Q91. What is the diamond problem and how do languages solve it?
The diamond problem occurs when a class inherits from two classes that share a common ancestor, so the same base members are inherited along two paths. Ambiguity arises o...
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Q92. What is the multiple comparisons problem?
When you run many hypothesis tests, the chance of at least one false positive grows quickly. With 20 independent tests at alpha 0.05, the probability of a false positive ...
Q93. What is data leakage in machine learning?
Data leakage is when information unavailable at prediction time seeps into training, producing optimistic validation scores that collapse in production. Common sources: -...
Q94. How do you handle hot keys in a distributed cache?
A hot key is accessed so frequently that a single cache node or partition becomes a bottleneck. Keys are distributed by consistent hashing, but one key always maps to one...
Q95. How do you revoke a JWT before it expires?
A stateless JWT cannot be un-issued, so revocation needs supporting state. Options: - Denylist: store revoked token identifiers (`jti`) until their `exp`, and check on ea...
Q96. How does Kafka provide exactly-once semantics?
Kafka combines two features: - Idempotent producer: each producer gets a producer id and sequence numbers. The broker deduplicates retries within a session, so a network ...
Q97. How does the CAP theorem affect microservice design?
CAP states that during a network partition a distributed system must choose between consistency (every read sees the latest write) and availability (every request gets a ...
Q98. When is REST the wrong choice, and what would you use instead?
REST excels at resource-oriented CRUD with cacheable, uniform interfaces and a broad tool ecosystem. It becomes awkward when: - The domain is action-oriented or RPC-like,...
Q99. How would you design a test strategy for a microservices system?
Testing a distributed system needs a layered strategy, because full end-to-end coverage does not scale. - Unit tests per service for domain logic, run on every commit. - ...
Q100. How would you scale a relational database as traffic grows?
Scaling relational databases follows a progression, because a single node eventually hits CPU, memory or I/O limits. 1. Optimise first: fix queries, add indexes, tune the...