What Is Compaction in Data Structure?


Larry Thompson

In data structure, compaction refers to the process of reducing the size of a data structure by eliminating empty or unused spaces. It is an important technique used to optimize memory utilization and improve the efficiency of operations performed on the data structure. Compaction is commonly used in array-based data structures, such as arrays and linked lists, where elements are stored in consecutive memory locations.

Why is Compaction Important?

Compaction plays a crucial role in managing memory efficiently. By eliminating empty or unused spaces within a data structure, it allows for better utilization of available memory. This can result in significant improvements in performance and reduced memory overhead.

Advantages of Compaction

  • Reduced Memory Waste: Compaction eliminates unused or empty spaces within a data structure, reducing memory waste and enabling more efficient use of available memory.
  • Better Cache Performance: Compact data structures are more cache-friendly as they occupy fewer cache lines, leading to improved cache performance and faster access times.
  • Faster Operations: Compacting a data structure can improve the performance of various operations such as searching, insertion, and deletion by reducing the number of memory accesses required.

How Does Compaction Work?

The process of compaction involves rearranging the elements within a data structure to eliminate empty or unused spaces. There are various techniques for performing compaction depending on the type of data structure being used.

Array-based Data Structures

In array-based data structures like arrays and linked lists, compaction typically involves shifting elements towards one end of the array while maintaining their relative order. This is achieved by moving non-empty elements to fill up any empty spaces left behind by deleted elements.

Example: Consider an array-based data structure with the following elements:

  Index: 0   1   2   3   4
  Array: A   B       C

If element B is deleted, the compaction process would shift element C to fill the empty space:

  Index: 0   1   2
  Array: A   C

Linked Data Structures

In linked data structures like linked lists, compaction involves removing any nodes that are no longer needed and updating the necessary pointers to maintain connectivity within the list. The freed memory can then be reused for other purposes.

Example: Consider a singly linked list with the following elements:

      +---+    +---+    +---+    +---+
Head -> | A | -> | B | -> |     | -> | C |
      +---+    +---+    +---+    +---+

If node B is deleted, the compaction process would update the pointer of node A to point directly to node C, effectively removing node B from the list:

      +---+         +---+         +---+
Head -> | A | ------> |     | ------> | C |
      +---+         +---+         +---+


Compaction is a vital technique in data structure that helps optimize memory utilization and improve performance. By eliminating empty or unused spaces, compaction reduces memory waste and enables more efficient use of available memory. It plays a significant role in improving cache performance and speeding up various operations performed on a data structure.

Understanding the concept of compaction and its application in different data structures is essential for developing efficient algorithms and designing memory-efficient programs.

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