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The base problem is manageable if you've seen it before.
Start by clearly defining authentication and authorization, emphasizing that authentication verifies identity while authorization determines access rights. Then, illustrate the distinction with a concrete example, such as a user logging in (authentication) and then accessing a specific resource (authorization). Finally, discuss how they work together in a secure system, mentioning common protocols and best practices.
Pro tip: Relate the concepts to a real-world scenario like Amazon's IAM or API Gateway to show practical understanding. Also, mention that authentication always precedes authorization, but authorization can be context-dependent and dynamic.
Explain that authentication is the process of verifying a user's identity, typically through credentials like passwords, biometrics, or tokens.
Explain that authorization is the process of determining what an authenticated user is allowed to do, often based on roles, policies, or permissions.
Emphasize that authentication is a prerequisite for authorization; you must know who the user is before deciding what they can access.
Give a concrete example, such as a user logging into a system (authentication) and then being granted access to specific API endpoints based on their role (authorization).
Mention common technologies and standards, like OAuth 2.0 for authorization, OpenID Connect for authentication, and how they integrate in modern applications.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Ran through encapsulation, inheritance, polymorphism, abstraction.
Classic OOD question and I knew it going in, which helped.
Start by clarifying the requirements: capacity, operations (get, put), and eviction policy. Then, describe the optimal data structure combination: a hash map for O(1) access and a doubly linked list for O(1) updates and evictions. Walk through the implementation details, including edge cases like updating existing keys and handling capacity limits.
Pro tip: Mention thread-safety considerations upfront, as production caches often need concurrent access. Also, discuss potential optimizations like using a sentinel head/tail to simplify edge cases.
Ask about expected capacity, operations (get, put), and eviction policy (LRU). Confirm that get and put should be O(1) time complexity.
Explain that a hash map alone is insufficient because it doesn't track order. Propose a combination: hash map for key-to-node mapping and a doubly linked list for recency order.
Detail how get and put work: on get, move the accessed node to the front (most recent); on put, add new node to front, and if capacity exceeded, remove the least recent node (tail).
Discuss updating an existing key (update value and move to front), and handling capacity of 0 or 1. Also, consider thread-safety if needed.
Conclude that both get and put are O(1) time and O(capacity) space. Mention that this is optimal for LRU cache.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.