What Is Evaluated in a Machine Coding Round?
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.
Here are the key areas evaluated in a Machine Coding Interview.
1. Requirement Understanding
Before writing code, you need to clearly understand what the system is supposed to do.
Interviewers look at how you identify:
- Functional requirements
- User actions
- Inputs and outputs
- Business rules
- Constraints
- Edge cases
For example, in a Parking Lot problem, you should clarify what is mentioned in the question — 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.
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.
You should be comfortable with:
- Classes and objects
- Interfaces
- Abstraction
- Encapsulation
- Inheritance
- Polymorphism
- Composition
The important question is not just:
"Which classes should I create?"
It is:
"Which class should be responsible for what?"
Good OOP design keeps responsibilities clear and reduces unnecessary coupling.
3. SOLID Principles
SOLID principles help you write code that is easier to maintain and extend.
The five principles are:
- Single Responsibility Principle
- Open/Closed Principle
- Liskov Substitution Principle
- Interface Segregation Principle
- Dependency Inversion Principle
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.
Focus on:
- Meaningful names
- Small, focused methods
- Clear abstractions
- Separation of responsibilities
- Avoiding duplicate code
- Avoiding unnecessary complexity
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.
For example:
"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.
The interviewer wants to know:
"Can your code evolve when requirements change?"
6. Design Patterns
Design patterns can help solve common design problems.
Some commonly useful patterns include:
- Strategy
- Factory
- Observer
- Builder
- State
- Command
But don't use a pattern just because you know it.
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.
Depending on the problem, you might use:
- Array / ArrayList
- HashMap
- HashSet
- Queue
- Stack
- Priority Queue
- Tree
- Graph
The interviewer may also ask about time complexity, space complexity, lookup performance, and memory usage.
Choose the data structure based on the problem rather than using one by default.
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.
You should understand concepts such as:
- Thread safety
- Race conditions
- Atomicity
- Synchronization
- Locks
- Deadlocks
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
A strong Machine Coding solution should:
Understand the requirements → Design the objects → Write clean code → Apply SOLID where useful → Make the system extensible → Choose the right data structures → Handle concurrency when required.
The goal is not to write the most complicated solution.
The goal is to write a clean, working, and extensible solution that can evolve as requirements change.