{"podcast":{"title":"Software Engineer Interview Prep Podcast","slug":"software-engineer-interview-prep-podcast-7756520","podcast_index_feed_id":7756520,"rss_url":"https://anchor.fm/s/10f2c0f8c/podcast/rss","website_url":"https://podcasters.spotify.com/pod/show/prabuddha-ganegoda","image_url":"https://d3t3ozftmdmh3i.cloudfront.net/staging/podcast_uploaded_nologo/45395131/45395131-1771326099446-dba64f511934f.jpg","author":"Prabuddha Ganegoda","episode_count":35,"summary":"Ace your Software Engineer interviews with confidence. This podcast helps you organize your thinking, strengthen problem-solving skills, and prepare effectively for real technical interviews. Topics covered include: Programming (Java & Python) Data Structures & Algorithms System Design AI for Software Engineers Interview strategies & mindset Whether you're targeting Big Tech, startups, or senior engineering roles, each episode helps you think clearly, solve better, and perform at your best.","last_synced_at":"2026-06-09T02:20:02.878789+00:00","page_url":"https://stenobird.com/podcast/software-engineer-interview-prep-podcast-7756520"},"episode":{"title":"[DSA] Sliding Window Algorithm","slug":"dsa-sliding-window-algorithm","published_at":"2026-03-13T11:26:20+00:00","page_url":"https://stenobird.com/podcast/software-engineer-interview-prep-podcast-7756520/dsa-sliding-window-algorithm","show_page_url":"https://stenobird.com/podcast/software-engineer-interview-prep-podcast-7756520","url":"https://podcasters.spotify.com/pod/show/prabuddha-ganegoda/episodes/DSA-Sliding-Window-Algorithm-e3gcps1","audio_url":"https://anchor.fm/s/10f2c0f8c/podcast/play/116860225/https%3A%2F%2Fd3ctxlq1ktw2nl.cloudfront.net%2Fstaging%2F2026-2-13%2F419929944-44100-2-e2cecaa05f701.mp3","summary":"The Sliding Window Algorithm is a powerful technique used to reduce the time complexity of problems involving arrays or strings—specifically those that require finding a sub-segment that meets certain criteria. Instead of using nested loops O(n^2), the sliding window maintains a dynamic range that "slides" across the data, usually bringing the complexity down to O(n). Problem:Find the maximum sum of a contiguous subarray of size `k`. public class SlidingWindow { public static int findMaxSum(int[] arr, int k) { int n = arr.length; if (n < k) return -1; int windowSum = 0; // 1. Compute sum of the first window for (int i = 0; i < k; i++) { windowSum += arr[i]; } int maxSum = windowSum; // 2. Slide the window from index k to n-1 for (int i = k; i < n; i++) { // Add the next element, remove the first element of the previous window windowSum += arr[i] - arr[i - k]; maxSum = Math.max(maxSum, windowSum); } return maxSum; } }","meta_description":"The Sliding Window Algorithm is a powerful technique used to reduce the time complexity of problems involving arrays or strings—specifically those that re…","key_points":[],"chapters":[],"topics":[],"duration_seconds":371,"processing_state":"not_requested","actions":[{"name":"request_transcript","method":"POST","url":"https://stenobird.com/v1/public/podcasts/software-engineer-interview-prep-podcast-7756520/episodes/dsa-sliding-window-algorithm/transcription-requests","description":"Idempotently request low-priority transcript generation for this episode."},{"name":"read_markdown","method":"GET","url":"https://stenobird.com/podcast/software-engineer-interview-prep-podcast-7756520/dsa-sliding-window-algorithm.md","description":"Read the agent-friendly Markdown representation of this episode resource."}]}}