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Home/Machine Coding/Machine coding Tutorial/What Is Evaluated in a Machine Coding Round?
Chapters — Machine coding Tutorial▾

What Is Evaluated in a Machine Coding Round?

4 min read·Sep 6, 2026
Keywords:Machine Coding RoundLow Level Design

What is evaluated in a machine coding round? Learn the 8 evaluation areas — OOP, SOLID, clean code, extensibility, testing and more.

What Is Evaluated in a Machine Coding Round? — Machine coding Tutorial
What is evaluated in a machine coding round? Learn the 8 evaluation areas — OOP, SOLID, clean code, extensibility, testing and more.

A Machine Coding Round evaluates more than just whether your code works. Interviewers want to see how you understand requirements, design a solution, write clean code, and handle changing requirements.

Lens

How you understand → design → code → evolve matters more than just making tests pass.

1. Requirement Understanding

Before writing code, you need to clearly understand what the system is supposed to do.

Requirement signals
Signal
What to clarify
Functional requirements
Core actions the system must support
User actions
Who does what, step by step
Inputs and outputs
Request payloads and response shapes
Business rules
Invariants and domain constraints
Constraints
Limits, capacities, and time boxes
Edge cases
Empty, full, invalid, duplicate flows
Example — Parking Lot

For a Parking Lot problem, clarify number of floors, vehicle types, parking spot types, assignment rules, ticket generation, and what happens when the parking lot is full.

For anything not clearly specified, it is okay to make an assumption — state it explicitly at that time, but make sure the assumption can be changed easily if any requirement changes later.

Rule

Don't start coding before you understand the requirements.

2. Object-Oriented Programming

OOP is one of the most important parts of a Machine Coding Round.

OOP building blocks
Concept
What to get right
Classes and objects
Model real entities with clear boundaries
Interfaces
Define contracts for pluggable behaviour
Abstraction
Hide implementation behind intention-revealing APIs
Encapsulation
Protect invariants; expose only what is needed
Inheritance
Use sparingly for true is-a extension
Polymorphism
Swap behaviours without branching everywhere
Composition
Build has-a relationships over deep hierarchies
Key question

Which class should be responsible for what? Good OOP keeps responsibilities clear and reduces unnecessary coupling.

3. SOLID Principles

SOLID principles help you write code that is easier to maintain and extend.

SOLID
Principle
When to use
Single Responsibility
One reason to change per class
Open/Closed
Extend via new types, not by editing existing ones
Liskov Substitution
Subtypes behave as their base type promises
Interface Segregation
Small, focused interfaces over fat ones
Dependency Inversion
Depend on abstractions, not concrete classes
Don't force

You don't need to force SOLID into every solution. Use these principles when they make your code simpler, cleaner, and easier to change.

4. Clean Code

Interviewers also evaluate whether your code is clean and easy to understand.

Clean code signals
Signal
What to do
Meaningful names
Domain language, not temp/v1
Small, focused methods
One intent per method, easy to test
Clear abstractions
Models and services have sharp boundaries
Separation of responsibilities
Split where change is likely
Avoid duplicate code
Share via composition, not copy-paste
Avoid unnecessary complexity
No cleverness that obscures flow

A working solution is not enough if everything is written inside one large class.

5. Extensibility

Machine Coding problems often introduce new requirements after you finish the basic implementation.

Example twist

"Your payment system currently supports Credit Card. Now add UPI." Your design should allow you to add UPIPayment without rewriting the entire system.

This is where abstraction, interfaces, composition, dependency injection, and design patterns can help.

Test

Can your code evolve when requirements change?

6. Design Patterns

Design patterns can help solve common design problems.

Useful patterns
Pattern
Typical use
Strategy
Swap pricing, payment, or fee algorithms
Factory
Create families of related objects
Observer
Notify on state changes
Builder
Assemble complex request/response objects
State
Model slot, ticket, or booking lifecycles
Command
Encapsulate actions for undo or retry
Keep it simple

Use the simplest design that solves the problem. Good design is not about using more patterns — it is about using the right abstraction at the right place.

7. Data Structures

Machine Coding is not a DSA interview, but choosing the right data structure still matters.

Choosing structures
Structure
Use when
Array / ArrayList
Ordered, index-based iteration
HashMap
Fast lookup by ID or key
HashSet
Uniqueness and membership checks
Queue
FIFO ordering or processing
Stack
LIFO or backtracking
Priority Queue
Priority-based access
Tree / Graph
Hierarchies or relations between entities

Choose the data structure based on the problem rather than using one by default. The interviewer may also ask about time complexity, space complexity, lookup performance, and memory usage.

8. Concurrency

For advanced Machine Coding problems, interviewers may evaluate how you handle multiple operations happening at the same time.

For example, two users may try to book the same seat simultaneously.

Concurrency concepts
Concept
Why it matters
Thread safety
Shared state behaves correctly
Race conditions
Prevent interleaving bugs
Atomicity
All-or-nothing transitions
Synchronization
Guard critical sections
Locks
Protect the right resource, not everything
Deadlocks
Avoid circular waits

The important part is not adding locks everywhere, but understanding which shared resources need protection and why. A good solution should maintain data consistency even when multiple operations happen concurrently.

In Short

In short

A strong Machine Coding solution nails the same loop every time:

Understand → Design → Code clean → Apply SOLID judiciously → Keep it extensible → Pick the right structure → Guard concurrency only where needed.

Not the most complex — the cleanest, working, and future-proof solution wins. Build it so the next requirement is a small diff, not a rewrite.

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On this page
  • 1. Requirement Understanding
  • 2. Object-Oriented Programming
  • 3. SOLID Principles
  • 4. Clean Code
  • 5. Extensibility
  • 6. Design Patterns
  • 7. Data Structures
  • 8. Concurrency
  • In Short