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INTRODUCTION
• DATA STRUCTURE CAN BE DEFINED AS THE GROUP OF DATA
ELEMENTS WHICH PROVIDES AN EFFICIENT WAY OF STORING AND
ORGANIZING DATA IN THE COMPUTER SO THAT IT CAN BE USED
EFFICIENTLY.
• DATA STRUCTURES ARE WIDELY USED IN ALMOST EVERY ASPECT OF
COMPUTER SCIENCE I.E. OPERATING SYSTEM, COMPILER DESIGN,
ARTIFICIAL INTELLIGENCE, GRAPHICS AND MANY MORE.
NEED OF DATA STRUCTURES
• PROCESSOR SPEED: TO HANDLE VERY LARGE AMOUNT OF DATA, HIGH
SPEED PROCESSING IS REQUIRED, BUT AS THE DATA IS GROWING DAY BY
DAY TO THE BILLIONS OF FILES PER ENTITY, PROCESSOR MAY FAIL TO DEAL
WITH THAT MUCH AMOUNT OF DATA.
• DATA SEARCH: CONSIDER AN INVENTORY SIZE OF 106 ITEMS IN A
STORE, IF OUR APPLICATION NEEDS TO SEARCH FOR A PARTICULAR ITEM,
IT NEEDS TO TRAVERSE 106 ITEMS EVERY TIME, RESULTS IN SLOWING
DOWN THE SEARCH PROCESS.
• MULTIPLE REQUESTS: IF THOUSANDS OF USERS ARE SEARCHING THE
DATA SIMULTANEOUSLY ON A WEB SERVER, THEN THERE ARE THE CHANCES
THAT A VERY LARGE SERVER CAN BE FAILED DURING THAT PROCESS
ADVANTAGES OF DATA STRUCTURES
• EFFICIENCY: EFFICIENCY OF A PROGRAM DEPENDS UPON THE CHOICE OF DATA
STRUCTURES. FOR EXAMPLE: SUPPOSE, WE HAVE SOME DATA AND WE NEED TO
PERFORM THE SEARCH FOR A PARTICULAR RECORD. IN THAT CASE, IF WE
ORGANIZE OUR DATA IN AN ARRAY, WE WILL HAVE TO SEARCH SEQUENTIALLY
ELEMENT BY ELEMENT. HENCE, USING ARRAY MAY NOT BE VERY EFFICIENT HERE.
• REUSABILITY: DATA STRUCTURES ARE REUSABLE, I.E. ONCE WE HAVE
IMPLEMENTED A PARTICULAR DATA STRUCTURE, WE CAN USE IT AT ANY OTHER
PLACE. IMPLEMENTATION OF DATA STRUCTURES CAN BE COMPILED INTO
LIBRARIES WHICH CAN BE USED BY DIFFERENT CLIENTS.
• ABSTRACTION: DATA STRUCTURE IS SPECIFIED BY THE ADT WHICH PROVIDES A
LEVEL OF ABSTRACTION. THE CLIENT PROGRAM USES THE DATA STRUCTURE
THROUGH INTERFACE ONLY, WITHOUT GETTING INTO THE IMPLEMENTATION
DETAILS.
DATA STRUCTURE CLASSIFICATION
LINEAR
• A DATA STRUCTURE IS CALLED LINEAR IF ALL OF ITS ELEMENTS ARE ARRANGED IN THE LINEAR
ORDER. IN LINEAR DATA STRUCTURES, THE ELEMENTS ARE STORED IN NON-HIERARCHICAL WAY
WHERE EACH ELEMENT HAS THE SUCCESSORS AND PREDECESSORS EXCEPT THE FIRST AND LAST
ELEMENT.
• TYPES OF LINEAR DATA STRUCTURES ARE GIVEN BELOW:
1. ARRAYS: AN ARRAY IS A COLLECTION OF SIMILAR TYPE OF DATA ITEMS AND EACH DATA ITEM IS
CALLED AN ELEMENT OF THE ARRAY. THE DATA TYPE OF THE ELEMENT MAY BE ANY VALID DATA TYPE
LIKE CHAR, INT, FLOAT OR DOUBLE.
2. LINKED LIST: LINKED LIST IS A LINEAR DATA STRUCTURE WHICH IS USED TO MAINTAIN A LIST IN
THE MEMORY. IT CAN BE SEEN AS THE COLLECTION OF NODES STORED AT NON-CONTIGUOUS
MEMORY LOCATIONS. EACH NODE OF THE LIST CONTAINS A POINTER TO ITS ADJACENT NODE.
3. STACK: STACK IS A LINEAR LIST IN WHICH INSERTION AND DELETIONS ARE ALLOWED ONLY AT ONE
END, CALLED TOP.
4. QUEUE: QUEUE IS A LINEAR LIST IN WHICH ELEMENTS CAN BE INSERTED ONLY AT ONE END
CALLED REAR AND DELETED ONLY AT THE OTHER END CALLED FRONT.
OPERATIONS ON DATA STRUCTURE
• TRAVERSING: EVERY DATA STRUCTURE CONTAINS THE SET OF DATA
ELEMENTS. TRAVERSING THE DATA STRUCTURE MEANS VISITING
EACH ELEMENT OF THE DATA STRUCTURE IN ORDER TO PERFORM
SOME SPECIFIC OPERATION LIKE SEARCHING OR SORTING.
• INSERTION: INSERTION CAN BE DEFINED AS THE PROCESS OF
ADDING THE ELEMENTS TO THE DATA STRUCTURE AT ANY LOCATION.
• DELETION: THE PROCESS OF REMOVING AN ELEMENT FROM THE
DATA STRUCTURE IS CALLED DELETION. WE CAN DELETE AN
ELEMENT FROM THE DATA STRUCTURE AT ANY RANDOM LOCATION.
• SEARCHING: THE PROCESS OF FINDING THE LOCATION OF AN
ELEMENT WITHIN THE DATA STRUCTURE IS CALLED SEARCHING.
THERE ARE TWO ALGORITHMS TO PERFORM SEARCHING, LINEAR
SEARCH AND BINARY SEARCH.
• SORTING: THE PROCESS OF ARRANGING THE DATA STRUCTURE IN A
SPECIFIC ORDER IS KNOWN AS SORTING. THERE ARE MANY
ALGORITHMS THAT CAN BE USED TO PERFORM SORTING, FOR
EXAMPLE, INSERTION SORT, SELECTION SORT, BUBBLE SORT, ETC.
• MERGING: WHEN TWO LISTS LIST A AND LIST B OF SIZE M AND
N RESPECTIVELY, OF SIMILAR TYPE OF ELEMENTS, CLUBBED OR
JOINED TO PRODUCE THE THIRD LIST, LIST C OF SIZE (M+N),
THEN THIS PROCESS IS CALLED MERGING
ALGORITHM
• AN ALGORITHM IS A PROCEDURE HAVING WELL DEFINED STEPS FOR SOLVING A
PARTICULAR PROBLEM.
• ALGORITHM IS FINITE SET OF LOGIC OR INSTRUCTIONS, WRITTEN IN ORDER FOR
ACCOMPLISH THE CERTAIN PREDEFINED TASK.
• IT IS NOT THE COMPLETE PROGRAM OR CODE, IT IS JUST A SOLUTION (LOGIC) OF A
PROBLEM, WHICH CAN BE REPRESENTED EITHER AS AN INFORMAL DESCRIPTION USING A
FLOWCHART OR PSEUDO CODE.
• THE MAJOR CATEGORIES OF ALGORITHMS ARE GIVEN BELOW:
1. SORTING
2. SEARCHING
3. DELETION
4. INSERTION
5. UPDATING
•
1. TIME COMPLEXITY:
2. SPACE COMPLEXITY:
•
1. INPUT:
2. OUTPUT:
3. FEASIBILITY:
4. INDEPENDENT:
5. UNAMBIGUOUS:
Intro to data structures.pptx

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Intro to data structures.pptx

  • 1.
  • 2. INTRODUCTION • DATA STRUCTURE CAN BE DEFINED AS THE GROUP OF DATA ELEMENTS WHICH PROVIDES AN EFFICIENT WAY OF STORING AND ORGANIZING DATA IN THE COMPUTER SO THAT IT CAN BE USED EFFICIENTLY. • DATA STRUCTURES ARE WIDELY USED IN ALMOST EVERY ASPECT OF COMPUTER SCIENCE I.E. OPERATING SYSTEM, COMPILER DESIGN, ARTIFICIAL INTELLIGENCE, GRAPHICS AND MANY MORE.
  • 3. NEED OF DATA STRUCTURES • PROCESSOR SPEED: TO HANDLE VERY LARGE AMOUNT OF DATA, HIGH SPEED PROCESSING IS REQUIRED, BUT AS THE DATA IS GROWING DAY BY DAY TO THE BILLIONS OF FILES PER ENTITY, PROCESSOR MAY FAIL TO DEAL WITH THAT MUCH AMOUNT OF DATA. • DATA SEARCH: CONSIDER AN INVENTORY SIZE OF 106 ITEMS IN A STORE, IF OUR APPLICATION NEEDS TO SEARCH FOR A PARTICULAR ITEM, IT NEEDS TO TRAVERSE 106 ITEMS EVERY TIME, RESULTS IN SLOWING DOWN THE SEARCH PROCESS. • MULTIPLE REQUESTS: IF THOUSANDS OF USERS ARE SEARCHING THE DATA SIMULTANEOUSLY ON A WEB SERVER, THEN THERE ARE THE CHANCES THAT A VERY LARGE SERVER CAN BE FAILED DURING THAT PROCESS
  • 4. ADVANTAGES OF DATA STRUCTURES • EFFICIENCY: EFFICIENCY OF A PROGRAM DEPENDS UPON THE CHOICE OF DATA STRUCTURES. FOR EXAMPLE: SUPPOSE, WE HAVE SOME DATA AND WE NEED TO PERFORM THE SEARCH FOR A PARTICULAR RECORD. IN THAT CASE, IF WE ORGANIZE OUR DATA IN AN ARRAY, WE WILL HAVE TO SEARCH SEQUENTIALLY ELEMENT BY ELEMENT. HENCE, USING ARRAY MAY NOT BE VERY EFFICIENT HERE. • REUSABILITY: DATA STRUCTURES ARE REUSABLE, I.E. ONCE WE HAVE IMPLEMENTED A PARTICULAR DATA STRUCTURE, WE CAN USE IT AT ANY OTHER PLACE. IMPLEMENTATION OF DATA STRUCTURES CAN BE COMPILED INTO LIBRARIES WHICH CAN BE USED BY DIFFERENT CLIENTS. • ABSTRACTION: DATA STRUCTURE IS SPECIFIED BY THE ADT WHICH PROVIDES A LEVEL OF ABSTRACTION. THE CLIENT PROGRAM USES THE DATA STRUCTURE THROUGH INTERFACE ONLY, WITHOUT GETTING INTO THE IMPLEMENTATION DETAILS.
  • 6. LINEAR • A DATA STRUCTURE IS CALLED LINEAR IF ALL OF ITS ELEMENTS ARE ARRANGED IN THE LINEAR ORDER. IN LINEAR DATA STRUCTURES, THE ELEMENTS ARE STORED IN NON-HIERARCHICAL WAY WHERE EACH ELEMENT HAS THE SUCCESSORS AND PREDECESSORS EXCEPT THE FIRST AND LAST ELEMENT. • TYPES OF LINEAR DATA STRUCTURES ARE GIVEN BELOW: 1. ARRAYS: AN ARRAY IS A COLLECTION OF SIMILAR TYPE OF DATA ITEMS AND EACH DATA ITEM IS CALLED AN ELEMENT OF THE ARRAY. THE DATA TYPE OF THE ELEMENT MAY BE ANY VALID DATA TYPE LIKE CHAR, INT, FLOAT OR DOUBLE. 2. LINKED LIST: LINKED LIST IS A LINEAR DATA STRUCTURE WHICH IS USED TO MAINTAIN A LIST IN THE MEMORY. IT CAN BE SEEN AS THE COLLECTION OF NODES STORED AT NON-CONTIGUOUS MEMORY LOCATIONS. EACH NODE OF THE LIST CONTAINS A POINTER TO ITS ADJACENT NODE. 3. STACK: STACK IS A LINEAR LIST IN WHICH INSERTION AND DELETIONS ARE ALLOWED ONLY AT ONE END, CALLED TOP. 4. QUEUE: QUEUE IS A LINEAR LIST IN WHICH ELEMENTS CAN BE INSERTED ONLY AT ONE END CALLED REAR AND DELETED ONLY AT THE OTHER END CALLED FRONT.
  • 7. OPERATIONS ON DATA STRUCTURE • TRAVERSING: EVERY DATA STRUCTURE CONTAINS THE SET OF DATA ELEMENTS. TRAVERSING THE DATA STRUCTURE MEANS VISITING EACH ELEMENT OF THE DATA STRUCTURE IN ORDER TO PERFORM SOME SPECIFIC OPERATION LIKE SEARCHING OR SORTING. • INSERTION: INSERTION CAN BE DEFINED AS THE PROCESS OF ADDING THE ELEMENTS TO THE DATA STRUCTURE AT ANY LOCATION. • DELETION: THE PROCESS OF REMOVING AN ELEMENT FROM THE DATA STRUCTURE IS CALLED DELETION. WE CAN DELETE AN ELEMENT FROM THE DATA STRUCTURE AT ANY RANDOM LOCATION.
  • 8. • SEARCHING: THE PROCESS OF FINDING THE LOCATION OF AN ELEMENT WITHIN THE DATA STRUCTURE IS CALLED SEARCHING. THERE ARE TWO ALGORITHMS TO PERFORM SEARCHING, LINEAR SEARCH AND BINARY SEARCH. • SORTING: THE PROCESS OF ARRANGING THE DATA STRUCTURE IN A SPECIFIC ORDER IS KNOWN AS SORTING. THERE ARE MANY ALGORITHMS THAT CAN BE USED TO PERFORM SORTING, FOR EXAMPLE, INSERTION SORT, SELECTION SORT, BUBBLE SORT, ETC. • MERGING: WHEN TWO LISTS LIST A AND LIST B OF SIZE M AND N RESPECTIVELY, OF SIMILAR TYPE OF ELEMENTS, CLUBBED OR JOINED TO PRODUCE THE THIRD LIST, LIST C OF SIZE (M+N), THEN THIS PROCESS IS CALLED MERGING
  • 9. ALGORITHM • AN ALGORITHM IS A PROCEDURE HAVING WELL DEFINED STEPS FOR SOLVING A PARTICULAR PROBLEM. • ALGORITHM IS FINITE SET OF LOGIC OR INSTRUCTIONS, WRITTEN IN ORDER FOR ACCOMPLISH THE CERTAIN PREDEFINED TASK. • IT IS NOT THE COMPLETE PROGRAM OR CODE, IT IS JUST A SOLUTION (LOGIC) OF A PROBLEM, WHICH CAN BE REPRESENTED EITHER AS AN INFORMAL DESCRIPTION USING A FLOWCHART OR PSEUDO CODE. • THE MAJOR CATEGORIES OF ALGORITHMS ARE GIVEN BELOW: 1. SORTING 2. SEARCHING 3. DELETION 4. INSERTION 5. UPDATING
  • 10. • 1. TIME COMPLEXITY: 2. SPACE COMPLEXITY:
  • 11. • 1. INPUT: 2. OUTPUT: 3. FEASIBILITY: 4. INDEPENDENT: 5. UNAMBIGUOUS: