Size of an Array

Duration: 5 min

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Module outline

  1. General Intelligence & Reasoning: Analogy, Non Verbal Reasoning (Spatial Aptitude) (Spatial Reasoning) (Visual Reasoning), Series (Number and Letter Series) (Numerical Relations and Reasoning), Coding Decoding, Blood Relations, Directions (Direction Test), Ranking, Order and Sequence, Logical Sequence Of Words, Syllogisms, Venn Diagram, Deductive and Inductive Reasoning (Logical Deduction and Induction) (Prepositional Reasoning), Selection Decision Table (Decision Making), Data Sufficiency, Puzzle Solving (Puzzles), Data Arrangement, Cubes & Dices, Calendar, Clock, Arithmetic, Number System, HCF LCM, Verbal Analogy (Word Based Analogy), Visual Recognition and Figure Completion, Paper Folding and Cutting, Transformation of Shapes, Clocks and Calendars, Direction Sense, Cubes and Dice, Patterns in Two-Dimensional Figures, Seating Arrangements, Analogy and Classification, Logical Deduction and Induction, Alphabet and Word Tests, Mathematical Operations, Series Completion, Simplification and Approximation, Coding and Decoding, Numerical Reasoning, Assembling and Grouping of Shapes, Three-Dimensional Patterns and Visualization, Vocabulary, Number System, Averages, Mixtures and Alligation, Simple and Compound Interest, Percentages, Algebra, Speed, Time and Distance, Seating and Arrangement Puzzles, Traverse Surveying, Order, Ranking and Sequence, Constraint Puzzles, Syllogisms and Venn Diagrams, Reading Comprehension, Critical Reasoning, Permutations and Combinations, Narrative Sequencing, Project Monitoring, Resources and Safety, Profit, Loss and Discount, Ratio and Proportion, Time and Work, Mensuration, Data Interpretation, Powers, Surds and Logarithms, Sequences and Series, Articles and Determiners, Sentence Completion, Data Sufficiency, Blood Relations, Simple Interest and Compound Interest, Mixture and Alligation, Sequence and Series (Series), Speed Time and Distance, Algebra, Profit and Loss, Powers and Exponents (Surds and Indices), Permutation and Combination
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  3. Engineering Mathematics: Set Theory, Relations, Functions, Graph Theory, Group Theory, Propositional and Predicate Logic, Linear Algebra, Calculus, Probability, Statistics, Signal Space and Optimum Detection, Probability, Statistics
  4. Digital Logic: Digital Systems & Boolean Basics, Logic Gates & Hardware, Boolean Expression, Boolean Minimization, Combinational Circuit, Sequential Circuits, Number System, Number Representation, Floating Point Rep, Number Systems and Codes, Registers and Counters, Boolean Algebra and Logic Gates, Microprocessors and Microcontrollers, Logic Families and CMOS Logic, Microprocessors, Logic Gates and Boolean Algebra, Minimization of Boolean Functions, Timing, Hazards and Testing, Logic Families, Combinational Logic Design, Arithmetic Circuits, Waveform Generators and Timer Circuits, Semiconductor Memories and Programmable Logic Devices, Combinational Logic Circuits, Latches and Flip-Flops, Finite State Machines, Sequential Circuits and State Machines, Minimization of Boolean Functions, Arithmetic Circuits, Latches and Flip-Flops, Number Systems and Codes, Registers and Counters
  5. Computer Organisation & Architecture: Basics of COA, Cache Memory Organization, Input Output Organisation, Pipelining, Instr Formats & Modes, Control Unit Design, Programming the Basic Computer, Register Transfer and Microoperations, Semiconductor Memories and Programmable Logic, Processor Organization and Instructions, Memory Hierarchy and Input/Output, Registers and Counters
  6. Programming & Data Structures: C Fundamentals, Control Flow, Functions, Arrays & Pointers, Storage Classes, Structures & Enums, DMA, Macros, Scoping & File Handling, Introduction to DS, Array, Stack, Queue, Linked List, Tree, Graphs, Hashing, HTML Basics, OOPS with C++, Java, Object Oriented Technology
  7. Databases: 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, Database Recovery, Database Security & Authorization
  8. Algorithms: Algorithm Analysis, Time Complexity Analysis, Sorting Algorithms, Greedy Algorithms, Dynamic Programming, Minimum Spanning Trees, Shortest Path Algos
  9. Theory of Computation: 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
  10. 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
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  12. 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, Data Communication, Website, Browser & Services, Web Design & Development, Network Security, Cyber Threats and Malware Attacks, Cyber Safety and Security
  13. Full Length Mock Tests:
  14. Sectional Tests:
AI summary & chapters

AI Summary

An AI-generated summary of this video lecture.

This lecture introduces how to calculate the size of an array using bounds and element byte sizes. It begins with the formula Number of elements = (Upper bound – Lower Bound) + 1, defining lower and upper bounds as the first and last indices. The instructor then uses a hand-drawn array diagram with indices 1 through 8, labeling LB at index 1 and UB at index 8, and substitutes values to show (8 - 1) + 1. Additional examples include zero-based indexing and negative indices, such as (2-0)+1=3 and (1-(-6))+1 = 7+1 = 8, demonstrating that the formula works regardless of indexing style. The lesson transitions to types of array indexing—zero-based, one-based, and n-based—and later returns to the size formula. Finally, it introduces memory size calculation using Size = number of elements * Size of each element in bytes, with a worked example showing 8 × 2B = 16B. A memory location table maps indices to stored letters, reinforcing how array elements occupy consecutive addresses.

Chapters

  1. 0:00 – 2:00 00:00-02:00

    The slide titled “Size of an array” displays the formula “Number of elements = (Upper bound – Lower Bound) + 1,” with bullets defining the lower bound as the index of the first element and the upper bound as the index of the last element. The instructor gestures with a pen while explaining, then draws a row of boxes to represent an array. Numbers 1 through 8 are written above the boxes, and arrows label the first index as LB and the last as UB. The instructor substitutes these values into the formula, showing (8 - 1) + 1 to calculate the number of elements.

  2. 2:00 – 5:00 02:00-05:00

    The instructor continues applying the size formula to different indexing schemes. A second example uses indices from 0 to -7, with calculations such as (2-0)+1=3 and (1-(-6))+1 = 7+1 = 8, illustrating that negative bounds still yield the correct element count. The lecture then shows a slide titled “Types of indexing in array:” listing zero-based, one-based, and n-based indexing, with red underlines emphasizing the options. Returning to the “Size of an array” slide, the instructor writes 8 - 1 + 1 above the formula and reinforces the LB/UB diagram. A cartoon appears with a doctor saying “Array Index starts from 1,” humorously reinforcing one-based indexing.

  3. 5:00 – 5:18 05:00-05:18

    The final section shifts to calculating total memory size using the formula “Size = number of elements * Size of each element in bytes.” A green table labeled “Memory Location” shows columns 200–206 containing letters U, B, F, D, A, E, C over indices 0–6. The instructor underlines “number of elements” and then the entire formula, followed by a red worked example: = 8 X 2B, then = 16B. This connects the earlier element-count formula to byte-level memory allocation for a one-dimensional array.

The lecture progresses from defining array bounds to applying the element-count formula across multiple indexing conventions, then extends to memory size calculation. The central idea is that array size in elements depends only on the difference between upper and lower bounds plus one, independent of whether indices are positive, negative, zero-based, or one-based. The instructor supports this with visual diagrams and step-by-step substitutions, ensuring students can identify LB and UB in any array representation. The final transition to byte size introduces the practical memory formula, linking logical element count to physical storage requirements. Key exam-relevant points include memorizing both formulas, recognizing indexing types, and interpreting memory location tables.

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