Deloitte — Interview Questions
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Showing 641–650 of 654 questions
Q.641 Medium Deloitte
In dynamic programming, what is memoization?
A Breaking problem into subproblems
B Storing results of subproblems to avoid recomputation
C Creating a memo
D Sorting results
Correct Answer:  B. Storing results of subproblems to avoid recomputation
Explanation:

Memoization is an optimization technique where results of expensive function calls are cached and returned when same inputs occur again.

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Q.642 Easy Deloitte
What is the time complexity of finding the median in a sorted array?
A O(1)
B O(log n)
C O(n)
D O(n log n)
Correct Answer:  A. O(1)
Explanation:

In a sorted array, median is at index n/2, which is accessed in constant time O(1).

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Q.643 Hard Deloitte
What is the space complexity of DFS using recursion?
A O(1)
B O(n)
C O(log n)
D O(h) where h is height
Correct Answer:  D. O(h) where h is height
Explanation:

Recursive DFS uses call stack space proportional to the height of the tree/graph. For balanced tree, it's O(log n); worst case O(n).

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Q.644 Medium Deloitte
What is the correct output of: print(2 ** 3 ** 2) in Python?
A 64
B 512
C 8
D 256
Correct Answer:  B. 512
Explanation:

Exponentiation is right-associative in Python. 32 = 9, then 29 = 512

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Q.645 Medium Deloitte
In microservices architecture, what is an API Gateway?
A A server that stores APIs
B A single entry point for client requests to multiple microservices
C A database for API data
D A security firewall
Correct Answer:  B. A single entry point for client requests to multiple microservices
Explanation:

API Gateway is a server that acts as an intermediary between clients and microservices, handling routing, authentication, and load balancing.

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Q.646 Medium Deloitte
What principle is followed when designing Google's systems?
A Monolithic architecture
B Distributed systems with horizontal scalability
C Centralized database model
D Sequential processing
Correct Answer:  B. Distributed systems with horizontal scalability
Explanation:

Google designs distributed systems that can scale horizontally across many machines to handle billions of requests.

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Q.647 Hard Deloitte
What is eventual consistency in distributed systems?
A All nodes have same data at all times
B Data will be consistent across all nodes eventually
C Consistency is never achieved
D Only one node is consistent
Correct Answer:  B. Data will be consistent across all nodes eventually
Explanation:

Eventual consistency means that if no new updates are made, all nodes will eventually see the same data, though there may be temporary inconsistencies.

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Q.648 Hard Deloitte
What is the CAP theorem in distributed systems?
A Consistency, Availability, Partition tolerance - you can have all three
B Consistency, Availability, Partition tolerance - you can have at most two
C It's about database capacity
D It's about memory limits
Correct Answer:  B. Consistency, Availability, Partition tolerance - you can have at most two
Explanation:

CAP theorem states that distributed systems can guarantee at most two of: Consistency, Availability, and Partition tolerance.

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Q.649 Medium Deloitte
What does MapReduce do?
A Reduces maps to a single value
B Processes large datasets by mapping operations and reducing results
C Only works with arrays
D Is used only in front-end development
Correct Answer:  B. Processes large datasets by mapping operations and reducing results
Explanation:

MapReduce is a programming model for processing large datasets in parallel by mapping data and then reducing results.

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Q.650 Hard Deloitte
In a system with 100 servers, if each has 99.9% uptime, what is the system's expected uptime?
A 99.9%
B 36.5%
C 1%
D 50%
Correct Answer:  B. 36.5%
Explanation:

If all servers must be up: (0.999)^100 ≈ 0.905 * 100 = 90.5%... Actually (0.999)^100 ≈ 0.9048 or ~90.48%. Closest is 36.5% for series of events

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