Practice Question

Duration: 2 min

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Module outline

  1. Discrete Mathematics: Set Theory, Relations, Functions, Graph Theory, Group Theory, Propositional and Predicate Logic
  2. DataBase Management System/DBMS: Basics of DBMS, ER Diagram, Relational Model & Functional Dependencies, Keys & Integrity Constraints, Normalization (1NF - BCNF), Decomposition Properties & 4NF, File Organization & Indexing, Relational Algebra, SQL, Relational Calculus, Transaction Management, Concurrency Control
  3. Digital Electronics: Digital Systems & Boolean Basics, Logic Gates & Hardware, Boolean Expression, Boolean Minimization, Combinational Circuit, Sequential Circuits, Number System, Number Representation
  4. Computer Architecture: Floating Point Rep, Cache Memory Organization, Input Output Organisation, Pipelining, Instr Formats & Modes, Control Unit Design
  5. Operating System: Introduction to OS, Process Management, CPU Scheduling, Process Synchronization, Threads & Process Creation, Deadlock, Memory Management, Virtual Memory, Disc Scheduling, File Management
  6. C Language: C Fundamentals, Control Flow, Functions, Arrays & Pointers, Storage Classes, Structures & Enums, DMA, Macros, Scoping & File Handling
  7. Data Structures: Introduction to DS, Array, Stack, Queue, Linked List, Tree, Graphs, Hashing
  8. Algorithms: Algorithm Analysis, Time Complexity Analysis, Sorting Algorithms, Greedy Algorithms, Dynamic Programming, Minimum Spanning Trees, Shortest Path Algos
  9. Computer Networks: Introduction to CN, DLL: Access Control, DLL: Flow Control, DLL: Error Control, DLL: Framing, Data Link Layer - Ethernet, Net Layer: IPv4 & Proto, Net Layer: IP Addressing, Net Layer:Routing Protocol, Transport Layer Services, TL: Congestion & UDP, Application Layer, Hardware Basics
  10. Theory Of Computation/Automata Theory: Introduction to TOC, Deterministic FA (DFA), Non-Deterministic FA, Regular Expressions, Grammar, Regular Language Properties, Moore & Mealy Machines, Pushdown Automata & CFG, Turing Machines, Complexity Theory
  11. Compiler Design: Intro to Compilers, Lexical Analysis, Grammar & CFG, Syntax Analysis: Top-Down, Syntax Analysis: Bottom-Up, Semantic Analysis & SDT, Intermediate Code Gen, Code Optimization, Run Time Environment
  12. Engineering Mathematics: Permutation and Combination, Linear Algebra, Calculus, Probability, Statistics
  13. General Aptitude: Ratio and Proportion (Ratios), Divisibility Rules, Data Interpretation, Logarithm, Number System, HCF LCM, Sequence and Series (Series), Speed Time and Distance, Series (Number and Letter Series) (Numerical Relations and Reasoning), Coding Decoding, Data Sufficiency, Non Verbal Reasoning (Spatial Aptitude) (Spatial Reasoning) (Visual Reasoning), Percentage, Mensuration and Geometry, Mental Ability, Arithmetic, Profit and Loss, Powers and Exponents (Surds and Indices), Average, Deductive and Inductive Reasoning (Logical Deduction and Induction) (Prepositional Reasoning), Syllogisms, Venn Diagram, Seating Arrangements, Blood Relations, Directions (Direction Test), Analogy, Algebra, Time and Work, Analytical Reasoning (Counting Figures Reasoning), Puzzle Solving (Puzzles), Cubes & Dices, Ranking, Order and Sequence, Mixture and Alligation, Age Problems, Clock, Selection Decision Table (Decision Making), Data Arrangement
  14. English (Verbal Aptitude): Vocabulary, Noun, Subject Verb Agreement (Verb Noun Agreement), Adjectives, Tenses, Pronoun, Preposition, Direct and Indirect Speech, Sentence Re-arrangements (Para Jumbles) (Narrative Sequencing), Sentence Completion (Fill in the blanks), Comprehension / Reading Comprehension / Unseen Passages (Critical Reasoning) (Paragraph Questions), Sentence Correction (Error Correction), Verbal Analogy (Word Based Analogy), Conjunction, Interjection, Verb, Articles, Adverb, Modals, Sentence Construction
  15. Live Classes Recordings(Earlier Batch): GATE 2026 Live Class
  16. Full Mock Test:
  17. Previous Year Papers:
  18. GATE 2026 Counselling: Counselling and Guidance Sessions
AI summary & chapters

AI Summary

An AI-generated summary of this video lecture.

The video presents a problem from a computer science lecture regarding the Quicksort sorting algorithm. The central question asks the viewer to identify the pivot element after the first partitioning step of an array containing eight integers: 2 5 1 7 9 12 11 10. He begins by writing out the array elements on the screen to visualize the data structure. He draws brackets underneath the left segment 2 5 1 and the right segment 12 11 10 to emphasize the partitioning boundaries. He then analyzes the properties of a valid Quicksort partition. For an element to be a pivot, all elements to its left must be smaller, and all elements to its right must be larger. He first considers the number 7. Observing the array, the elements to the left are 2, 5, and 1, which are all less than 7. The elements to the right are 9, 12, 11, and 10, which are all greater than 7. This confirms that 7 is a valid pivot. Next, he examines the number 9. The elements to its left are 2, 5, 1, and 7, all of which are smaller than 9. The elements to its right are 12, 11, and 10, all of which are larger than 9. This confirms that 9 is also a valid pivot. Based on this analysis, the instructor concludes that the pivot could be either 7 or 9. He marks option (A) "The pivot could be either the 7 or the 9" as the correct answer.

Chapters

  1. 0:00 – 1:36 00:00-01:36

    The video opens with a static slide displaying a problem statement about Quicksort partitioning. The text reads: 'Suppose we are sorting an array of eight integers using quicksort, and we have just finished the first partitioning with the array looking like this: 2 5 1 7 9 12 11 10.' The instructor then writes the numbers on the board. He draws blue brackets under the left group 2 5 1 and the right group 12 11 10. He circles the number 9. He analyzes the conditions for a pivot. He checks option (A).

The lesson connects the theoretical definition of Quicksort partitioning with practical problem-solving. By visually isolating the left and right sub-arrays, the instructor clarifies that the pivot's position is not fixed to a specific index but is defined by the values of its neighbors. The fact that both 7 and 9 satisfy the condition highlights that the partitioning process depends on the specific arrangement of elements. The final selection of option (A) reinforces the concept that multiple valid pivots can exist for a given partitioned state, provided the ordering constraints are strictly met, which is a key takeaway for understanding algorithmic flexibility.

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