Searching An Element In Link List Using Loop

Duration: 5 min

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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.

This educational video lecture focuses on implementing iterative search algorithms for linked lists. The instructor begins by addressing the general problem of searching for a key in an unsorted linked list, providing pseudo-code that traverses the list node by node until the key is found or the end is reached. The lesson then progresses to a more optimized scenario: searching within a sorted linked list arranged in increasing order. Here, the instructor demonstrates how the sorted property allows for an early termination condition. If the current node's value exceeds the target key, the search can immediately conclude that the key is not present, saving unnecessary iterations compared to the general linear search approach.

Chapters

  1. 0:00 – 2:00 00:00-02:00

    The instructor introduces the problem of writing pseudo-code to search for a key in a linked list iteratively. He displays a diagram of a linked list containing nodes 'a', 'b', 'c', and 'd'. The on-screen code defines a function `What` that takes a head pointer and a key. The logic initializes a pointer `ptr` to `head` and enters a `while` loop that continues as long as `ptr` is not NULL. Inside the loop, an `If` statement checks if `ptr->data` equals the `key`. If the condition is met, the function returns the current pointer. Otherwise, the `else` block executes `ptr = ptr->next` to move to the subsequent node. If the loop finishes without finding the key, the function returns NULL. The instructor traces this process by searching for 'c', showing `ptr` advancing from 'a' to 'b' and finally stopping at 'c' where the match is found.

  2. 2:00 – 5:00 02:00-05:00

    The lecture transitions to a modified problem: searching in a sorted linked list in increasing order. The diagram updates to show a list with values 10, 20, 30, and 40. The pseudo-code is revised to include an optimization. The `If` condition remains `ptr->data == key`. However, the `Else` block is split. An `Else if(ptr->data < key)` condition checks if the current value is smaller than the key; if so, it proceeds to the next node. Crucially, a final `Else` block handles the case where `ptr->data > key`. In this scenario, the code immediately returns NULL. The instructor explains that because the list is sorted, finding a value greater than the target key guarantees the key is not in the list. He traces a search for 25, showing the pointer moving past 10 and 20, but stopping at 30. Since 30 is greater than 25, the algorithm returns NULL, demonstrating the efficiency gain over the unsorted search.

The video effectively contrasts two search strategies for linked lists. The first method is a standard linear search applicable to any list structure, requiring a full traversal in the worst case. The second method leverages the sorted nature of the data to introduce a pruning condition. By checking if the current node's value exceeds the target, the algorithm can terminate early, avoiding unnecessary comparisons. This progression highlights how data structure properties, such as ordering, can be exploited to optimize algorithmic performance.

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