Model Question Paper and Answers PCCST303 Data Structures and Algorithms

 

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Data Structures and Algorithms PCCST303 KTU 2024 Scheme- Dr Binu V P

About Me Syllabus and Evaluation Scheme  Model Question Paper and Answers PCCST303 Data Structures and Algorithms Try the following programs in lab to understand the theory better 1.Basic Concepts of Data Structures Stacks and Queues     Data Structures and Data Abstraction     Time and Space Complexity     Asymptotic Analysis and Asymptotic Notations     Best case, Worst case and Average Case Analysis of Algorithms     Frequency Count Method of Algorithm Analysis          Array as a Data Structure     Polynomial Representation using arrays      Polynomial Addition using arrays      Sparse Addition and Transpose     Stacks     Multi Stacks      Queue using array      Circular Queue using array      Double ended Queue using array     Infix to postfix and postfix evaluation     Infix to ...
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Memory Allocation - First Fit

  Memory Allocation Strategy When a program requests memory from the operating system (OS) — say for creating variables, arrays, or objects — the OS must decide where in the memory to place this data. This decision-making is known as a Memory Allocation Strategy . In dynamic memory allocation, main memory (RAM) is managed in chunks called blocks . As programs request and release memory, the memory space gets fragmented into free and occupied blocks. So, an important task for the OS is to find an appropriate free block when a program requests memory. To manage this efficiently, different allocation strategies are used. First Fit Memory Allocation Strategy Definition : In the First Fit strategy, the OS searches from the beginning of memory and allocates the first free block that is large enough to satisfy the request. It doesn't check all blocks. As soon as a large enough block is found, allocation happens. Example : Assume free memory blocks of sizes: 200KB , 500KB ,...
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Performance Analysis - Time and Space Complexity

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  📚 Performance Analysis  Performance analysis means studying how efficient an algorithm or data structure is. Mainly, we check two things: Time Complexity — How much time (number of operations) the algorithm takes. Space Complexity — How much memory (space) the algorithm uses. ✅ Goal : To predict how the algorithm will behave as the input size grows without running the code. 📍 1. Time Complexity Measures the amount of time an algorithm takes to complete. It is expressed as a function of the input size n . We usually use Big-O notation (e.g., O(n), O(log n), O(n²)) to express it. ⏳ Why it matters? Because we want algorithms that are fast even for large inputs . Example for Time Complexity: Suppose we have a simple loop: for ( int i = 0 ; i < n; i++) { printf ( "%d " , i); } The loop runs n times . Each printf is a constant-time operation. So, Time Complexity = O(n) (linear time). Types of Common Time Complexities...
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