 - α)
Insert< 1 / (1 - α)
Delete< 1 / (1 - α)

At α = 0.5, expected probes ≈ 2; at α = 0.9, expected probes ≈ 10.

Open Addressing vs. Separate Chaining

AspectOpen AddressingSeparate Chaining
Table sizeMust be ≥ nAny
CacheExcellentPoor
ClusteringYesNo
InsertSlight computationO(1) prepend
DeleteTombstones neededDirect removal
Load factorα < 1Any
Pointer overheadNonePer node
Best forKnown workloadsDynamic workloads

Syntax & Core Mechanics

Slot States

c

#define EMPTY (-1) #define DELETED (-2)

Sentinel keys mark empty and deleted slots.

Basic Structure

c

typedef struct { int *keys; int *values; int capacity; int size; int deletedCount; } HashTable;

Probe Sequences

c

/* Linear Probing */ pos = (base + i) % capacity; /* Quadratic Probing */ pos = (base + i * i) % capacity; /* Double Hashing */ pos = (base + i * h2(key)) % capacity;

Second Hash Function (Double Hashing)

Must never return 0:

c

int h2(int key, int m) { return 1 + (key % (m - 1)); /* Ensures non-zero step */ }

Load Factor Threshold

Keep α < 0.7 for good performance; rehash when exceeded.

c

double lf = (double)(size + deletedCount) / capacity; if (lf > 0.7) rehash();

Full Practical Code Example with Explanation

This program demonstrates all three probing strategies with a unified hash table.

c

/** * open_addressing.c * Complete hash table using open addressing. * Supports linear, quadratic, and double hashing. */ #include <stdio.h> #include <stdlib.h> #include <string.h> #include <errno.h> #define MAX_LINE_LEN 100 #define EMPTY (-1) #define DELETED (-2) #define REHASH_THRESHOLD 0.7 typedef enum { PROBE_LINEAR, PROBE_QUADRATIC, PROBE_DOUBLE } ProbeType; typedef struct { int *keys; int *values; int capacity; int size; int deletedCount; ProbeType probe; } HashTable; /* Next prime >= n */ static int nextPrime(int n) { if (n <= 2) return 2; if (n % 2 == 0) n++; while (1) { int isPrime = 1; for (int i = 3; i * i <= n; i += 2) { if (n % i == 0) { isPrime = 0; break; } } if (isPrime) return n; n += 2; } } /* Primary hash */ static unsigned int h1(int key, int m) { return ((unsigned int)key) % (unsigned int)m; } /* Secondary hash for double hashing (must never be 0) */ static unsigned int h2(int key, int m) { return 1u + ((unsigned int)key % (unsigned int)(m - 1)); } /* Compute probe index for iteration i */ static int probeAt(int base, int i, int key, int m, ProbeType type) { unsigned int idx; switch (type) { case PROBE_LINEAR: idx = ((unsigned int)base + (unsigned int)i) % (unsigned int)m; break; case PROBE_QUADRATIC: idx = ((unsigned int)base + (unsigned int)(i * i)) % (unsigned int)m; break; case PROBE_DOUBLE: idx = ((unsigned int)base + (unsigned int)i * h2(key, m)) % (unsigned int)m; break; default: return -1; } return (int)idx; } HashTable *createHashTable(int initialCapacity, ProbeType probe) { HashTable *ht = malloc(sizeof(HashTable)); if (ht == NULL) return NULL; int capacity = nextPrime(initialCapacity); ht->keys = malloc(capacity * sizeof(int)); ht->values = malloc(capacity * sizeof(int)); if (ht->keys == NULL || ht->values == NULL) { free(ht->keys); free(ht->values); free(ht); return NULL; } for (int i = 0; i < capacity; i++) { ht->keys[i] = EMPTY; ht->values[i] = 0; } ht->capacity = capacity; ht->size = 0; ht->deletedCount = 0; ht->probe = probe; return ht; } void freeHashTable(HashTable *ht) { if (ht == NULL) return; free(ht->keys); free(ht->values); free(ht); } /* Rehash: double capacity and reinsert all live entries */ static int rehash(HashTable *ht) { int oldCap = ht->capacity; int *oldKeys = ht->keys; int *oldValues = ht->values; int newCap = nextPrime(oldCap * 2); int *newKeys = malloc(newCap * sizeof(int)); int *newValues = malloc(newCap * sizeof(int)); if (newKeys == NULL || newValues == NULL) { free(newKeys); free(newValues); return -1; } for (int i = 0; i < newCap; i++) { newKeys[i] = EMPTY; newValues[i] = 0; } ht->keys = newKeys; ht->values = newValues; ht->capacity = newCap; ht->size = 0; ht->deletedCount = 0; for (int i = 0; i < oldCap; i++) { if (oldKeys[i] != EMPTY && oldKeys[i] != DELETED) { int key = oldKeys[i]; int value = oldValues[i]; int base = (int)h1(key, newCap); for (int j = 0; j < newCap; j++) { int pos = probeAt(base, j, key, newCap, ht->probe); if (newKeys[pos] == EMPTY) { newKeys[pos] = key; newValues[pos] = value; ht->size++; break; } } } } free(oldKeys); free(oldValues); return 0; } int insert(HashTable *ht, int key, int value) { double lf = (double)(ht->size + ht->deletedCount) / ht->capacity; if (lf > REHASH_THRESHOLD) { if (rehash(ht) != 0) return -1; } int base = (int)h1(key, ht->capacity); for (int i = 0; i < ht->capacity; i++) { int pos = probeAt(base, i, key, ht->capacity, ht->probe); if (ht->keys[pos] == key) { ht->values[pos] = value; return 0; } if (ht->keys[pos] == EMPTY || ht->keys[pos] == DELETED) { if (ht->keys[pos] == DELETED) ht->deletedCount--; ht->keys[pos] = key; ht->values[pos] = value; ht->size++; return 0; } } return -1; } int search(HashTable *ht, int key, int *outValue) { int base = (int)h1(key, ht->capacity); for (int i = 0; i < ht->capacity; i++) { int pos = probeAt(base, i, key, ht->capacity, ht->probe); if (ht->keys[pos] == EMPTY) return 0; if (ht->keys[pos] == key) { *outValue = ht->values[pos]; return 1; } } return 0; } int deleteKey(HashTable *ht, int key) { int base = (int)h1(key, ht->capacity); for (int i = 0; i < ht->capacity; i++) { int pos = probeAt(base, i, key, ht->capacity, ht->probe); if (ht->keys[pos] == EMPTY) return -1; if (ht->keys[pos] == key) { ht->keys[pos] = DELETED; ht->deletedCount++; ht->size--; return 0; } } return -1; } static const char *probeName(ProbeType t) { switch (t) { case PROBE_LINEAR: return "linear"; case PROBE_QUADRATIC: return "quadratic"; case PROBE_DOUBLE: return "double"; } return "unknown"; } void display(const HashTable *ht) { double lf = (double)ht->size / ht->capacity; printf("Hash Table (%s, size=%d, capacity=%d, deleted=%d, load=%.2f):\n", probeName(ht->probe), ht->size, ht->capacity, ht->deletedCount, lf); for (int i = 0; i < ht->capacity; i++) { printf(" [%2d]: ", i); if (ht->keys[i] == EMPTY) printf("EMPTY\n"); else if (ht->keys[i] == DELETED) printf("DELETED\n"); else printf("(%d → %d)\n", ht->keys[i], ht->values[i]); } } /* ============ Demos ============ */ static void demoLinear(void) { printf("\n=== Linear Probing ===\n"); HashTable *ht = createHashTable(7, PROBE_LINEAR); if (ht == NULL) return; int keys[] = {50, 70, 76, 85, 93}; for (int i = 0; i < 5; i++) insert(ht, keys[i], keys[i]); display(ht); int v; printf("\nSearch 76: "); if (search(ht, 76, &v)) printf("%d\n", v); else printf("not found\n"); printf("Delete 70...\n"); deleteKey(ht, 70); display(ht); freeHashTable(ht); } static void demoQuadratic(void) { printf("\n=== Quadratic Probing ===\n"); HashTable *ht = createHashTable(7, PROBE_QUADRATIC); if (ht == NULL) return; int keys[] = {22, 30, 50}; for (int i = 0; i < 3; i++) insert(ht, keys[i], keys[i]); display(ht); freeHashTable(ht); } static void demoDouble(void) { printf("\n=== Double Hashing ===\n"); HashTable *ht = createHashTable(7, PROBE_DOUBLE); if (ht == NULL) return; int keys[] = {27, 43, 692, 72}; for (int i = 0; i < 4; i++) insert(ht, keys[i], keys[i]); display(ht); freeHashTable(ht); } static void demoComparison(void) { printf("\n=== Probe Sequence Comparison ===\n"); int keys[] = {50, 70, 76, 85, 93}; HashTable *lin = createHashTable(11, PROBE_LINEAR); HashTable *quad = createHashTable(11, PROBE_QUADRATIC); HashTable *dbl = createHashTable(11, PROBE_DOUBLE); if (!lin || !quad || !dbl) { freeHashTable(lin); freeHashTable(quad); freeHashTable(dbl); return; } for (int i = 0; i < 5; i++) { insert(lin, keys[i], keys[i]); insert(quad, keys[i], keys[i]); insert(dbl, keys[i], keys[i]); } printf("Linear table:\n"); for (int i = 0; i < lin->capacity; i++) printf("%4d ", lin->keys[i]); printf("\n\nQuadratic table:\n"); for (int i = 0; i < quad->capacity; i++) printf("%4d ", quad->keys[i]); printf("\n\nDouble hashing table:\n"); for (int i = 0; i < dbl->capacity; i++) printf("%4d ", dbl->keys[i]); printf("\n"); freeHashTable(lin); freeHashTable(quad); freeHashTable(dbl); } static int readInteger(const char *prompt, int *outValue) { char buffer[MAX_LINE_LEN]; char *endPtr; long val; printf("%s", prompt); fflush(stdout); if (fgets(buffer, sizeof(buffer), stdin) == NULL) return -1; errno = 0; val = strtol(buffer, &endPtr, 10); if (endPtr == buffer || (*endPtr != '\n' && *endPtr != '\0')) return -1; if (errno == ERANGE || val < -2147483647 - 1 || val > 2147483647) return -1; *outValue = (int)val; return 0; } int main(void) { int choice; char buffer[MAX_LINE_LEN]; printf("=== Open Addressing Demo ===\n"); while (1) { printf("\n--- Menu ---\n"); printf("1. Linear Probing\n"); printf("2. Quadratic Probing\n"); printf("3. Double Hashing\n"); printf("4. Compare All Three\n"); printf("5. Interactive (Linear Probing)\n"); printf("6. Exit\n"); printf("Enter choice: "); fflush(stdout); if (fgets(buffer, sizeof(buffer), stdin) == NULL) { fprintf(stderr, "Error reading choice.\n"); return EXIT_FAILURE; } choice = atoi(buffer); if (choice == 1) { demoLinear(); } else if (choice == 2) { demoQuadratic(); } else if (choice == 3) { demoDouble(); } else if (choice == 4) { demoComparison(); } else if (choice == 5) { HashTable *ht = createHashTable(11, PROBE_LINEAR); if (ht == NULL) continue; int opt; while (1) { printf("\n--- Interactive Hash Table ---\n"); printf("1. Insert\n2. Search\n3. Delete\n4. Display\n5. Back\n"); printf("Enter choice: "); fflush(stdout); if (fgets(buffer, sizeof(buffer), stdin) == NULL) break; opt = atoi(buffer); if (opt == 1) { int k, v; if (readInteger("Key: ", &k) == 0 && readInteger("Value: ", &v) == 0) { insert(ht, k, v); printf("Inserted (%d → %d)\n", k, v); } } else if (opt == 2) { int k, v; if (readInteger("Key: ", &k) == 0) { if (search(ht, k, &v)) printf("Found: %d → %d\n", k, v); else printf("Key %d not found\n", k); } } else if (opt == 3) { int k; if (readInteger("Key: ", &k) == 0) { if (deleteKey(ht, k) == 0) printf("Deleted %d\n", k); else printf("Key %d not found\n", k); } } else if (opt == 4) { display(ht); } else if (opt == 5) { break; } } freeHashTable(ht); } else if (choice == 6) { printf("Exiting.\n"); return EXIT_SUCCESS; } else { printf("Invalid choice.\n"); } } return EXIT_SUCCESS; }

Explanation of the Code

  1. HashTable — Stores keys, values, capacity, size, deleted count, and probe type.
  2. h1 — Primary division hash.
  3. h2 — Secondary hash for double hashing; returns 1..m-1.
  4. probeAt — Computes index for iteration i based on probe type.
  5. insert — Probes until key matched or EMPTY/DELETED found.
  6. search — Probes until key found or EMPTY encountered.
  7. deleteKey — Replaces key with DELETED tombstone.
  8. rehash — Grows capacity and reinserts live entries.

Expected Output (sample run)

text

=== Linear Probing === Hash Table (linear, size=5, capacity=7, deleted=0, load=0.71): [ 0]: (70 → 70) [ 1]: (50 → 50) [ 2]: (76 → 76) [ 3]: (85 → 85) [ 4]: (93 → 93) [ 5]: EMPTY [ 6]: EMPTY Search 76: 76 Delete 70... Hash Table (linear, size=4, capacity=7, deleted=1, load=0.57): [ 0]: DELETED [ 1]: (50 → 50) [ 2]: (76 → 76) [ 3]: (85 → 85) [ 4]: (93 → 93) [ 5]: EMPTY [ 6]: EMPTY === Quadratic Probing === Hash Table (quadratic, size=3, capacity=7, deleted=0, load=0.43): [ 0]: EMPTY [ 1]: (22 → 22) [ 2]: (30 → 30) [ 3]: EMPTY [ 4]: EMPTY [ 5]: (50 → 50) [ 6]: EMPTY === Double Hashing === Hash Table (double, size=4, capacity=7, deleted=0, load=0.57): ... === Probe Sequence Comparison === Linear table: 70 50 76 85 93 -1 -1 ... Quadratic table: -1 50 70 93 -1 76 85 ... Double hashing table: ...

Common Pitfalls, Edge Cases & Memory Considerations

1. Infinite Probe Loop

Unbounded probing can loop forever if no empty slot exists.

Solution: Bound loop by capacity.

2. Quadratic Probing Not Visiting All Slots

Standard quadratic probing may miss slots if m is not prime and load is high.

Solution: Use prime table sizes; or use the modified formula from the previous tutorial.

3. Double Hashing with h2(k) = 0

If h2(k) returns 0, probing stalls.

Solution: Ensure h2(k) ∈ [1, m-1].

4. Forgetting Tombstones

Deleting by clearing breaks probe chains.

Solution: Use DELETED marker.

5. Load Factor Reaching 1

Table becomes full; insert fails.

Solution: Rehash when α > 0.7.

6. Primary Clustering (Linear)

Runs of occupied slots slow lookups.

Solution: Use quadratic or double hashing.

7. Secondary Clustering (Quadratic)

Keys with same initial hash follow identical probes.

Solution: Use double hashing.

8. Rehash Double-Counting

Not updating size and deletedCount correctly during rehash.

Solution: Reset counters at rehash start, then count entries as they are reinserted.

9. Negative Keys

key % m for negative keys yields negative indices.

Solution: Cast to unsigned int.

10. Memory Considerations

  • Keys + values arrays: capacity × (sizeof(int) × 2).
  • No pointers per entry — memory efficient.
  • Rehash doubles memory temporarily.
  • Free all arrays on cleanup.

Summary & Best Practices

Open Addressing is a memory-efficient, cache-friendly collision resolution strategy. Choosing the right probe sequence (linear, quadratic, double hashing) determines performance and clustering behavior.

Key Takeaways

  • All entries stored in the table itself.
  • Three probe strategies: linear, quadratic, double.
  • Linear: best cache, primary clustering.
  • Quadratic: middle ground, secondary clustering.
  • Double: best distribution, poor cache.
  • Deletion uses tombstones.
  • Load factor α = n/m; keep below 0.7.
  • Expected operations: O(1 / (1 - α)).

Best Practices

  1. Use prime table sizes for better distribution.
  2. Keep α ≤ 0.7; rehash proactively.
  3. Use tombstones for deletion.
  4. Bound probe loops by capacity.
  5. Choose double hashing for minimal clustering.
  6. Choose linear probing for cache-sensitive workloads.
  7. Ensure h2(k) is never 0 in double hashing.
  8. Track deletedCount to trigger rehash.
  9. Cast keys to unsigned before modulo.
  10. Profile with real workloads to pick the best strategy.

By mastering open addressing, you’ll implement memory-efficient, high-performance hash tables suitable for embedded systems, real-time applications, and cache-sensitive workloads.

Teacher pointing to whiteboard chart about linear probing in hash tables in a classroom

Linear Probing in Hash Tables in C: Complete Guide

Linear Probing in Hash Tables in C: A Comprehensive Tutorial

Linear Probing is the simplest and most widely used Open Addressing collision resolution technique. When a collision occurs, the algorithm probes the next slot in the table linearly until it finds an empty, deleted, or matching slot. All elements are stored directly in the hash table itself, requiring no auxiliary linked lists.

This tutorial provides an in-depth exploration of Linear Probing in C: fundamental concepts, insertion, search, deletion with tombstones, rehashing, complexity analysis, complete implementation, common pitfalls, and best practices.


Conceptual Introduction & Fundamentals

What is Linear Probing?

Linear Probing is an Open Addressing strategy where, on collision at index h(k), we check h(k) + 1, h(k) + 2, … (modulo table size) until we find a suitable slot.

Probe sequence: (h(k) + i) % m for i = 0, 1, 2, ..., m-1

Why Linear Probing?

  • No extra memory: All elements are stored directly in the table.
  • Cache-friendly: Sequential probing has excellent cache locality.
  • Simple to implement: No linked lists or pointers needed.
  • Fast for low load factors: α < 0.7 yields O(1) average operations.

Key Concepts

ConceptDescription
Open AddressingAll keys stored in the table itself
ProbeSequence of slots examined on collision
Load Factor (α)n / m (entries / table size)
TombstoneMarker for deleted slot
ClusteringAdjacent occupied slots form a cluster
RehashingResizing table when α exceeds threshold

The Tombstone Problem

Simply clearing a deleted slot would break probe chains. Instead, mark the slot with a tombstone (a special value indicating deletion). Searches continue past tombstones; insertions may reuse them.

Example issue without tombstones:

text

Insert 1, 11, 21 with h(k) = k % 10: [1]: 1, [2]: 11, [3]: 21 Delete 11 (clear slot): [1]: 1, [2]: EMPTY, [3]: 21 Search 21 → hits EMPTY at [2], stops, reports "not found" (BUG!)

With tombstone:

text

Delete 11 (mark as DELETED): [1]: 1, [2]: DELETED, [3]: 21 Search 21 → passes [2] tombstone, finds 21 at [3] ✓

Complexity Analysis

OperationBestAverageWorst
InsertO(1)O(1)O(n)
SearchO(1)O(1)O(n)
DeleteO(1)O(1)O(n)

Worst case occurs when many collisions cluster keys (primary clustering).

Linear Probing vs Chaining

AspectLinear ProbingChaining
MemoryNo pointers; table-onlyExtra pointer per entry
CacheExcellent localityPoor for long chains
Load factorMust stay < 1Can exceed 1
DeletionRequires tombstonesDirect node removal
ClusteringPrimary clusteringNone
PerformanceDegrades fast near α = 1Degrades linearly

Syntax & Core Mechanics

Slot States

c

#define EMPTY (-1) #define DELETED (-2)

We use sentinel keys to mark empty and deleted slots.

Basic Structure

c

typedef struct { int *keys; /* Keys array */ int *values; /* Values array */ int *states; /* EMPTY, DELETED, or OCCUPIED (0/1) */ int capacity; int size; } HashTable;

Alternative: Use a single sentinel key DELETED (e.g., -1) with the slot’s key field.

c

typedef struct { int key; /* -1 = empty, -2 = deleted */ int value; } Slot; typedef struct { Slot *slots; int capacity; int size; } HashTable;

Insertion Algorithm

  1. Compute idx = h(key).
  2. Probe: pos = (idx + i) % m for i = 0, 1, ....
  3. If slots[pos].key == EMPTY or DELETED: insert; if it was EMPTY, increment size.
  4. If slots[pos].key == key: update value.
  5. Continue until inserted or full.

Search Algorithm

  1. Compute idx = h(key).
  2. Probe: pos = (idx + i) % m.
  3. If slots[pos].key == key: found.
  4. If slots[pos].key == EMPTY: stop (key absent).
  5. If slots[pos].key == DELETED: continue probing.
  6. Stop after examining all slots.

Deletion Algorithm

  1. Find the key via probe.
  2. Replace with DELETED marker (tombstone).
  3. Decrement size.

Rehashing

When load factor > threshold (typically 0.7):

  1. Double capacity (choose prime).
  2. Create new slot array (all EMPTY).
  3. Reinsert all non-empty, non-deleted entries.

Full Practical Code Example with Explanation

This program implements a complete hash table using linear probing with tombstones and rehashing.

c

/** * linear_probing.c * Complete hash table implementation using linear probing. * Supports insert, search, delete, rehashing, and display. */ #include <stdio.h> #include <stdlib.h> #include <string.h> #include <errno.h> #define MAX_LINE_LEN 100 #define EMPTY (-1) #define DELETED (-2) #define REHASH_THRESHOLD 0.7 /* Slot in the hash table */ typedef struct { int key; /* EMPTY, DELETED, or a valid key */ int value; } Slot; /* Hash table using linear probing */ typedef struct { Slot *slots; int capacity; int size; /* Number of live entries */ int deletedCount; } HashTable; /* Find next prime >= n */ static int nextPrime(int n) { if (n <= 2) return 2; if (n % 2 == 0) n++; while (1) { int isPrime = 1; for (int i = 3; i * i <= n; i += 2) { if (n % i == 0) { isPrime = 0; break; } } if (isPrime) return n; n += 2; } } /* Hash function */ static unsigned int hashIndex(int key, int capacity) { return ((unsigned int)key) % (unsigned int)capacity; } /* Create a hash table with given initial capacity */ HashTable *createHashTable(int initialCapacity) { HashTable *ht = malloc(sizeof(HashTable)); if (ht == NULL) return NULL; int capacity = nextPrime(initialCapacity); ht->slots = malloc(capacity * sizeof(Slot)); if (ht->slots == NULL) { free(ht); return NULL; } for (int i = 0; i < capacity; i++) { ht->slots[i].key = EMPTY; ht->slots[i].value = 0; } ht->capacity = capacity; ht->size = 0; ht->deletedCount = 0; return ht; } void freeHashTable(HashTable *ht) { if (ht == NULL) return; free(ht->slots); free(ht); } /* Rehash: grow table and reinsert entries */ static int rehash(HashTable *ht) { int oldCapacity = ht->capacity; Slot *oldSlots = ht->slots; int newCapacity = nextPrime(oldCapacity * 2); Slot *newSlots = malloc(newCapacity * sizeof(Slot)); if (newSlots == NULL) return -1; for (int i = 0; i < newCapacity; i++) { newSlots[i].key = EMPTY; newSlots[i].value = 0; } ht->slots = newSlots; ht->capacity = newCapacity; ht->size = 0; ht->deletedCount = 0; for (int i = 0; i < oldCapacity; i++) { if (oldSlots[i].key != EMPTY && oldSlots[i].key != DELETED) { int key = oldSlots[i].key; int value = oldSlots[i].value; unsigned int idx = hashIndex(key, newCapacity); for (int j = 0; j < newCapacity; j++) { int pos = (int)((idx + (unsigned int)j) % (unsigned int)newCapacity); if (newSlots[pos].key == EMPTY) { newSlots[pos].key = key; newSlots[pos].value = value; ht->size++; break; } } } } free(oldSlots); return 0; } /* Insert or update key-value pair */ int insert(HashTable *ht, int key, int value) { double lf = (double)(ht->size + ht->deletedCount) / ht->capacity; if (lf > REHASH_THRESHOLD) { if (rehash(ht) != 0) return -1; } unsigned int idx = hashIndex(key, ht->capacity); for (int i = 0; i < ht->capacity; i++) { int pos = (int)((idx + (unsigned int)i) % (unsigned int)ht->capacity); if (ht->slots[pos].key == key) { ht->slots[pos].value = value; /* Update */ return 0; } if (ht->slots[pos].key == EMPTY || ht->slots[pos].key == DELETED) { if (ht->slots[pos].key == DELETED) ht->deletedCount--; ht->slots[pos].key = key; ht->slots[pos].value = value; ht->size++; return 0; } } return -1; /* Table full */ } /* Search for a key; returns 1 if found */ int search(HashTable *ht, int key, int *outValue) { unsigned int idx = hashIndex(key, ht->capacity); for (int i = 0; i < ht->capacity; i++) { int pos = (int)((idx + (unsigned int)i) % (unsigned int)ht->capacity); if (ht->slots[pos].key == EMPTY) { return 0; /* Not found */ } if (ht->slots[pos].key == key) { *outValue = ht->slots[pos].value; return 1; } /* Continue past DELETED slots */ } return 0; } /* Delete a key; returns 0 on success */ int deleteKey(HashTable *ht, int key) { unsigned int idx = hashIndex(key, ht->capacity); for (int i = 0; i < ht->capacity; i++) { int pos = (int)((idx + (unsigned int)i) % (unsigned int)ht->capacity); if (ht->slots[pos].key == EMPTY) { return -1; /* Not found */ } if (ht->slots[pos].key == key) { ht->slots[pos].key = DELETED; ht->deletedCount++; ht->size--; return 0; } } return -1; } /* Display the table */ void display(const HashTable *ht) { double lf = (double)ht->size / ht->capacity; printf("Hash Table (size=%d, capacity=%d, deleted=%d, load=%.2f):\n", ht->size, ht->capacity, ht->deletedCount, lf); for (int i = 0; i < ht->capacity; i++) { printf(" [%2d]: ", i); if (ht->slots[i].key == EMPTY) printf("EMPTY\n"); else if (ht->slots[i].key == DELETED) printf("DELETED\n"); else printf("(%d → %d)\n", ht->slots[i].key, ht->slots[i].value); } } /* ============ Demos ============ */ static void demoBasicOperations(void) { printf("\n=== Basic Linear Probing Demo ===\n"); HashTable *ht = createHashTable(10); if (ht == NULL) return; int keys[] = {1, 2, 3, 22, 42}; int n = sizeof(keys) / sizeof(keys[0]); for (int i = 0; i < n; i++) { insert(ht, keys[i], keys[i] * 10); } display(ht); int value; printf("\nSearch 3: "); if (search(ht, 3, &value)) printf("%d\n", value); else printf("not found\n"); printf("Search 22: "); if (search(ht, 22, &value)) printf("%d\n", value); else printf("not found\n"); printf("Search 100: "); if (search(ht, 100, &value)) printf("%d\n", value); else printf("not found\n"); printf("\nDeleting 2...\n"); deleteKey(ht, 2); display(ht); printf("\nAfter delete, search 22: "); if (search(ht, 22, &value)) printf("%d (past tombstone)\n", value); else printf("not found\n"); printf("Insert 12 (reuses DELETED slot)...\n"); insert(ht, 12, 120); display(ht); freeHashTable(ht); } static void demoRehashing(void) { printf("\n=== Rehashing Demo ===\n"); HashTable *ht = createHashTable(5); if (ht == NULL) return; for (int i = 0; i < 15; i++) { int key = (i * 7 + 3) % 100; insert(ht, key, key * 10); if (i == 4 || i == 9) { printf("\nAfter %d inserts:\n", i + 1); display(ht); } } printf("\nFinal table:\n"); display(ht); freeHashTable(ht); } /* Read integer safely */ static int readInteger(const char *prompt, int *outValue) { char buffer[MAX_LINE_LEN]; char *endPtr; long val; printf("%s", prompt); fflush(stdout); if (fgets(buffer, sizeof(buffer), stdin) == NULL) return -1; errno = 0; val = strtol(buffer, &endPtr, 10); if (endPtr == buffer || (*endPtr != '\n' && *endPtr != '\0')) return -1; if (errno == ERANGE || val < -2147483647 - 1 || val > 2147483647) return -1; *outValue = (int)val; return 0; } int main(void) { int choice; char buffer[MAX_LINE_LEN]; printf("=== Linear Probing Hash Table Demo ===\n"); while (1) { printf("\n--- Menu ---\n"); printf("1. Basic Operations Demo\n"); printf("2. Rehashing Demo\n"); printf("3. Interactive Hash Table\n"); printf("4. Exit\n"); printf("Enter choice: "); fflush(stdout); if (fgets(buffer, sizeof(buffer), stdin) == NULL) { fprintf(stderr, "Error reading choice.\n"); return EXIT_FAILURE; } choice = atoi(buffer); if (choice == 1) { demoBasicOperations(); } else if (choice == 2) { demoRehashing(); } else if (choice == 3) { HashTable *ht = createHashTable(10); if (ht == NULL) continue; int opt; while (1) { printf("\n--- Interactive Hash Table ---\n"); printf("1. Insert\n2. Search\n3. Delete\n4. Display\n5. Back\n"); printf("Enter choice: "); fflush(stdout); if (fgets(buffer, sizeof(buffer), stdin) == NULL) break; opt = atoi(buffer); if (opt == 1) { int k, v; if (readInteger("Key: ", &k) == 0 && readInteger("Value: ", &v) == 0) { insert(ht, k, v); printf("Inserted (%d → %d)\n", k, v); } } else if (opt == 2) { int k, v; if (readInteger("Key: ", &k) == 0) { if (search(ht, k, &v)) printf("Found: %d → %d\n", k, v); else printf("Key %d not found\n", k); } } else if (opt == 3) { int k; if (readInteger("Key: ", &k) == 0) { if (deleteKey(ht, k) == 0) printf("Deleted %d\n", k); else printf("Key %d not found\n", k); } } else if (opt == 4) { display(ht); } else if (opt == 5) { break; } } freeHashTable(ht); } else if (choice == 4) { printf("Exiting.\n"); return EXIT_SUCCESS; } else { printf("Invalid choice.\n"); } } return EXIT_SUCCESS; }

Explanation of the Code

  1. Slot — Stores key and value; sentinel keys mark EMPTY and DELETED.
  2. HashTable — Contains slots array, capacity, size, and deleted count.
  3. hashIndex — Division-method hash with unsigned cast.
  4. nextPrime — Finds next prime ≥ n for capacity.
  5. createHashTable — Allocates and initializes all slots to EMPTY.
  6. insert — Probes linearly; updates existing key, reuses DELETED, or inserts at EMPTY.
  7. search — Probes until key found or EMPTY encountered; passes over DELETED.
  8. deleteKey — Replaces slot with DELETED tombstone.
  9. rehash — Doubles capacity, reinserts live entries.
  10. display — Prints each slot’s state.

Expected Output (sample run)

text

=== Basic Linear Probing Demo === Hash Table (size=5, capacity=11, deleted=0, load=0.45): [ 0]: (22 → 220) [ 1]: (1 → 10) [ 2]: (2 → 20) [ 3]: (3 → 30) [ 4]: (42 → 420) [ 5]: EMPTY [ 6]: EMPTY [ 7]: EMPTY [ 8]: EMPTY [ 9]: EMPTY [10]: EMPTY Search 3: 30 Search 22: 220 Search 100: not found Deleting 2... Hash Table (size=4, capacity=11, deleted=1, load=0.36): [ 0]: (22 → 220) [ 1]: (1 → 10) [ 2]: DELETED [ 3]: (3 → 30) [ 4]: (42 → 420) ... After delete, search 22: 220 (past tombstone) Insert 12 (reuses DELETED slot)... Hash Table (size=5, capacity=11, deleted=0, load=0.45): [ 0]: (22 → 220) [ 1]: (1 → 10) [ 2]: (12 → 120) [ 3]: (3 → 30) [ 4]: (42 → 420) ...

Common Pitfalls, Edge Cases & Memory Considerations

1. Infinite Probe Loop

If the table is full and no tombstone exists, probing never terminates.

c

for (int i = 0; i < ht->capacity; i++) { ... } /* Bounded loop */

Solution: Always bound the probe loop by capacity.

2. Tombstone Accumulation

Frequent deletes fill the table with tombstones, degrading performance.

Solution: Track deletedCount and trigger rehash when (size + deleted) / capacity exceeds threshold.

3. Wrong Load Factor

Using only size / capacity ignores tombstones.

Solution: Use (size + deleted) / capacity for rehash decisions.

4. Search Stops at DELETED

Searches must continue past DELETED slots.

c

if (slots[pos].key == EMPTY) return 0; /* Stop */ if (slots[pos].key == key) return 1; /* Found */ /* else continue past DELETED */

5. Table Size Not Prime

Non-prime sizes cause clustering.

Solution: Use nextPrime.

6. Unbounded Rehashing

Rehashing in a loop can cause infinite recursion.

Solution: Rehash once per insert, not recursively.

7. Deleting from Empty Table

Guard against size == 0 before deleting.

8. Negative Keys

Cast to unsigned int before modulo.

9. Rehashing During Insert

Ensure rehash happens before computing the initial probe index.

10. Memory Considerations

  • Table memory: capacity × sizeof(Slot).
  • No pointers per entry — memory efficient.
  • Rehashing doubles temporary memory.
  • Free the slots array on destruction.

Summary & Best Practices

Linear Probing is a straightforward Open Addressing strategy with excellent cache locality. Handling tombstones and rehashing correctly is essential for maintaining O(1) average performance.

Key Takeaways

  • Probe sequence: (h(k) + i) % m.
  • Use tombstones for deletion.
  • Bound probe loops by capacity.
  • Rehash when (size + deleted) / capacity > 0.7.
  • Use prime table sizes.
  • Complexity: O(1) average; O(n) worst.

Best Practices

  1. Use prime table sizes for better distribution.
  2. Bound probe loops by capacity to avoid infinite loops.
  3. Track tombstones and rehash when they accumulate.
  4. Continue search past DELETED slots.
  5. Rehash when load factor exceeds 0.7.
  6. Cast keys to unsigned before modulo.
  7. Prefer linear probing for cache-friendly workloads.
  8. Consider quadratic probing or double hashing for lower clustering.
  9. Free the slots array on cleanup.
  10. Profile for large datasets to tune thresholds.

By mastering linear probing, you’ll implement efficient in-place hash maps without pointer overhead, ideal for cache-sensitive applications.