Importance of Coding Principles

SOLID Principles: The Bedrock of Clean, Maintainable Code As software engineers, we strive for code that's robust, flexible, and easy to maintain. Let's revisit SOLID principles - a set of guidelines that, when followed, lead to better software design. Let's break them down: 𝗦 - 𝗦𝗶𝗻𝗴𝗹𝗲 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆 𝗣𝗿𝗶𝗻𝗰𝗶𝗽𝗹𝗲 • Each class should have one, and only one, reason to change • Keep your code simple, focused, and easier to understand • Think: "Does this class do too much?" 𝗢 - 𝗢𝗽𝗲𝗻-𝗖𝗹𝗼𝘀𝗲𝗱 𝗣𝗿𝗶𝗻𝗰𝗶𝗽𝗹𝗲 • Software entities should be open for extension, but closed for modification • Add new features without altering existing code • Use abstractions and polymorphism to achieve this 𝗟 - 𝗟𝗶𝘀𝗸𝗼𝘃 𝗦𝘂𝗯𝘀𝘁𝗶𝘁𝘂𝘁𝗶𝗼𝗻 𝗣𝗿𝗶𝗻𝗰𝗶𝗽𝗹𝗲 • Derived classes must be substitutable for their base classes • Subclasses should extend, not replace, the behavior of the base class • Ensures different parts of your code can work together seamlessly 𝗜 - 𝗜𝗻𝘁𝗲𝗿𝗳𝗮𝗰𝗲 𝗦𝗲𝗴𝗿𝗲𝗴𝗮𝘁𝗶𝗼𝗻 𝗣𝗿𝗶𝗻𝗰𝗶𝗽𝗹𝗲 • Many client-specific interfaces are better than one general-purpose interface • Keep interfaces focused and lean • Prevents classes from implementing methods they don't need 𝗗 - 𝗗𝗲𝗽𝗲𝗻𝗱𝗲𝗻𝗰𝘆 𝗜𝗻𝘃𝗲𝗿𝘀𝗶𝗼𝗻 𝗣𝗿𝗶𝗻𝗰𝗶𝗽𝗹𝗲 • Depend on abstractions, not concretions • High-level modules shouldn't depend on low-level modules; both should depend on abstractions • Promotes flexibility and easier testing through decoupling Implementing SOLID principles might seem challenging at first, but the long-term benefits are substantial: • Increased code maintainability • Easier testing and debugging • Enhanced scalability and flexibility How have you applied SOLID principles in your projects? What challenges did you face, and how did you overcome them?

In late 2016, while at Microsoft, I wrote a piece of code that caused severe crashes across 8+ regions, reducing our Service Level Agreements (SLAs) significantly. Within 30 hours, our team had jumped into action and resolved the crisis. This is the story of one of my biggest career mistakes and what it taught me. It all started with a subtle error: a null pointer exception in a rarely used code path. I thought it wasn't urgent and even considered going on vacation. But as life would have it, another team made changes that increased the frequency of this problematic code path, leading to massive crashes in multiple regions and affecting our SLAs badly. I was in shock when I realized the magnitude of what had happened. My heart pounded, but I knew I couldn't freeze. I took ownership and immediately informed leadership. Initially, they thought I was joking, but soon realized the severity of the issue. I involved the Product Management team to communicate with impacted customers while I focused on finding a fix. Within 30-40 minutes, I had a solution. I tested it thoroughly, validated it in a test region, and gathered approvals for a hotfix. Within 30 hours, we rolled out the fix to all regions. This experience taught me: 1. High-Quality Code Is Non-Negotiable: Quality code and thorough testing are critical, especially at scale. 2. Ownership Earns Respect: Taking responsibility rather than deflecting blame is crucial in resolving issues. 3. Communication Is Key: Proactive communication with leadership and customers maintains trust. 4. Learn and Reflect: Reflecting on mistakes and learning from them is what makes us better. I survived one of my worst mistakes by owning, fixing, and growing. Mistakes happen, but it’s how we respond that defines us. What's your biggest mistake, and what did it teach you?

In my previous post, I talked about README files. Another way to keep yourself organized and avoid headaches in the long run is by using effective inline comments within the code. Think about the comments as a bridge between the logic in your mind and the understanding of others (or even your future self). Comments make your code more readable and maintainable, making sure that anyone who revisits the project can follow your thought process. Here are some tips for writing effective code comments: ⭐️ Comment the Why, Not the What: Avoid explaining what the code is doing (which is often clear from reading the code itself). Instead, explain why a particular approach was chosen or why a piece of logic exists. (This is when the logic is not too complex) ⭐️ Explain Complex Logic: When dealing with intricate or non-obvious code, break it down with comments. This helps others (and you) follow along without needing to decipher the code. ⭐️ Keep It Concise and Relevant: Comments should be concise yet informative. Avoid over-commenting, as too much information can clutter the code and make it harder to read. ⭐️ Use Section Headers: In large scripts, use comments as section headers to break the code into logical chunks. This improves readability and makes navigation easier. How do you use comments in your workflow? Share below 😊

🚨 “𝗪𝗲 𝗨𝘀𝗲 𝗥𝘂𝘀𝘁” 𝗜𝘀𝗻’𝘁 𝗮 𝗖𝘆𝗯𝗲𝗿𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝘆 —𝘮𝘺 𝘱𝘦𝘳𝘴𝘰𝘯𝘢𝘭 𝘷𝘪𝘦𝘸; 𝘰𝘱𝘪𝘯𝘪𝘰𝘯𝘴 𝘢𝘳𝘦 𝘮𝘺 𝘰𝘸𝘯. It’s becoming a common line: “𝘖𝘶𝘳 𝘴𝘺𝘴𝘵𝘦𝘮 𝘪𝘴 𝘴𝘦𝘤𝘶𝘳𝘦 — 𝘸𝘦 𝘶𝘴𝘦 𝘙𝘶𝘴𝘵.” Let’s be honest. 🟢 𝗥𝘂𝘀𝘁 𝗶𝘀 𝗮 𝗹𝗲𝗮𝗽 𝗳𝗼𝗿𝘄𝗮𝗿𝗱:  • Memory-safe by design  • Eliminates entire classes of bugs (buffer overflows, use-after-free)  • Catches issues at compile time  • Reduces your memory-related attack surface 📊 Microsoft & Google estimate ~70% of historical CVEs stem from memory safety issues — and Rust helps slash that risk. But… 🔴 𝗥𝘂𝘀𝘁 𝗶𝘀𝗻’𝘁 𝗮 𝘀𝗶𝗹𝘃𝗲𝗿 𝗯𝘂𝗹𝗹𝗲𝘁: ❌ Logic flaws still exist ❌ Bad architecture is still bad ❌ Misconfigurations still get exploited ❌ Malicious dependencies still sneak in 𝗖 𝗼𝗿 𝗖++ 𝗱𝗼𝗲𝘀𝗻’𝘁 𝗺𝗮𝗸𝗲 𝘆𝗼𝘂𝗿 𝘀𝘆𝘀𝘁𝗲𝗺 𝘂𝗻𝘀𝗮𝗳𝗲. 𝗥𝘂𝘀𝘁 𝗱𝗼𝗲𝘀𝗻’𝘁 𝗺𝗮𝗸𝗲 𝘆𝗼𝘂𝗿 𝘀𝘆𝘀𝘁𝗲𝗺 𝘀𝗲𝗰𝘂𝗿𝗲. Security is layered: 🔐 Threat modeling 🔐 Defense-in-depth 🔐 Secure-by-design thinking 𝗨𝘀𝗲 𝗥𝘂𝘀𝘁. 𝗟𝗼𝘃𝗲 𝗥𝘂𝘀𝘁. Just don’t confuse 𝘴𝘢𝘧𝘦 𝘤𝘰𝘥𝘦 with a 𝘴𝘦𝘤𝘶𝘳𝘦 𝘴𝘺𝘴𝘵𝘦𝘮. (Clarity matters. Repost to spread it. ♻️) #AutomotiveCybersecurity #SDV #RUST #EmbeddedSecurity

If you're memorizing a coding concept without understanding it, you're setting yourself up for trouble. We've all been there. You hit a snag, hop onto Stack Overflow, copy and paste some code, and bam! Problem solved. Or is it? When you get something working with a quick fix, it probably feels great. It's done, so you move on to the next bug. But this leads to a shallow understanding of the underlying problem. You're basically using a band-aid instead of fixing the core issue. And yes, not understanding something is definitely a problem. Over the next days or weeks, you'll likely face a similar issue and end up back at square one -- searching Stack Overflow, still not understanding, looking for the next quick fix. And getting many quick hits like this doesn't sound like the development of good habits. True understanding comes from being absolutely obsessed with the fundamentals. If you want to truly master something, and your knowledge is built on shaky ground, ...it's bound to collapse. So, what's the alternative? Dive deep into the foundational concepts. This principle applies to mastering anything that's hard to learn, whether it's PHP, Magento, a new JavaScript framework, or some other complex system. Start by focusing on one concept at a time. Break it down into small, manageable chunks. For example, if you're working with Magento, take the time to understand how the framework is structured. - What are its core components? - How do they interact with each other? - What's the purpose of each piece of code you're writing? Then, do a deep-dive. There are plenty of great videos, tutorials, and articles online that will teach you everything you need to know. I created a trove of video lessons to learn Magento at Macademy to save you time, but you can also learn for free if you're on a budget. Instead of copying and pasting code from Stack Overflow, dig into the comments and ask yourself some questions. Why does this thing work the way it does? Are there certain things going on under the hood that I'm not aware of? The idea is to learn something small, experiment, and continue to ask tons of questions. And you can begin by asking narrow questions about one specific thing. If you learn one small piece of the puzzle every day, you're starting to build up the foundations of becoming a rock-star developer. You'll move from relying on patches from Stack Overflow to contributing answers yourself. And let me tell you, when your answers start getting upvoted, it definitely helps your confidence in becoming the coder you aspire to be. #magento #php #opensource #programming

Some best practices for writing code-comments. Often, comments should only answer questions code can't (e.g. the "why") Good code should read like a well-written prose, and inline comments act as its annotations. Yet, writing meaningful comments is often overlooked, considered a secondary or trivial task. But a poor or missing comment can confuse or mislead the reader, causing more harm than no comments at all. Ellen Spertus laid out an excellent framework for how to get code comments right: https://lnkd.in/gKjvHd4N: Rule 1: Comments should not duplicate the code. Rule 2: Good comments do not excuse unclear code. Rule 3: If you can't write a clear comment, there may be a problem with the code. Rule 4: Comments should dispel confusion, not cause it. Rule 5: Explain unidiomatic code in comments. Rule 6: Provide links to the original source of copied code. Rule 7: Include links to external references where they will be most helpful. Rule 8: Add comments when fixing bugs. Rule 9: Use comments to mark incomplete implementations. Rule 1: Avoid Redundancy Comments shouldn't echo the code. Redundant comments are mere noise. A comment like i = i + 1; // Add one to i doesn't help anyone. It only distracts. Rule 2: Clarity Over Comments If you find yourself writing a comment to make a complicated block of code clear, stop. Rethink and refactor the code first. Good variable naming often obviates the need for comments. Rule 3: If It's Complicated to Comment, It's Likely Wrong If you can't write a clear comment for a piece of code, that might be a red flag. Maybe the code is too convoluted or the logic too tangled. Rewrite it. Rule 4: Clarify, Don't Confuse Don't let your comments turn into riddles. If a comment generates more questions than it answers, it's a bad comment. Rule 5: Comment Unidiomatic Code Sometimes you have to break the usual rules for special cases. When you do, explain why. A well-placed comment can prevent future devs from "fixing" code that isn't broken. Rule 6: Attribute Copied Code If you're lifting code from Stack Overflow/GPT or any other source, provide a link. This is good for both context and complying with licenses. Rule 7: Link to External References When your code adheres to a particular standard or responds to an RFC, say so in a comment and link to it. Rule 8: Comment Bug Fixes When you fix a bug, leave a breadcrumb for future developers. This might be as simple as a comment pointing to an issue number or explaining the bug's behavior. Rule 9: Mark Incomplete Code Sometimes you have to commit code with known limitations. Use a standard TODO format to highlight these. Mention the technical debt and perhaps link to an issue tracker. Conclusion Comments don't fix bad code; they complement good code. When done poorly, they obfuscate. Keep these guidelines in mind #programming #developers #code #work 

SOLID principles are key in object-oriented programming. But what does each principle actually mean, and why are they significant? 𝗦𝗢𝗟𝗜𝗗 𝗿𝗲𝗽𝗿𝗲𝘀𝗲𝗻𝘁𝘀 𝗳𝗶𝘃𝗲 𝗽𝗿𝗶𝗻𝗰𝗶𝗽𝗹𝗲𝘀 𝗼𝗳 𝗼𝗯𝗷𝗲𝗰𝘁-𝗼𝗿𝗶𝗲𝗻𝘁𝗲𝗱 𝗽𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴. Whether or not you use OOP, 𝗸𝗻𝗼𝘄𝗶𝗻𝗴 𝘁𝗵𝗲𝘀𝗲 𝗽𝗿𝗶𝗻𝗰𝗶𝗽𝗹𝗲𝘀 𝗴𝗶𝘃𝗲𝘀 𝘆𝗼𝘂 𝗮 𝗹𝗲𝗻𝘀 𝗶𝗻𝘁𝗼 𝘁𝗵𝗲 𝗳𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻𝘀 𝗼𝗳 𝗰𝗹𝗲𝗮𝗻 𝗰𝗼𝗱𝗲 which can be applied to many areas of programming. 𝗦 — Single Responsibility Principle 𝗢 — Open/Closed Principle 𝗟 — Liskov Substitution Principle 𝗜 — Interface Segregation Principle 𝗗 — Dependency Inversion Principle Let’s break down each principle ↓ 𝟭. 𝗦𝗶𝗻𝗴𝗹𝗲 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆 𝗣𝗿𝗶𝗻𝗰𝗶𝗽𝗹𝗲 (𝗦𝗥𝗣) Each unit of code should only have one job or responsibility. A unit can be a class, module, function, or component. This keeps code modular and removes the risk of tight coupling. 𝟮. 𝗢𝗽𝗲𝗻-𝗖𝗹𝗼𝘀𝗲𝗱 𝗣𝗿𝗶𝗻𝗰𝗶𝗽𝗹𝗲 (𝗢𝗖𝗣) Units of code should be open for extension but closed for modification. You should be able to extend functionality with additional code rather than modifying existing ones. This principle can be applied to component-based systems such as a React frontend. 𝟯. 𝗟𝗶𝘀𝗸𝗼𝘃 𝗦𝘂𝗯𝘀𝘁𝗶𝘁𝘂𝘁𝗶𝗼𝗻 𝗣𝗿𝗶𝗻𝗰𝗶𝗽𝗹𝗲 (𝗟𝗦𝗣) You should be able to substitute objects a of base class with objects of its subclass without altering the ‘correctness’ of the program. An example of this is with a Bird base class. You might assume that it should have a ‘fly’ method. But what about the birds that can’t fly? Like a Penguin. In this example, having a ‘fly’ method in the Bird class would violate LSP. 𝟰. 𝗜𝗻𝘁𝗲𝗿𝗳𝗮𝗰𝗲 𝗦𝗲𝗴𝗿𝗲𝗴𝗮𝘁𝗶𝗼𝗻 𝗣𝗿𝗶𝗻𝗰𝗶𝗽𝗹𝗲 (𝗜𝗦𝗣) Provide multiple interfaces with specific responsibilities rather than a small set of general-purpose interfaces. Clients shouldn’t need to know about the methods & properties that don't relate to their use case. Complexity ↓ Code flexibility ↑ 𝟱. 𝗗𝗲𝗽𝗲𝗻𝗱𝗲𝗻𝗰𝘆 𝗜𝗻𝘃𝗲𝗿𝘀𝗶𝗼𝗻 𝗣𝗿𝗶𝗻𝗰𝗶𝗽𝗹𝗲 (𝗗𝗜𝗣) You should depend on abstractions, not on concrete classes. Use abstractions to decouple dependencies between different parts of the systems. Direct calls between units of code shouldn’t be done, instead interfaces or abstractions should be used. Post Credit: Nikki Siapno #systemdesign #solidprinciples #systemarchitecture

This blog post, "Secure Vibe Coding Guide," published by the Cloud Security Alliance in April 2025 and authored by Ken Huang, CISSP, aims to elevate the practice of "Vibe Coding" by embedding a security-first mindset from its inception. Read the full "Secure Vibe Coding Guide" here: https://lnkd.in/g_thmryW * * * What is Vibe Coding? It's an AI-assisted programming approach where users describe software requirements in natural language, and LLMs generate the code. This shifts the developer's role to guiding, testing, and refining AI output. While accessible to non-programmers, it often involves accepting code without full implementation understanding, raising reliability concerns. Why is Security Crucial? Research, like that behind BaxBench, shows that top foundational LLMs can generate at least 36% insecure code. This guide bridges that gap, ensuring innovative projects are also secure. What to do? To secure "vibe-coded" applications, a holistic approach is vital. It begins with secure coding fundamentals, like avoiding hardcoded sensitive data and rigorously validating all inputs to prevent injection attacks. Next, application security (AppSec) integrates security throughout the development pipeline, with automated vulnerability scanning in CI/CD and regular penetration testing. This ensures continuous vigilance. API and GitHub security are crucial for protecting your application's entry points and codebase. Implement strong authentication for APIs, use rate limiting, and secure your repositories with 2FA and dependency updates. Database security is paramount for data protection, requiring parameterized queries to prevent SQL injection, encryption for sensitive data, and strict access controls. Crucially, AI-specific risks, as highlighted by the OWASP LLM Top 10, must be addressed. This includes defending against prompt injection, sensitive information disclosure, and supply chain vulnerabilities unique to LLMs. Finally, secure cloud deployment (leveraging platform features like firewalls and secure environment variables) and the human element (staying informed and seeking expert advice) complete the security framework, ensuring your vibe-coded innovations are robust and protected. The guide further empowers developers by including practical secure vibe coding prompts, designed to integrate security considerations directly into the AI-assisted workflow from the outset. * * * As Ken Huang, CISSP emphasizes in his "Secure Vibe Coding Guide," while vibe coding is here to stay and transforming software development, security isn't a one-time fix - it's a shared and continuous responsibility. By implementing these practices, we can build secure, reliable, and innovative applications. A huge thanks to my incredible colleague and go-to AI expert, Ben Prescott, Head of AI Solutioning at Trace3, for sharing this!

𝐂# 𝐓𝐢𝐩: 𝐃𝐢𝐟𝐟𝐞𝐫𝐞𝐧𝐭 𝐖𝐚𝐲𝐬 𝐭𝐨 𝐂𝐡𝐞𝐜𝐤 𝐟𝐨𝐫 𝐍𝐮𝐥𝐥𝐬 𝐢𝐧 .𝐍𝐄𝐓 💡 Handling null values effectively is crucial in any .NET application to avoid unexpected crashes or NullReferenceException errors. Let’s explore some common ways to check for null in C#, including a few modern approaches. 1. 𝐂𝐥𝐚𝐬𝐬𝐢𝐜 𝐢𝐟 𝐒𝐭𝐚𝐭𝐞𝐦𝐞𝐧𝐭 The traditional way to check for null is using the if statement. 2. 𝐍𝐮𝐥𝐥-𝐂𝐨𝐚𝐥𝐞𝐬𝐜𝐢𝐧𝐠 𝐎𝐩𝐞𝐫𝐚𝐭𝐨𝐫 (??) The ?? operator provides a shorthand for checking null and assigning a default value. Image example: If obj is null, result will be assigned "Default Value". 3. 𝐍𝐮𝐥𝐥-𝐂𝐨𝐧𝐝𝐢𝐭𝐢𝐨𝐧𝐚𝐥 𝐎𝐩𝐞𝐫𝐚𝐭𝐨𝐫 (?.) Introduced in C# 6, the null-conditional operator simplifies checking for null and avoids throwing exceptions. Image example: If obj is null, length will also be null, preventing a NullReferenceException. 4. 𝐏𝐚𝐭𝐭𝐞𝐫𝐧 𝐌𝐚𝐭𝐜𝐡𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝐢𝐬 In modern C# versions, you can use pattern matching with is to check for null. 5. 𝐍𝐮𝐥𝐥𝐚𝐛𝐥𝐞 𝐑𝐞𝐟𝐞𝐫𝐞𝐧𝐜𝐞 𝐓𝐲𝐩𝐞𝐬 (𝐂# 8+) With C# 8.0, you can enable nullable reference types, which allow you to explicitly mark reference types as nullable or non-nullable. The compiler will provide warnings if you're not handling nulls properly. 𝐅𝐢𝐧𝐚𝐥 𝐓𝐡𝐨𝐮𝐠𝐡𝐭𝐬 Handling null correctly is essential for writing robust and error-free code. Choose the method that best fits your needs based on readability and performance. If you found this useful, give it a like, share it with your network, and comment below with your preferred way to handle null values! 🚀 #CSharp #DotNet #NullHandling #ProgrammingTips #SoftwareDevelopment #DevCommunity #BestPractices #CleanCode

One of the best advice I’ve received from a senior early in my career was to read Clean Code by Robert C. This is one of the most impactful books I’ve ever read. It forever changed how I used to code. If I had to summarize the 10 most important principles from the book, they would be: 1. Meaningful Names - Choose clear, descriptive names that reveal the intent of your code. - Names should help others understand the purpose without extra context. - Example: Use `totalCost` instead of `x` for clarity. 2. Small Functions - Keep functions small and focused on a single task. - If a function exceeds 20 lines, consider refactoring. - Example: A `calculateTotal()` function should only handle calculations, not logging. 3. DRY Principle (Don’t Repeat Yourself) - Avoid code duplication to reduce maintenance complexity and potential bugs. - Aim for reusability and modularity in your code. - Example: Use a `processUserInput()` function rather than repeating the same logic multiple times. 4. Avoid Comments - Write self-explanatory code to minimize the need for comments. - Outdated comments can mislead, so focus on making the code itself clear. - Example: Refactor a complicated `for` loop into a well-named function rather than explaining it with comments. 5. Error Handling - Separate error handling from business logic to keep code clean. - Handle exceptions gracefully to maintain resilience. - Example: Use a `try-catch` block around critical operations and log errors in a dedicated function. 6. Readable Code - Prioritize readability over cleverness to make the code easy to understand. - Consistent formatting and naming conventions enhance code clarity. - Example: Use clear indentation and consistent variable names like `userName` and `userAge`. 7. Single Responsibility Principle (SRP) - Ensure each class and function has one responsibility or reason to change. - This principle makes the code more modular and easier to test. - Example: A `User` class should only handle user-related data, not database operations. 8. Dependency Injection - Rely on interfaces or abstractions rather than concrete implementations. - This approach decouples components and makes the code more flexible and testable. - Example: Inject a `PaymentProcessor` interface into a `Checkout` class rather than using a specific payment gateway directly. 9. Testing - Write automated tests to validate your code and catch bugs early. - Tests act as a safety net, ensuring code behaves as expected after changes. - Example: Use unit tests to verify that a `calculateDiscount()` function returns the correct value for various input scenarios. 10. Refactoring - Continuously improve your code through refactoring to maintain quality. - Refactoring should be an ongoing process, not a one-time task. - Example: Regularly revisit old code to simplify logic or reduce duplication, like merging similar methods into one.