Easy Notes Of Data structure using C unit-2 @Computer Diploma

Description

Searching Keywords

• Linear Search:
  • Sequential access: The method involves checking every element in the sequence one by one.
  • Unsorted data sets: Linear search can be applied effectively to data that hasn’t been ordered.
  • Worst-case time complexity $O(n)$: Describes the maximum time taken, proportional to the number of elements ($n$).
• Binary Search:
  • Divide and conquer strategy: The core technique of repeatedly splitting the search interval in half.
  • Sorted data sets prerequisite: The essential condition that the data must be ordered for the search to function correctly.
  • Logarithmic time complexity $O(\log n)$: Indicates a highly efficient search time that grows very slowly as the data set size increases.
  • Middle element comparison: The repeated action of comparing the target item to the value at the center of the current sub list.

Sorting Keywords

• Bubble Sort:
  • Adjacent element comparison and swapping: The fundamental operation of comparing and potentially exchanging neighboring items.
  • Repeated passes: Multiple full iterations over the list are required to place elements in their correct positions.
  • Stable sorting algorithm: Maintains the relative order of elements with equal values.
• Selection Sort:
  • Minimum (or maximum) element finding: The process of locating the smallest (or largest) item in the unsorted portion of the list.
  • In-place sorting algorithm: Requires only a small, constant amount of extra memory space.
  • Minimizing swaps: This method is characterized by a low number of element exchanges, typically only one per pass.
• Insertion Sort:
  • Sorted and unsorted sublists: The array is conceptually divided into these two parts during the sorting process.
  • Key element placement: The action of taking an item from the unsorted part and inserting it into its correct position within the sorted part.
  • Adaptive sorting algorithm: Its efficiency improves significantly when dealing with data that is already partially sorted.
• Quick Sort:
  • Pivot element selection: Choosing an item around which the other elements will be partitioned.
  • Recursive partitioning: The process of dividing the list into two sub-lists (smaller and larger than the pivot) and then applying the sort to the sub-lists.
  • Average-case time complexity $O(n\log n)$: The typical and most desirable performance characteristic.
• Merge Sort:
  • Merging sorted sub-arrays: The primary operation where two ordered lists are combined into a single, larger ordered list.
  • Guaranteed worst-case $O(n\log n)$ performance: Its efficiency is consistently high regardless of the initial order of the data.
  • External sorting compatibility: Can be easily adapted to sort data sets that are too large to fit into memory.