Day 27: Review All Topics Covered in the Last Month
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1. Objective of Day 27
The goal for Day 27 is to review all the topics you’ve covered over the past month in preparation for the SDE 2 interview at Google. This day is about reinforcing key concepts, identifying areas where further refinement is needed, and ensuring you are well-prepared for the final stretch of your preparation. The review should cover system design, data structures and algorithms, and advanced topics like those discussed earlier in Week 4.
2. System Design Review
System design is a major component of the SDE 2 interview at Google, so it’s essential to ensure you understand the core principles of designing scalable, reliable systems.
a. Key Principles of System Design:
Scalability: Ensure your designs can scale horizontally (adding more machines) or vertically (upgrading machines). Review strategies for sharding, load balancing, and caching.
Reliability: Review fault tolerance mechanisms such as data replication, failover strategies, and how systems handle downtime or partial failures.
Consistency and Availability: Revisit the CAP theorem (Consistency, Availability, Partition Tolerance) and the trade-offs involved in distributed systems.
Latency and Performance Optimization: Understand techniques to reduce latency, such as caching, using CDNs, and optimizing database queries.
b. Key Topics to Review:
Database Design: SQL vs. NoSQL, normalization, denormalization, and indexing strategies.
Caching Strategies: Types of caches (e.g., Redis, Memcached), cache invalidation strategies, and how caching can reduce load on databases.
Load Balancing: Review strategies for distributing traffic across servers (e.g., Round Robin, Least Connections, IP Hashing).
APIs and Microservices: REST vs. gRPC, best practices for designing scalable APIs, and microservices communication patterns (e.g., synchronous vs. asynchronous).
Messaging Systems: Event-driven architectures, message brokers (e.g., Kafka, RabbitMQ), and how to handle event streams efficiently.
Security: Review authentication (OAuth 2.0, JWT), data encryption, rate limiting, and security best practices.
c. Action Item:
Review any notes or system design projects you’ve worked on during the past month, and make sure you understand key trade-offs for each component in your designs.
3. Data Structures and Algorithms Review
Data structures and algorithms are a crucial part of the interview process. For SDE 2 interviews, you are expected to have a deep understanding of the fundamentals and be able to solve problems efficiently.
a. Key Data Structures:
Arrays and Strings: Review common algorithms (e.g., sliding window, two-pointer technique) for problems involving arrays and strings.
Linked Lists: Revisit problems like reversing a linked list, detecting cycles, and merging sorted lists.
Stacks and Queues: Focus on problems like balanced parentheses, implementing stacks/queues using other data structures, and monotonic stacks.
Trees and Graphs:
Review tree traversals (preorder, inorder, postorder, level order) and key algorithms like depth-first search (DFS) and breadth-first search (BFS).
Revisit binary search trees, AVL trees, and problems involving graph traversals, such as shortest path algorithms (Dijkstra, Bellman-Ford).
Heaps: Understand how to implement a heap and solve problems related to priority queues, such as finding the k largest/smallest elements in a list.
Hashing: Review hash tables and common problems involving hash maps, such as two-sum, frequency counting, and finding duplicates.
b. Key Algorithms:
Sorting and Searching: Quick Sort, Merge Sort, Binary Search, and problems that involve custom sorting.
Dynamic Programming: Revisit the most common dynamic programming patterns such as the knapsack problem, longest common subsequence, and maximum subarray problems.
Greedy Algorithms: Review greedy problems like interval scheduling, Huffman encoding, and the coin change problem.
Backtracking: Revisit problems like the N-Queens problem, Sudoku solver, and subsets/permutations generation.
Graph Algorithms: Ensure familiarity with algorithms for detecting cycles, finding connected components, and pathfinding (BFS, DFS, Dijkstra, Floyd-Warshall).
c. Action Item:
Practice Problems: Use platforms like LeetCode, HackerRank, or Codeforces to solve a few medium to hard-level problems from each of these categories. Focus on writing clean, optimal code and improving time and space complexity.
Review the Big-O complexities of all common data structures and algorithms to ensure you can explain why certain approaches are more efficient than others.
4. Advanced Topics Review
In Week 4, you explored advanced system design topics like Blockchain, Serverless Architectures, Event-Driven Architecture, Microservices, and Distributed Systems. It’s important to revisit these advanced topics to ensure you can discuss them fluently in an interview setting.
a. Key Topics to Revisit:
Blockchain: How and where blockchain might be useful in a system (e.g., data immutability, decentralized applications). Understand the trade-offs and limitations of blockchain in terms of performance and scalability.
Serverless Architecture: Benefits of using serverless functions for cost-efficient, scalable systems and the potential downsides like cold start latency and execution time limits.
Event-Driven Architecture: Review how event-driven architectures work, with a focus on message brokers, asynchronous communication, and eventual consistency.
Microservices Architecture: Understand the benefits of microservices (e.g., independent deployment, scalability) and the challenges (e.g., inter-service communication, database consistency).
Distributed Systems and Consensus: Review consensus algorithms like Paxos and Raft, and understand when to apply them in distributed systems.
b. Action Item:
Write a short summary of each advanced topic and how it might apply to real-world systems. Think about trade-offs (e.g., when to use microservices vs. monoliths, when blockchain might add value to a system).
5. Interview Strategy and Mock Interviews
Today is also a good time to revisit your interview strategy. Focus on improving the way you approach and communicate your solutions in interviews.
a. Interview Framework:
Clarify the Problem: Before jumping into solving a problem, take time to understand the requirements. Clarify any ambiguities or edge cases with the interviewer.
Break the Problem Down: Decompose the problem into smaller, more manageable parts, especially for complex system design questions.
Explain Your Approach: Whether solving an algorithmic problem or a system design question, explain your thought process clearly. This shows your reasoning and makes it easier for the interviewer to follow your approach.
Optimize Gradually: Start by solving the problem in the simplest way, then work towards optimizing it. This shows that you can balance time to implementation with the need for optimization.
Test Your Solution: Once you’ve written your code or explained your design, make sure to test it thoroughly (e.g., with edge cases, stress tests).
b. Practice Mock Interviews:
If possible, schedule a mock interview (either with a peer, mentor, or an online service like Pramp, Interviewing.io, or Exponent). This will help simulate real interview conditions and give you feedback on how well you are communicating your solutions.
Focus on both coding and system design questions during the mock interview, as both are important for SDE 2 positions.
6. Reflection and Self-Evaluation
After reviewing the topics, reflect on your strengths and areas for improvement. Ask yourself:
Strengths: What areas do you feel confident in? Which problems or system design concepts do you solve efficiently?
Weaknesses: Which topics need further revision? Are there specific data structures or advanced topics you’re less confident in?
Time Management: Are you solving algorithmic problems within the expected time limits (typically 30–45 minutes)? Can you articulate a system design solution in 45–60 minutes?
Action Item:
Plan Final Review: Based on your self-evaluation, create a final review plan for Day 28 to focus on weak areas and fine-tune your approach.
7. Next Steps for Day 27
Comprehensive Review: Go over all the topics and projects you’ve worked on during the past month.
Practice Coding Problems: Solve problems from each major category (data structures and algorithms) to reinforce your skills.
Mock Interview: If possible, schedule or participate in a mock interview to get real-time feedback.
Prepare Final Notes: Summarize key points for each topic in preparation for your final day of mock interviews and practice on Day 28.
By the end of Day 27, you should have refreshed your understanding of core concepts and identified key areas for improvement, ensuring you are fully prepared for your final review and practice on Day 28.
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