Tree Practice Question

Duration: 2 min

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Inside: a video lesson and guided study material.

Module outline

  1. Quantitative Ability: Percentage, Profit and Loss, Ratio and Proportion (Ratios), Average, Time and Work, Speed Time and Distance, Simple Interest and Compound Interest, Age Problems, Number System, Divisibility Rules, HCF LCM, Algebra, Permutation and Combination, Probability, Data Interpretation, Logarithm, Sequence and Series (Series), Powers and Exponents (Surds and Indices), Speed Mathematics and Basic Mathematics
  2. Logical Reasoning: Seating Arrangements, Puzzle Solving (Puzzles), Data Arrangement, Coding Decoding, Blood Relations, Directions (Direction Test), Ranking, Order and Sequence, Data Sufficiency, Venn Diagram, Inequality, Series (Number and Letter Series) (Numerical Relations and Reasoning), Logical Sequence Of Words, Deductive and Inductive Reasoning (Logical Deduction and Induction) (Prepositional Reasoning), Selection Decision Table (Decision Making), Analogy, Non Verbal Reasoning (Spatial Aptitude) (Spatial Reasoning) (Visual Reasoning)
  3. Verbal Ability: Comprehension / Reading Comprehension / Unseen Passages (Critical Reasoning) (Paragraph Questions), Subject Verb Agreement (Verb Noun Agreement), Tenses, Articles, Preposition, Conjunction, Modals, Active Passive Voice (Voice), Direct and Indirect Speech, Vocabulary, Sentence Re-arrangements (Para Jumbles) (Narrative Sequencing), Sentence Completion (Fill in the blanks), Sentence Correction (Error Correction), Cloze Test (Cloze Passage), Facts, Inference and Judgements
  4. Programming Fundamentals (Technical): C Fundamentals
  5. Data Structures (Technical): Introduction to DS, Array, Stack, Queue, Linked List, Tree, Graphs, Hashing
  6. Algorithms (Technical): Algorithm Analysis, Sorting Algorithms, Greedy Algorithms, Dynamic Programming, Minimum Spanning Trees, Shortest Path Algos, Time Complexity Analysis, Advanced Algorithms
  7. OOPs (Technical): Object Oriented Programming (OOPS)
  8. DBMS (Technical): Basics of DBMS, ER Diagram, Relational Model & Functional Dependencies, Keys & Integrity Constraints, Normalization (1NF - BCNF), Decomposition Properties & 4NF, File Organization & Indexing, Relational Algebra, Relational Calculus, Transaction Management, Concurrency Control, Database Recovery, ORDBMS, Database Security & Authorization, Query Processing & Optimization, Enhanced Data Models, Data Warehousing & Mining, Big Data Systems, NoSQL
  9. SQL (Technical): SQL
  10. Operating Systems (Technical): Introduction to OS, Process Management, CPU Scheduling, Process Synchronization, Deadlock, Threads & Process Creation, Memory Management, Virtual Memory, Disc Scheduling, File Management, Windows OS, Linux OS, Security, Distributed Systems, Virtual Machines
  11. Computer Networks (Technical): Introduction to CN, Data Communication, 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, Network Security, Mobile Technology, Cloud Computing and IoT, Cyber and Info Security
  12. Software Engineering (Technical): Fundamentals of Software Engineering, Software Requirements and Quality Assurance, Software Design, Estimation and Metrics, Software Testing, Software Maintenance and Configuration Management
  13. Coding/Automata Round: Coding Questions by Yash Sir, C Programming by Yash Sir, Programming in C++, Java, Python for Placements by Yash Sir, Pseudo Codes
  14. Personality / Behavioral Assessment: Behavioral Assessment (Behavioral Competency Profiling) (Psychometric Test)
  15. Writing Assessment: English Writing Ability
AI summary & chapters

AI Summary

An AI-generated summary of this video lecture.

The video presents an academic lecture analyzing a C function operating on a binary tree structure. The instructor displays a multiple-choice question asking for the function's behavior. The code defines a recursive function `fun` that returns 0 for NULL roots and leaf nodes, but returns `1 + fun(left) + fun(right)` for other nodes. The options suggest the function counts leaf nodes, internal nodes, returns height, or returns diameter. The instructor methodically evaluates the code against these options to determine the correct answer.

Chapters

  1. 0:00 – 2:00 00:00-02:00

    The instructor introduces the problem, displaying the code snippet `int fun(struct node *root)`. He underlines the recursive line `return 1 + fun(root->left) + fun(root->right)`. He draws a small tree diagram with a root and two children to test the logic. He points out that the condition `if (root->left == NULL && root->right == NULL)` returns 0, which contradicts option (A) "Counts leaf nodes" since leaves would return 0 instead of 1. He begins to hypothesize that the function might be counting internal nodes based on the `1 +` addition. He also briefly considers option (C) regarding height but dismisses it because height usually involves `max`, not `sum`.

  2. 2:00 – 2:25 02:00-02:25

    The instructor focuses on the return value `1` in the recursive step. He traces the execution for the drawn tree: the root is not a leaf, so it returns `1 + fun(left) + fun(right)`. Since the children are leaves, their function calls return 0. Thus, the total is `1 + 0 + 0 = 1`. This confirms the function counts the root as one internal node. He explicitly crosses out options (A), (C), and (D), concluding that the function counts internal nodes, making (B) the correct answer. He emphasizes that the summation `fun(left) + fun(right)` aggregates the counts from subtrees.

The lesson progresses from code analysis to logical deduction using a concrete example. By observing that leaf nodes return 0 and internal nodes add 1 to the sum of their subtrees, the instructor proves the function calculates the total count of internal nodes in the binary tree. This method of tracing base cases and recursive steps is a standard technique for analyzing tree algorithms.

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