Spring Boot Interview Question: Batch Normalization API

Normalization, Performance, CPU bound, Code samples and more.

Scenario

You are building a data analytics service that receives numeric metrics from various clients and normalizes them into a fixed range before further processing.

This service will expose a REST API that accepts a batch of numeric values and returns the normalized results.

Problem Statement

1. Create a Spring Boot REST API with a POST endpoint /normalize.

2. The endpoint should accept a JSON payload:

{
  "values": [50, 75, 120, -10],
  "targetMin": 0,
  "targetMax": 1
}

The API should return the normalized values as a JSON array:

[0.5, 0.875, 1.0, 0.0]

The API should handle edge cases:

• Empty arrays

• All identical values (map to middle of target range)

• Inverted target ranges (e.g., [1,0])

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Solution

From the problem statement , it feels like we need to focus on 3 things:

• Data modeling – defining the input and output.

• Normalization logic – how we actually compute normalized values.

• Exposing the API – building a Spring Boot endpoint for clients.

Data modeling

For the request, we should define a DTO with:

• An array of doubles, values

• targetMin and targetMax

This keeps the API flexible, since clients can normalize into any range they want.