Here's how you can apply problem-solving techniques to different programming languages.

In my view whether you choose specific programming language over another depends on your specific problem scenario. Regardless of which language you choose, the first step in problem solving would be understanding the problem, and then develop a best algorithm (in terms of time and space complexity ) for it. After that you may have more than one data structure to implement the algorithm, but you must choose the one that best suits your algorithm (as the choice of data structure also affects both running time and space complexity of your algorithm.) and implement it. lastly you must test and debug your program.

Based on my experiences in the software development journey, problem-solving techniques can be applied across different programming languages. The key is to understand the core concepts and logic behind the problem. Once you grasp these fundamentals, you can adapt your solutions to any language. It's all about breaking down the problem, planning your approach, and then translating that plan into code. The principles remain the same whether you're using JavaScript, C++, Java, or any other language. Experience across multiple languages also broadens your toolkit, giving you more strategies to tackle complex problems effectively.

For every problem, in almost most cases, at least two programming languages can be chosen. The important thing is to understand the problem at the beginning. Now you can choose the programming language based on the problem solving method.

Understanding the basics before starting coding and development is crucial for several reasons: Foundational Knowledge Strong Foundation: Basics provide a solid foundation upon which more complex concepts are built. Understanding fundamental principles ensures you can grasp advanced topics more easily. Core Concepts: Core programming concepts such as variables, loops, conditionals, functions, and data structures are essential for writing efficient and effective code. Code Efficiency: Knowing the basics helps write more efficient code. Understanding how algorithms and data structures work allows you to optimize performance and resource usage. Overall knowing the basics would definitely reduce your stress in debugging the rookie errors. ??

Tips for Applying Problem-Solving Techniques Across Languages: Language Paradigms: Understand the paradigms (procedural, object-oriented, functional) and use them appropriately. Standard Libraries: Familiarize yourself with the standard libraries and frameworks available in each language for common tasks. Community and Resources: Engage with the language community (forums, Stack Overflow) to learn best practices and efficient solutions. Practice: Regularly solve problems in different languages to build fluency and versatility.

Yes! You don't need a specific programming language to solve problems! Just think in an abstract way and then try to apply the solution to your technology using the best and techniques available!

Designing an algorithm is a straightforward process. The first step is to understand the problem thoroughly, ask the following questions, - Why is this an issue? - What are the requirements? - What is the goal? - What do I need to achieve this goal? Now with all these questions answered, grab a pen and paper and, depending on your problem, start with a top-down or bottom-up approach. Break the problem down into smaller chunks and start writing your pseudocode to solve all of those chunks one by one until you reach your end goal.

Debugging skills highly depend on the amount of experience you have because with experience you start recognising patterns which eventually leads to solving problems quickly so the more you code the better you get. But once in a while you do get a dreaded edge case which is difficult to spot. In these cases go back to your basics and do not view your code as whole divide it and go through each and every step.

By leveraging built-in methods, or simplifying complex code through techniques like DRY (Don't Repeat Yourself) and SRP (Single Responsibility Principle). In statically-typed languages like Swift, reducing force unwraps, and improving code structure through better use of enums, protocols, or generics. Engaging in code reviews with peers can also provide fresh perspectives and identify areas for improvement. Additionally, using automated refactoring tools and testing frameworks can help you validate changes and ensure that your refactoring efforts do not introduce new issues. By continuously applying refactoring techniques, you ensure that your solutions are not only correct but also clean, maintainable, and scalable for future development.

Refactoring enables you to restructure code without changing its behavior You can refactor code in many ways, which includes the following methods: - Don't Repeat Yourself (DRY): Write functions to ensure the repeated code is referenced from a single function. - Open / Closed Principle: Write code that is open for extension but closed for modification. - Single Responsibility: Every class in your codebase should deal with a single entity. - Dependency Inversion: Rather than creating dependencies internally, provide them from outside - Documentation: Write concise documentation for your code, code comments need to be short and to the point. These principles ensure your code is clean, scalable, portable and maintainable.

This approach often helps because once you know what your use cases are and what you are testing for , there will be less redundant and more optimised code