Voici comment vous pouvez maîtriser les compétences essentielles en résolution de problèmes pour une carrière réussie en génie logiciel.

Las capacidades técnicas con practica se logran dominar, es muy importante también las blandas, inclusive son un poco más importantes y difíciles de desarrollar , evitar la procrastinación

Data structures, algorithms and design patterns are extremely important in programming. Problem solving skill in programming is trained through solving hundreds of coding tasks and puzzles, polishing you instincts on picking efficient algorithms and data structures. Choose the difficulty level smartly: it should be barely doable, should contain some open questions, unknown parts, but you should feel you have a draft plan in your head. If you're stuck- don't spend too much time, work in other tasks, learn new stuff and come back later. Never search for a direct solution of the task you feel you're getting stuck with, always break down the problem, and try to identify the missing parts- only then google 🙂

Having knowledge to tackle immediate problems is valuable, but a person with a strong understanding of the basics in any field becomes indispensable in their surroundings. In today's technological world, fewer people are starting their journey from absolute basics.

I totally agree that data structures, algorithms, and design patterns are the core of programming. They are the fundamental block once you start doing good in this, it will help you in learning a programming language more in depth as well. You will understand each core functions of programming language and how and where to use that and all this knowledge will help you in solving the problem.

Mastering your chosen programming language is also key to effective problem-solving. Being proficient in the syntax and intricacies of the language allows you to write efficient and concise code. Moreover, it enables you to navigate and comprehend code written by others, which is a valuable skill in collaborative projects and when troubleshooting issues. By investing time in solidifying your knowledge of computer science fundamentals and polishing your programming skills, you pave the way for more effective problem-solving capabilities. This groundwork not only enhances your technical proficiency but also equips you with the necessary skills to tackle challenges and contribute meaningfully to software engineering projects.

Breaking down big problems to well defined tasks is something that will take you to new heights in the software world. Often big problems are amorphous and vauge. Meanwhile, creating well defined modular bites of code enhances reusability and maintenance. This skill if you get really good at it will be worth dividends later in support costs.

Being able to break down a bigger problem into bite-sized tasks is a skill which alone can move mountains. It won't be too far from truth to say that it actually is the problem solving.

To master essential problem-solving skills for a successful software engineering career, I focus on breaking down complex problems into smaller, more manageable parts. Then, I practice analyzing each component thoroughly to understand its function and potential solutions. Next, I experiment with different approaches, seeking feedback from peers and mentors along the way. Finally, I iterate and refine my problem-solving process continuously, learning from both successes and failures to improve my skills over time.

Solving a huge problem all at once is very difficult. Therefore, it's beneficial to break it into smaller chunks, making it easier to solve with minimal effort and time. This approach also offers other advantages, such as the ability to review, evaluate, and receive feedback.

firmly believe that breaking down complex problems into smaller, more manageable parts is an invaluable strategy. This divide-and-conquer approach prevents feeling overwhelmed and helps isolate the core issues. By outlining major components and dissecting each further, you can focus on one aspect at a time, leading to more efficient and effective solutions. This methodical approach enhances clarity, facilitates easier debugging, and allows for incremental progress, making it a cornerstone of successful problem-solving in software development and beyond

Patterns are, to some extent, a learned skill. You won't always spot them until you've seen them before. But, in general, a few hallmarks: - Is this a repeated problem? Is it solved elsewhere in the same codebase? - Does this resemble something you've seen? 90% of software problems are just an internet search away, if you can find the right parameters. - Gut feeling - Sometimes, something just feels "close" to another problem you've dealt with. In which case, try to adapt your previous solution to your current problem.

Recognizing patterns in problems is a hallmark of experienced software engineering. By identifying similarities to previously encountered challenges, you can apply or adapt known solutions, saving time and effort. This practice not only streamlines problem-solving but also builds a valuable repertoire of strategies for future use. It enhances efficiency and effectiveness, making it an essential skill for any seasoned developer.

Pattern recognition is a double-edged sword. It can get you quick results when you do it successfully. Equally, it can cost you lots of time when you get it incorrect. I find if I don't know it is 'exactly the same' pattern, its best treating it like a unique problem to avoid wasting time down an incorrect solution.

Testing is an integral part of software engineering. To successfully code, you must remember to test early for early error detection.

Detecção Precoce de Erros Identificar e corrigir erros em estágios iniciais do desenvolvimento é fundamental para economizar recursos financeiros. Os testes unitários permitem detectar falhas no código-fonte logo após sua criação, quando ainda são relativamente simples e baratas de corrigir. Isso evita que esses problemas se propaguem para estágios posteriores do projeto, onde sua resolução pode exigir mais tempo e recursos.

Test early, test often, and test well. Also, do not be afraid to enhance old tests as your product becomes more mature. The earlier problems are detected, the less solving them costs. The earlier testing is involved in developmemt process the better off the product.

Testing holds the same importance as building a brand new software product. Also testing of a newly developed product makes it for a longer run and testing rigorously gives stability and reliability too.

Dependiendo del tipo de proyecto que se debe enfrentar, es importante decidir antes cual metodología de trabajo utilizar, la clásica cascada para proyectos bien definidos y con metas fijadas en el tiempo, metodología Agile para desarrollos incrementales, cuando los objetivos y/o los plazos no son tan claros, híbridos entre ambas y algunas otras técnicas nuevas que van surgiendo

There it iterating quickly during development, which is one thing. There is also interating too often. One problem with changing the code often, or having a big team changing lots of different spots, is that sometimes tests get forgotten about. They don't change the tests with the code, and then error riddled code is getting released. Making sure to update tests to cover new code changes, is a tough task that prevents costly errors later.

It can be particularly valuable to find ways to collaborate with coworkers outside of the software engineering silo. For example, having the opportunity to work closely with someone in sales can give you insights on what actually matters to potential customers, and also gives you the opportunity to highlight to them what makes the work you and your team are doing is valuable to customers.

Conectar-se com membros de outras disciplinas é essencial para desenvolvedores. Isso oferece perspectivas diversas, aprendizado interdisciplinar, solução holística de problemas e colaboração efetiva. Enquanto equilibrar com o foco técnico é importante, essa interação enriquece habilidades, promove inovação e possibilita abordagens mais criativas. Geralmente, não é uma perda de tempo, mas uma oportunidade de crescimento profissional e pessoal.

IMO, this whole article is missing out on a fundamental component: "Engineering". This question asks for Software Engineering not Software Coding. Engineering is at it's heart a structured problem solving discipline. The formal steps to create a solution can be learned and adapted from systems engineering. The problem solving itself comes from experience and accepting a certain level of uncertainty and discomfort as you specify, understand, design, and test your solutions. The software practices are learned mostly through experience and keeping abreast of best practices. - This article has a lot of good insight on this. To summarize, I strongly recommend looking at this topic more holistically instead of just focusing on coding.

Coding is not an achievement... First you need to think on a piece of paper, with a pencil and a rubber... (Or anything similar to it). Just put yourself in the place of the data. You ARE the data... Where do you need to go so that the human being extracts most of your value. To do that, you MUST understand the data,... if not, no software design will be useful. Data is money, it cost a lot to get one useful piece of data with all of its connected knowledge (Say a weight measurement with the measurement method, the measurement unique ID, the uncertainties -- random and systematic -- etc.) Now, how to you propagate yourself (the data) to the final result, step by step towards the unique goal? This is THE key.