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What are the most effective ways to identify areas of weakness in your algorithm design skills?

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Algorithm design skills are essential for solving complex problems, optimizing performance, and creating elegant solutions. However, how do you know if your skills are up to par, or if you need to improve them? In this article, we will share some effective ways to identify areas of weakness in your algorithm design skills, and how to address them.

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Satbir Singh

Software Engineer @ Microsoft | DAIICT | Mentor | Algorithm Design, Software Development | Large Scale Distributed…
Janani Jayaraman

Director of Product Management - Building lead to cash portfolio @ ServiceNow l Ex- Freshworks | Ex-Cisco
Ayush Singh

SDE II @Microsoft

1 Assess your current level

The first step is to assess your current level of algorithm design skills, and compare it with the expectations of your role, project, or goal. You can do this by taking online tests, solving coding challenges, reviewing your past work, or asking for feedback from peers or mentors. You should also be aware of the common algorithm design topics, such as data structures, sorting, searching, recursion, dynamic programming, greedy algorithms, graph algorithms, and so on. By assessing your current level, you will have a clear picture of your strengths and weaknesses, and where you need to focus your improvement efforts.

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Oleg Bourdo

Backend Software Engineer
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For checking your current level and compare it with others do not be afraid to participate in programming challenges and hackatons. It will make your view wilder and make the progress in your skills

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2 Review the fundamentals

The second step is to review the fundamentals of algorithm design, and make sure you understand the basic concepts, principles, and techniques. You should also refresh your knowledge of the relevant programming languages, tools, and frameworks that you use or plan to use. You can review the fundamentals by reading books, articles, blogs, or tutorials, watching videos, podcasts, or courses, or taking online classes or workshops. You should also practice applying the fundamentals to simple problems, and check your solutions for correctness, efficiency, and readability.

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Ayush Singh

SDE II @Microsoft
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Problem solving is an art, which gets more refined as you age with it. Don't consider it like a syllabus which you need to complete, it's more like a marathon (move steadily but continuously). Don't feel bad in spending time in understanding the problem i.e once you are presented with a problem you generally try to understand it quickly as you need to spare more time to think about the solution. (Don't do this) My take here is, don't rush for thinking about the solution. Give ample amount of time in understanding the problem itself, dry running the given examples etc. In the beginning it will feel like you are wasting lot of time but trust me this will improve as you keep climbing.

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3 Learn from others

The third step is to learn from others who have more experience or expertise in algorithm design, and see how they approach and solve problems. You can learn from others by reading their code, following their blogs, podcasts, or courses, joining their communities, forums, or groups, or asking them questions or advice. You should also try to analyze and compare their solutions with yours, and identify what you can learn from them. You can also learn from others by participating in code reviews, pair programming, hackathons, or competitions, and getting feedback on your work.

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4 Solve more problems

The fourth step is to solve more problems that challenge your algorithm design skills, and expose you to different scenarios, domains, and requirements. You can solve more problems by finding online platforms, websites, or apps that offer coding challenges, puzzles, or games, or by creating your own problems based on real-world situations or interests. You should also try to solve problems that cover a variety of algorithm design topics, levels of difficulty, and types of input and output. You should also practice solving problems under different constraints, such as time, space, or resources.

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Satbir Singh

Software Engineer @ Microsoft | DAIICT | Mentor | Algorithm Design, Software Development | Large Scale Distributed Systems
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In my experience algorithms are just another form of Mathematics of problem solving, just we train our computers to solve the real world problem using the logic. As we know we become smarter and better at mathematics just by practicing it more and more. The same is the case with Algorithmic problem solving, by tackling new problems we sharpen our brain to help the computer solve the real world problems. For an example, in order to solve dynamic programming algorithms you need to practice enough of recursion problems. If you want to practice more coding problems you can actively participate in online contests with complexities of time and space.

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Janani Jayaraman

Director of Product Management - Building lead to cash portfolio @ ServiceNow l Ex- Freshworks | Ex-Cisco
(已编辑)
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There is no easy way to get better at any skill than practice. The more problems you have exposure to, the more you practice , you know when to use them & what to improve on. That is why experience is valued always. So focus on building the experience, you are bound to get better.

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5 Test and debug your solutions

The fifth step is to test and debug your solutions, and make sure they work as expected, and meet the specifications and expectations of the problem. You should also test and debug your solutions for edge cases, errors, exceptions, or bugs, and handle them appropriately. You can test and debug your solutions by using tools, frameworks, or libraries that support testing and debugging, such as unit testing, debugging tools, or code analysis tools. You should also use techniques, such as tracing, logging, or breakpoints, to monitor and inspect your code, and identify and fix any issues.

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6 Refine and optimize your solutions

The sixth step is to refine and optimize your solutions, and make them more elegant, efficient, and scalable. You should also refine and optimize your solutions for readability, maintainability, and modularity, and follow the best practices and standards of algorithm design and programming. You can refine and optimize your solutions by using tools, frameworks, or libraries that support optimization, such as performance analysis, profiling, or benchmarking tools. You should also use techniques, such as refactoring, code reuse, or documentation, to improve your code quality, and reduce complexity, redundancy, or errors.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Priyank Verma

Senior Software Development Engineer @ PayPay Japan | Ex-Amazon | DTU Almni |
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Enhance Coding Skills: Engage in online coding platforms like LeetCode, CodeSignal, or HackerRank to sharpen problem-solving abilities. Gain External Insights: Participate in code reviews with colleagues or mentors for valuable perspectives on algorithm design approaches. Challenge Yourself: Join programming competitions on platforms like Codeforces or TopCoder to thrive in time-constrained scenarios and elevate your skills. Continuous Improvement: Reflect on your problem-solving approach, seeking efficiency and elegance. Revisit past solutions to identify opportunities for enhancement.

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Kalyanaraman Srinivasan

Engineering @ Amadeus Software Labs
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Engaging in consistent coding practice along with peers helps in knowing different problem solving approach, participate in coding challenges, connect with like minded coding groups/communities to discuss diverse problems & approaches. These efforts would help to improve the algorithmic design skills.

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What are the most effective ways to identify areas of weakness in your algorithm design skills?

1

2

3

4

5

6

7

1 Assess your current level

2 Review the fundamentals

3 Learn from others

4 Solve more problems

5 Test and debug your solutions

6 Refine and optimize your solutions

7 Here’s what else to consider

Algorithms

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What are the most effective ways to identify areas of weakness in your algorithm design skills?

1

2

3

4

5

6

7

1 Assess your current level

2 Review the fundamentals

3 Learn from others

4 Solve more problems

5 Test and debug your solutions

6 Refine and optimize your solutions

7 Here’s what else to consider

Algorithms

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