How can you solve coding problems quickly without sacrificing quality?

The easiest way to fail to create a successful product is to make any assumptions. The fact is that a programmer’s perspective is focused on the problem and finding a solution. The user’s perspective is on how well the product fits their need. The key is talking to your stakeholders and especially the users to help guide them toward the proper solution. Users and other stakeholders will understand their wants and needs, not the technical details. Trust in their understanding of what they want and help them find the solution that fits their needs.

I can't state how important it is to take the time to understand the problem completely. We often start coding once we gain an understanding of part of the problem, then run into the 'gotchas' later on which slows progress. Understand the problem and make no assumptions!

Before you solve a coding problem, make sure you understand it. This will help you avoid common mistakes, like focusing on making the code faster before you have a working version. It will also help you write code that is easier to read and maintain.

The first and foremost step in system development is understanding the problem. The main challenge is differentiating between system needs and customer wishes. Needs are important for developing successful products while wishes can convince customer to pay.

Understanding the problem in isolation may not work well 100% of the time. Understanding the context of the problem is what makes us able to deliver real business value. The connection between problems gives us the ability to predict the future of the context, so it gives us the ability to find the most relevant solution.

- Understand the Problem: Before diving in, ensure you grasp the problem's core. Misunderstandings can lead to wasted time. - Plan Before Coding: Sketch out an approach on paper or pseudocode. Visualizing first prevents unnecessary revisions later. - Break It Down: Tackle big problems by dividing them into smaller, manageable parts. Solve each section step by step. - Test Regularly: Don't wait until the end. Regularly test your code to catch errors early. - Review: After solving, review your solution. Streamline if needed. Quality isn't just about working code but also efficient and readable code.

Experience means pattern recognition. Most of the problems we face daily are not unique, therefore are already solved somewhere else before. Learning how to approach problems is a skill to learn, and it can be perfected by facing more high-quality problems.

Hey everyone, it's Jahangeer! Let's shift gears and talk about the second crucial phase in coding: Choosing a Strategy. ??? Ever get stuck deciding between a brute-force solution and a fancy algorithm? Happened to me when optimizing search queries at work. Time was tight, and the knee-jerk reaction was to use a well-known, heavier algorithm for quick gains. Pause. Rewind. We took a step back and opted for a simpler, index-based approach. Guess what? It met our performance targets and was far easier to maintain. ?? Choosing the right strategy isn't just about quick fixes; it's about foreseeing implications and making an informed decision. So next time you're in a coding jam, think strategy, not just code.

Before delving into your IDE, try and understand which solution begets the problem. The following techniques have proven pivotal in my coding journey; 1. Conduct a mind map of the problem 2. Apply 'rudimentary' math solving knowledge to the word problem 3. Write some pseudocode to break the code in easier to understand chunks. 4. Go to your IDE and apply the solution. N/B DRY(Don't repeat yourself)

The best design lefts a lot of decisions not taken, don't try to predict far into the future. Don't do micro-optimizations. Break your problem into separate small and independently deployable iterations. Alongside all of this, I emphasize on the importance of test-first approach!

Although pseudo code came be useful, I find that interfaces are a great way to setup the parts of a program. Once you have your required structure as defined in interfaces, it is not only easier to fill in the details, but it is also easier to split apart the effort into easier to manage steps.

It is good practice to engage your interviewer/class/audience when writing code. This not only shows that you can work with cross-functional teams but its also indicates that you are willing to ask for help when stuck so as to alleviate bugs.

What I personally find extremely helpful is to visualize my solution in the form of a diagram. Whether it’s a finite state machine or an implementation for a communication protocol, it is always insighful to do so and brings a lot of potential issues with the design to the surface so they are easily fixed with minimum investment!

When we write things down, we force ourselves to make them "writeable". Also, after we write them down, we become able to see them. However, writing steps for a proposed solution only works if we do it without any fears. You can be wrong, and it's ok. We were all wrong at some point. If you're able to put the wrong solution on paper, you'll become able to see why it's wrong more clearly, therefore you'll be able to fix what's wrong more easily.

Hey folks, Jahangeer here again! This time, let's talk about an often-overlooked step in coding: Writing Pseudocode. ?? I was once part of a project that involved designing a recommendation system. We were torn between various algorithms and data sources. Before diving into code, we sketched out pseudocode as a team. And guess what? That simple act of drafting in plain language helped us identify gaps in our logic and inconsistencies in data flow. We could refine our strategy even before hitting the IDE! ?? So next time you're tackling a complex problem, start with pseudocode. It’s your roadmap; sometimes the journey is easier when you know the path. ???

Being in academia for 13 years, I always tell my students to sketch the problem into stages. Then, for each stage, explicitly determine the required input, output, and processing needed. This helps in breaking down the huge problem into smaller problems before coding and testing.

My typical strategy is to prioritize writing effective code to address a given problem. Concerns such as less conventional function names, large-scale functions lacking separation, and somewhat inefficient complexity usually take a back seat. The motto 'done is better than perfect' tends to prevail, suggesting that the initial goal should be solution-driven, with refinements to follow. Attempting perfection right from the start can lead to unnecessary time consumption. More importantly, if you're not in a interview, it's crucial to consider the input size. For smaller inputs, heavy optimization might not be needed. Even codes with higher complexity, such as O(n^2) or O(n^3), can function perfectly well for inputs around the size of 100.

Have a clear naming policy and coding style in mind. This gives you the ability to focus on the problem itself, not the style. Have clear expectations about what you want to achieve. TDD is a cool way for it, but even if you don't use TDD, make sure you have clear expectations for the outcomes, written down.

Hello again, it's Jahangeer! Today, let's discuss the heart of any project: Code and Test. ???? I remember working on a real-time analytics engine. After understanding the problem and sketching pseudocode, it was time to actually code. But here's the kicker: we integrated testing right from the get-go, not as an afterthought. For every module we coded, a suite of tests was built in parallel. Result? Each piece was verified as we progressed, reducing errors and speeding up the final QA phase. Plus, when we later scaled the engine, those initial tests were invaluable in ensuring stability. So, my two cents: Code, but always, always test as you go. It's not just about building, but building right.

Refactoring and optimizing the code is very important, but can also be a trap. You could continue to refactor and improve for a very long time and never deliver the desired product. Get it to work, then see how users utilize it before spending too much time rewriting for performance.

Don't overlook. Build your own process of coding a solution, and stick to it. If you overlook, you may risk drowning inside a problem that's not already there. But also, don't leave your code alone after first attempt. There will be things to change and adapt, and you'll be able to do all the necessary parts without overlooking, if you have your own process.

Hey everyone, Jahangeer here, back with another key topic: Refactor and Optimize. ???? We've all been there—code is functional, tests are passing, and it feels like mission accomplished. But is it, really? I found the answer while working on a natural language processing pipeline. The code worked but was a spaghetti maze of nested loops and conditionals. So, we refactored. Simplified code blocks, modularized functions, and even managed to slash runtime by 20%. Not just cleaner, but faster too! ?? Remember, good code works, but great code works efficiently and is maintainable. Don't just stop at the first working version—refactor, optimize, and elevate your code to the next level.

I have found that in order to solve complex problems in software programs, it is hard to lose track of where you would like to start. What works best for me is the Test Driven Development approach. First: Understand the problem in hand and the edge cases, valid inputs/outputs, and any business requirements that you need to take into consideration. Second: Write test cases for the problem. Map your edge cases, valid input/outputs, and your business requirements in the test cases. When you run the test cases they will fail. Third: Build the logic from there. Write the algorithm, and run tests again. Once all tests are passing, start refactoring your code. This has proven to produce high quality code, with less time and vast edge case coverage

Many coding challenges will be expected to read from stdin and write to stdout. But many languages (eg. Javascript running in NodeJS) make this awkward and you might spend a lot of time working out how to get started. So make sure you prepare this part of your skillset.