Data structures (introduction)

Data structures (introduction)

• 1.
  Data Structures Arvind Devaraj
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  Data Structure Selection •What data structure will you use in the following Scenarios
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  Ten people arestanding in a row. Every third person is eliminated. Which person remains Which Data structure ? Array, List, Tree, Stack, Queue ????? SCENARIO-1
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  SCENARIO 2 Recent 5missed calls must be displayed Which Data structure ? Array, List, Tree, Stack, Queue ?????
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  SCENARIO 3 • Needto maintain database of student names…support for – Insert, Delete, Search – (also) next and previous person – (also) find who got maximum marks Which Data structure ? Array, List, Tree, Stack, Queue ?????
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  SCENARIO 4 Each personis assigned a priority number when he enters an office. The person who has the highest priority is served Each process is having priority. The OS schedules the one having the highest priority Which Data structure ? Array, List, Tree, Stack, Queue ?????
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  Arrays (vs List) +Fast Access + Memory consumption is minimal - Insertion and deletion is complicated
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  Linked Lists • Away of making variable length arrays – In which insertions and deletions are easy • But nothing comes for free – Finding an element can be slow – Extra space is needed for the links
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  Linked List Example JillJoe Tom first Public static main (String[] argv) { Student first; … } Public class Student { String name; public Student next; }
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  Trees • Linked listwith multiple next elements Binary trees are useful for relationships like “<“ , “>” • Insertions and deletions are easy • Useful for fast searching of large collections
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  Binary Tree Example Jill Joe Tom rootPublic class Student { int String name; public Student left; public Student right; }
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  Write a program •height of binary tree • Count leaves • Find minimum value • Locate a particular node • Find successor of a node • Check if it’s a Binary Search tree
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  int height( BinaryTreeNode t) { if t is a null tree return -1; hl = height( left subtree of t); hr = height( right subtree of t); h = 1 + maximum of hl and hr; return h; }
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  Hashtables • Find anelement nearly as fast as in an array – With easy insertion and deletion – But without the ability to keep things in order • Fairly complex to implement – But Java defines a class to make it simple • Helpful to understand how it works – “One size fits all” approaches are inefficient
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  Choosing a DataStructure • What operations do you need to perform? • Hashing finds single elements quickly – But cannot preserve order • Stacks and linked lists preserve order easily – But they can only read one element at any time • Balanced trees are best when you need both – Need to read in blocks (for disks) – B-Tree is used