Searching An Element In LL Using Recursion

Duration: 5 min

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Module outline

  1. English Comprehension/Verbal Ability: Comprehension / Reading Comprehension / Unseen Passages (Critical Reasoning) (Paragraph Questions), Vocabulary, Sentence Correction (Error Correction), Sentence Completion (Fill in the blanks), Sentence Re-arrangements (Para Jumbles) (Narrative Sequencing), Subject Verb Agreement (Verb Noun Agreement), Tenses, Verb, Articles, Preposition, Conjunction, Pronoun, Noun, Adjectives, Adverb, Modals, Cloze Test (Cloze Passage), Active Passive Voice (Voice), Direct and Indirect Speech, Sentence Construction
  2. Logical Ability: Coding Decoding, Directions (Direction Test), Analogy, Inequality, Data Sufficiency, Series (Number and Letter Series) (Numerical Relations and Reasoning), Syllogisms, Seating Arrangements, Puzzle Solving (Puzzles), Blood Relations, Deductive and Inductive Reasoning (Logical Deduction and Induction) (Prepositional Reasoning), Ranking, Order and Sequence, Logical Sequence Of Words, Data Arrangement, Venn Diagram, Calendar, Clock
  3. Quantitative Ability: Logarithm, Permutation and Combination, Probability, Profit and Loss, Speed Time and Distance, Mixture and Alligation, Partnership, Simple Interest and Compound Interest, Percentage, Ratio and Proportion (Ratios), Average, Time and Work, Pipe and Cistern, Number System, Divisibility Rules, HCF LCM, Algebra, Powers and Exponents (Surds and Indices), Mensuration and Geometry, Age Problems, Data Interpretation, Sequence and Series (Series)
  4. Basic Analytical Ability: Non Verbal Reasoning (Spatial Aptitude) (Spatial Reasoning) (Visual Reasoning), Analytical Reasoning (Counting Figures Reasoning), Cubes & Dices, Selection Decision Table (Decision Making)
  5. Computer Programming: Pseudo Codes, Coding Questions by Yash Sir, C Programming by Yash Sir, Programming in C++, Java, Python for Placements by Yash Sir
  6. DBMS (Computer Science): Basics of DBMS, ER Diagram, Relational Model & Functional Dependencies, Keys & Integrity Constraints, Normalization (1NF - BCNF), Transaction Management, Concurrency Control, Database Security & Authorization
  7. SQL (Computer Science): SQL
  8. OS (Computer Science): Introduction to OS, Process Management, CPU Scheduling, Deadlock, Process Synchronization, Threads & Process Creation, Memory Management, Virtual Memory, File Management
  9. Computer Networks (Computer Science): 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
  10. Data Structures (Computer Science): Introduction to DS, Array, Stack, Queue, Linked List, Tree, Graphs, Hashing
  11. OOPs (Computer Science): Object Oriented Programming (OOPS)
  12. Software Engineering (Computer Science): Fundamentals of Software Engineering, Software Requirements and Quality Assurance, Software Design, Estimation and Metrics, Software Testing, Software Maintenance and Configuration Management
  13. SVAR Conversational - Spoken English: Communication Assessment
  14. HR Interview: MR & HR Interview Preparation
AI summary & chapters

AI Summary

An AI-generated summary of this video lecture.

This educational video lecture focuses on implementing a recursive search algorithm for a linked list. The instructor begins by presenting a specific problem statement requiring pseudo-code for searching a key recursively. He systematically constructs the function signature and base cases. The lesson progresses to discuss optimizations for sorted linked lists, demonstrating how to terminate the search early if the current node's value exceeds the target key, thereby improving efficiency compared to a standard linear search.

Chapters

  1. 0:00 – 2:00 00:00-02:00

    The instructor introduces the problem statement displayed on the screen: 'Write a pseudo code for searching a key in a link list recursively, where pointer head have the address of the first node of the list?'. He begins writing the function signature `*node What(node *head, int key)`. He establishes the base condition `if(head!=null)` to handle the end of the list. Inside the block, he writes the logic `If(head->data == key)` to check for a match. If a match is found, the code indicates `Return ptr;`. If not, the instructor explains the recursive step `What(head->next, key)` to move to the subsequent node in the list.

  2. 2:00 – 5:00 02:00-05:00

    The instructor refines the algorithm specifically for a sorted linked list to demonstrate optimization. He draws a diagram with nodes containing values 10, 20, 30, and 40, and sets the target key to 25. He modifies the code to include an `Else If(head -> data < key)` condition. This logic allows the function to continue searching only if the current data is less than the key. If the current data is greater than the key, the code executes `Return null;`, stopping the search early. He traces the execution flow: `W(10, 25)` calls `W(20, 25)`, which calls `W(30, 25)`. At the node with value 30, since 30 is greater than 25, the function returns null, proving the optimization works.

  3. 5:00 – 5:02 05:00-05:02

    The video concludes with the instructor finalizing the explanation of the sorted list search logic. He emphasizes the importance of the `Return null;` statement in the final else block, which handles the case where the key is not found or the list is exhausted. The screen displays the complete pseudo-code structure with the optimization logic clearly visible alongside the linked list diagram.

The lecture effectively transitions from a basic recursive search implementation to an optimized version for sorted data structures. By first establishing the fundamental recursive pattern of checking the current node and moving to the next, the instructor builds a solid foundation. The introduction of the sorted list optimization highlights a critical algorithmic concept: utilizing data properties (ordering) to prune the search space. The visual tracing of the function calls `W(10, 25)` through `W(30, 25)` provides a concrete example of how the recursion unwinds and terminates, reinforcing the theoretical explanation with practical execution flow.

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