@ankurm

Ankur in DSF

Implementing Doubly Linked List in Java

A Doubly Linked List (DLL) is a linked data structure where each node holds a value and two pointers: one pointing to the next node and one pointing to the previous node. This bidirectional linkage enables forward and reverse traversal — something a singly linked list cannot do without extra memory. A doubly-linked list: each node stores a value, a link to the next node, and a link to the previous node. In this post, we implement a DLL in Java that supports insertion at the first position, last position, after a given position, and before a given position — as well as deletion, search, and both forward and reverse display.

Ankur in DSF

Implementation of Circular Queue in Java with Array

A Circular Queue (also called a Ring Buffer) is a queue data structure that treats its underlying array as if it were connected end-to-end in a circle. Unlike a linear queue, once the rear pointer reaches the end of the array, it wraps back to index 0 — allowing reuse of freed slots without shifting elements. This post implements a true circular queue in Java using an array, with proper wraparound logic for both the front and rear pointers. How a Circular Queue Works Both front and rear start at -1 (empty state). Enqueue: Advance rear with wraparound: rear = (rear + 1) % size. The queue is full when (rear + 1) % size == front. Dequeue: Advance front with wraparound: front = (front + 1) % size. Reset both to -1 when the last element is removed. Circular property: Elements can be added to index 0 again after front has moved past it.

Ankur in DSF

Implementing Binary Search Tree in Java

A Binary Search Tree (BST) is a node-based binary tree data structure where each node stores a key, and every node in the left subtree holds a key strictly smaller than the parent, while every node in the right subtree holds a key strictly greater. This ordering property makes BSTs excellent for fast lookup, insertion, and deletion — all in O(log n) time on average. In this post, we implement a BST in Java that supports insertion, search, and three traversal orders: inorder, preorder, and postorder. BST Properties One node is designated the root of the tree. Each internal node contains a key and has at most two child subtrees. The left subtree of a node contains only keys strictly less than the node's key. The right subtree of a node contains only keys strictly greater than the node's key. Each subtree is itself a valid BST.

Ankur in DSF

Evaluating Postfix Expression with Java

Postfix notation (also called Reverse Polish Notation or RPN) is a mathematical notation where every operator follows all of its operands. For example, the infix expression 3 + 4 becomes 3 4 + in postfix. This eliminates the need for parentheses and operator precedence rules, making it ideal for stack-based evaluation. In this post, we implement a Java program that evaluates a postfix expression using a stack. The program reads the expression as a string and produces the integer result.

Ankur in AOAD

Program to Implement KMP Algorithm in Java

In this post, we’ll explore how to implement the Knuth-Morris-Pratt (KMP) string matching algorithm in Java. The KMP algorithm is an efficient way to search for a substring within a given string. It improves upon the brute-force approach by skipping over unnecessary comparisons after partial matches. What is the Knuth-Morris-Pratt (KMP) Algorithm? The KMP algorithm searches for a substring (pattern) in a larger string (text) efficiently by avoiding redundant comparisons. The key idea behind KMP is that when a mismatch happens, it uses previously gathered information about the pattern to shift the search window instead of starting from scratch. The algorithm uses two main components: Failure Function (Prefix Table): It helps determine how much the pattern should shift when a mismatch occurs. Search Process: Once the failure function is computed, the algorithm searches through the text to find the pattern.

Ankur in AOAD

Program to Implement K-Naive Algorithm in Java

In this post, we’ll implement the K-Naive (Brute-Force) string matching algorithm in Java. This is the simplest form of string search, where we check for the presence of a pattern in a text by checking one by one at every possible position. What is the K-Naive (Brute-Force) Algorithm? The Brute-Force algorithm searches for a substring (pattern) within a larger string (text) by checking for a match at every position in the text. It is simple to understand and implement but can be inefficient for large inputs.

Ankur

Quote

जगातील गोष्टी पाहाव्यात, ऐकाव्यात आणि "नशिबात नाही" अशी मनाला समजूत घालून विसरून जाव्यात! जग सुंदर आहे कारण ते तुमचं नाही... जगातील अनेक गोष्टी सुंदर आहेत कारण त्या तुमच्या नाहीत!

Ankur

Mediatech: ४ महिने थोडक्यात

Mediatech... वडाळा येथे असलेलेली छोटीशी web development कंपनी. ऑफिस antop hill warehouse मध्ये. सोमवार २३ जून २०१४ रोजी मी या कंपनीत रुजू झालो व ७ नव्हेंबर २०१४ रोजी कंपनीमधून रजा घेतली. तसा कार्यकाल फक्त ४ महिने आणि काही दिवसांचा! पण हा वेळ अनेक विविधरूपी आठवणींनी भरलेला होता. Technical आणि developer point of view ने तर बऱ्याच आठवणी आहेत परंतु इतरही काही किस्से सांगण्यालायक आहेत.

Ankur in AOAD

Java Program for Longest Common Subsequence (LCS) Problem

Learn how to solve the Longest Common Subsequence (LCS) problem in Java using dynamic programming. Includes a CC diagram, annotated DP table, traceback explanation, sample output, and a step-by-step output walkthrough.

Ankur

Mediatech: एक अनुभव

वय वर्षे २२. महाविद्यालयीन शिक्षणपूर्ण झाल्यावर वारे वाहू लागतात ते म्हणजे नोकरीचे. आणि आजच्या जगात मनाला हवी तशी नोकरी मिळणे हा तर नशिबाचा भाग. मी कदाचित इतका भाग्यवान नसेन पण त्या काळात नशिबाने मला खरोखरच साथ दिली. ३ जून २०१४. ४ थ्या वर्षाच्या ८ व्या सेमिस्टरचा पेपर झाला. जवळपास college life संपलं असे म्हणण्यास काही हरकत नाही. दुसरा भाग म्हणजे मी काही 'बेरोजगार' नव्हतो. College campus मधून TCS मध्ये placement झाली होती. त्यामुळे घरातल्यांचा तसा काही दबाव नव्हता कि अंकुर नोकरीचं बघ म्हणून! TCS आज न् उद्या बोलवेल त्यामुळे तसं काही tension देखील नव्हतं.