What do you do if your algorithm interview requires you to showcase clean and efficient code?

1. Requirement clarification & scope the problem 2. Think loudly - Keep sharing what you are thinking to interviewer 3. Explain the approach & note down everything 4. Write functional program 5. Once done, test with edge case This should be enough to get green signal.

1. Understand the problem thoroughly. 2. Plan a clear and efficient approach. 3. Use descriptive variable names. 4. Write modular code. 5. Avoid redundancy. 6. Follow coding conventions. 7. Handle edge cases robustly. 8. Utilize built-in functions and libraries. 9. Optimize algorithms and data structures. 10. Test code with various cases. 11. Optimize for readability. 12. Seek feedback for improvements.

The best and safest approach would be to discuss potential solution with the interviewer before jumping to code. The most common mistake people do is to start coding right away as soon as they finish reading the problem. While you discussing the approach, you can ask any occurring questions as well, such as for instance if you are given array, if values are unique or not etc. After you finish explaining the approach mention about Time complexity and Space complexity, and ask if this approach is okay with the interviewer and if you are good to jump into coding. While coding, it is better to also leave related comments. Good luck!

1. Understand the Problem: Clarify all doubts upfront for a solid start. 2. Plan Before Coding: Use pseudocode to map out your solution. 3. Clear Naming: Choose descriptive names for clarity. 4. Simplicity: Aim for clean, straightforward code. Comment Wisely: Explain the 'why' in your comments. 5. Follow Conventions: Stick to language standards and styles. 6. Thoughtful Optimization: Optimize for efficiency without losing clarity. 7. Handle Edge Cases: Make your code robust for various scenarios. 8. Refactor: Streamline and clean your code once it works. 9. Test Thoroughly: Validate with multiple test cases. 10. Explain Your Process: Clearly articulate your methods and reasoning.

1.Would highly recommend you to use the SOLID principle for explaining clean and efficient code. 2.Relax and give time to grasp the problem and explain what ever coming to your mind to the interviewer regarding that algorithm in clear and louder way. 3.Interviewer is not concerned about the solution, he is concerned about the approaches you are presenting in a better way and how well you are using those approaches to reach to the efficient solution. 4. Have good understanding of fundamentals. Because if basics are not clear, then you can't deliver an efficient code.

When writing code in an interview, make sure you give proper name to properties, methods, classes asper coding standards. So interviewer can understand your approach of the problem. Add comments wherever it’s necessary so that interviewer can understand the logic of the line of code.

Standard naming convention with proper and minimal inline docs covers 80% of this. Rest depends on implementation details like code smells and etc. Its always better to keep explaining the interviewer `what you are implementing` or `what you are going to implement`.

When writing the actual code, focus on writing clean, readable, and well-structured code. Follow best practices such as using descriptive variable names, proper indentation, consistent formatting, and meaningful comments to explain the logic where necessary.

Use meaningful and descriptive names for variables, functions, classes, and modules. Follow conventions like CamelCase for class names (MyClass), snake_case for function and variable names (my_function, my_variable), and uppercase for constants. Use consistent and appropriate indentation (usually 4 spaces or a tab) to show the structure of your code. Group related code together and separate logical sections with blank lines to improve readability. Add comments to explain complex logic, algorithms, or code blocks that might not be immediately clear to others (or even yourself in the future!). Write clear and concise docstrings for functions and classes to describe their purpose, parameters, return values, and any exceptions they may raise.

Its always good to lead with the solution which comes up early, many of the times we could visualize the enhancements while writing the code.

Many a times people start to think about the best solution and that’s wrong. You will not be able to reach to the best solution at once. It can be sometimes and not always. The very first thing is that you should understand the problem and the requirement and try building a naive solution around it. Once that is done they look at your code and try optimising it. It can happen that you are having a lot of unnecessary iterations which are not required. So you can reduce them and save running time of your code. So in this way you will finally reach an optimised solution.

Start with brute-force solution. It's not necessary to code it, but important just to highlight it and discuss. Working brute-force solution better then no solution at all. Then analyze it pain points and inefficient time / memory complexity, and think loud how you can optimize it. Let interviewer agree or disagree with you, and base on that propose a new solution or code a more efficient one that came up. It will allow you solve the problem from the fist perspective and eventually come up with more efficient solution if it exists.

In the high-pressure environment of an interview, it's tempting to dive straight into optimizing your code for efficiency. However, a more prudent approach is to focus on creating a solution that works first. Premature optimization can lead to convoluted and hard-to-read code, consuming valuable interview time and detracting from the clarity of your solution. Once you've devised a working solution, take a step back and analyze its time and space complexity. This step is crucial for identifying areas where optimization is needed. Look for opportunities to streamline your code by eliminating redundant calculations, leveraging more efficient data structures, or applying dynamic programming techniques if applicable.

When writing your code it is necessary to test the functionality of the actual outcome which matches with the requirements. Make sure to test all the scenarios including the edge cases like service is down or any null values which can break the code. This helps to pass a bug free code in later stages of deployment

Set aside the case of mass hiring, and you are just numbers on papers. We focus on showing our logical thinking process to the interviewer and complete the problem along the way. And as the target is "clean and efficient," state that your thought process is also helping. The interviewer will understand your idea and approach and sometimes can help point out the problem if have. Sure, your code can "talk" but adding more value with your communication skills will also help you gather more information.

A candidate's experience is reflected through their consistent coding style, which enhances navigability as our minds are adept at recognizing abstract patterns within seemingly random elements. Ultimately, a coding style can be supported by either the integrated configuration of an IDE or ingrained muscle memory, both of which are beneficial.

We have so many articles for interviews. This topic focuses on cleanliness and efficiency. So the takeaway here is: + Make your thought process clear to the interviewer. + Come from a basic solution and then go on to improve it. + Make progress with your own style and lead the conversation with the flow of code. And in the end, build up your confidence through practice.

Develop your solutions using a modular approach where possible. This involves breaking down the problem into smaller, manageable components or functions that can be tested and debuged independently. For example, in preparing for an interview focused on data structures, I practiced creating distinct functions for each major operation within a data structure (e.g., add, delete, search) which made my overall code cleaner and easier to understand. Refactor your code after your initial solution, helps improve code readability & efficiency by simplifying complex sections. During one particular algorithm interview, I initially wrote a somewhat convoluted solution to a sorting problem; refactored it, significantly simplifying the logic.

- Avoid distractions: If something is not working, isolate it, replace with any working solution, maybe keep it as TODO, and move on. Again, emphasis on getting a working solution and then figure out the rest. - Practice: Get into the practice mode, try to simulate the interview environment while preparing like keep a time limit, enforce explanation, etc. - Confident: Trust in your skills and the practice you've put in. Exhibit your problem-solving abilities and adaptiveness. Confidence stems from both technical knowledge and effective communication.

One of interesting factor to consider is comprehension skills to understand question quickly and completely along with debugging skill to fix issues (if any). I know incidents where people were rated very good for DSA in Google interview, still rejected because of average debugging and comprehension skills.