Latest news with #maintainability
Geeky Gadgets
a day ago
- Geeky Gadgets
The Secret to Designing Scalable, Future-Proof Software Systems
What does it take to design a software system that doesn't crumble under the weight of its own complexity? For many developers, the challenge of architecting large-scale software projects lies in balancing competing priorities: scalability, flexibility, and long-term maintainability. Picture this: a healthcare platform handling millions of patient records, or a mission-critical system in a jet fighter where even a minor failure could have catastrophic consequences. These systems demand more than just technical know-how—they require a thoughtful, deliberate approach to architecture. In this how-to, Eskil Steenberg unpacks the principles and practices that can transform chaotic, fragile codebases into robust, future-proof systems. In the video below Eskil Steenberg takes you through the core tenets of software architecture—from modular design to API strategies—and learn how to apply them to real-world scenarios. Whether you're building a plug-in system for video editing software or designing a scalable data platform, this guide will help you navigate the complexities of large-scale development. Along the way, you'll discover how to strike the perfect balance between simplicity and flexibility, making sure your software evolves with changing demands. By the end, you'll not only have a deeper understanding of scalable architecture but also practical tools to tackle your next big project with confidence. After all, the best systems aren't just built—they're carefully crafted. Foundations of Software Architecture To achieve these goals, consider the following: Dependability: Ensure your system is reliable and performs consistently under various conditions. Ensure your system is reliable and performs consistently under various conditions. Extendability: Design with future growth in mind, allowing for seamless integration of new features. Design with future growth in mind, allowing for seamless integration of new features. Development Efficiency: Streamline workflows to reduce complexity and improve team productivity. Why Modularity Matters Modularity is the cornerstone of scalable software design. Each module should function as a self-contained unit, exposing only its interface while concealing internal details. This 'black-box' approach simplifies maintenance, encourages reuse, and reduces overall system complexity. Assigning modules to small, focused teams enhances accountability and accelerates development cycles. Minimizing interdependencies between modules is equally critical. Loose coupling ensures that changes in one module do not cascade into others, improving both reliability and adaptability. By embracing modularity, you can create systems that are easier to scale, debug, and evolve. Principles of Large-Scale Software Architecture Explained Watch this video on YouTube. Explore further guides and articles from our vast library that you may find relevant to your interests in AI coding. Designing APIs and Data Formats APIs serve as the communication backbone of any software system. To ensure longevity and usability, design APIs that support enhancements without breaking existing functionality. This requires careful planning and adherence to best practices, such as versioning and backward compatibility. Separating the semantics (meaning) of data from its structure (format) is another critical consideration. This separation allows for greater flexibility and reuse, allowing your system to adapt to new requirements without significant rework. Keep data formats simple, consistent, and easy to implement to reduce integration challenges and improve developer experience. Strategies for Implementation Implementing a robust software architecture involves adopting strategies that enhance flexibility and scalability. One effective approach is the use of plug-in architectures, which isolate core functionality and enable additional features to be added as needed. This modular approach allows you to adapt to new requirements without overhauling the entire system. Supporting development with tools such as simulators, loggers, and visualizers can significantly improve testing and debugging efficiency. These tools provide valuable insights into system behavior, helping you identify and resolve issues more effectively. Additionally, abstracting implementation details helps avoid vendor lock-in, giving you the freedom to evolve your technology stack as needed. Real-World Applications of Modular Design Modular design principles are widely applicable across various industries and use cases. Here are some real-world examples that illustrate their effectiveness: Video Editing Software: The core of a video editor revolves around managing a timeline of clips with parameters. By modularizing the user interface, platform layers, and core processing, developers can ensure scalability and reuse. Plug-ins for video formats, effects, and rendering extend functionality without altering the core system. The core of a video editor revolves around managing a timeline of clips with parameters. By modularizing the user interface, platform layers, and core processing, developers can ensure scalability and reuse. Plug-ins for video formats, effects, and rendering extend functionality without altering the core system. Healthcare Systems: In healthcare software, events such as appointments and treatments form the core data structure. Abstracting storage and access layers allows for gradual migration from legacy systems. Providing APIs in multiple programming languages ensures compatibility with diverse use cases and user needs. In healthcare software, events such as appointments and treatments form the core data structure. Abstracting storage and access layers allows for gradual migration from legacy systems. Providing APIs in multiple programming languages ensures compatibility with diverse use cases and user needs. Mission-Critical Systems (e.g., Jet Fighters): For systems where reliability is paramount, centralizing the state of the world (e.g., sensor data, capabilities) in an authoritative core is essential. A subscription model efficiently distributes data to subsystems, while redundancy ensures reliability under critical conditions. Balancing Simplicity and Flexibility Striking the right balance between simplicity and flexibility is crucial in software design. Overly complex systems are harder to implement, maintain, and debug, increasing the likelihood of errors and inefficiencies. On the other hand, overly simplistic designs may fail to accommodate future requirements. To achieve this balance, focus on clarity and generalization while avoiding unnecessary complexity. Design systems that meet current needs while remaining adaptable to future changes. This approach ensures your software is both practical and resilient, capable of evolving alongside user demands and technological advancements. The Role of Tooling and Testing Effective tools are indispensable for successful software development and testing. Simulators, visualizers, and data recorders enable you to validate functionality and debug issues independently of the full system. Recording and replaying data helps identify and resolve problems efficiently, reducing downtime and improving overall system reliability. Comprehensive documentation and examples further support developers and users, making sure smooth adoption and integration. By investing in robust tooling and testing practices, you can enhance the quality and maintainability of your software. Maximizing the Potential of Plug-In Systems Plug-in systems offer a powerful way to extend the functionality of your software without disrupting its core architecture. By designing modular and reusable plug-ins, you can promote consistency, reduce development overhead, and scale your software's capabilities across multiple projects. Plug-ins should integrate seamlessly into your core system, providing additional features without dictating its overall structure. This approach not only enhances flexibility but also simplifies maintenance and future development efforts. Media Credit: Eskil Steenberg Filed Under: Guides Latest Geeky Gadgets Deals Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.
Forbes
23-07-2025
- Forbes
Bad Coding Habits That Hurt Team Efficiency And Collaboration
In the fast-paced world of development, clarity is key—but many developers fall into habits that obscure their code and make life difficult for their teammates. Writing good code isn't just about getting it to work; it's about making it maintainable, readable and clean. From vague comments and tangled logic to pull requests that try to do too much at once, code that only makes sense to its original author isn't sustainable. Below, members of Forbes Technology Council share common bad habits developers fall into—and what they should be doing instead to write cleaner, more team-friendly code. 1. Logging Inconsistently One bad habit developers fall into is following poor logging practices like vague, inconsistent logging statements. This makes it incredibly difficult for fellow developers to debug efficiently. Fix it with practices like providing contextual information. - Ramachander Rao Thallada, Manulife 2. Overengineering Code One bad habit developers fall into is overengineering, which complicates code unnecessarily and adds features with no real value. Instead, they should focus on creating flexible solutions that align with business goals, ensuring the code is understandable and maintainable for fellow developers. - Andrey Kozyrskiy, Specific-Group Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify? 3. Clinging To Personally Preferred Tools And Languages Something I've seen holding teams back is individuals clinging to their preferred tools, programming languages or styles over seeking the tools and processes that are most applicable to all. Languages and frameworks are just tools in your toolbox; real engineering is about curiosity and problem-solving. When teams embrace that, it's easier to align on what works best for the organization and engineering pace at each stage. - Eva Nahari, Vectara 4. Skipping Pseudocode And Inline Comments Pseudocode, pseudocode, pseudocode. Pseudocode helps you plan your code's logic before you write it, acting like a detailed blueprint. Comments within your code explain the purpose and how it works for anyone reading it. Together, they make your code clearer, easier to understand and simpler to maintain by others. - Vasanth Mudavatu, Dell Technologies 5. Withholding Descriptions When companies value knowledge as power over shared learning, developers find it useful to leave out descriptions of what they have done. A developer often comes to hold the belief that if they are the only one who can figure out their code, they will hold onto their job. - Laureen Knudsen, Empower Consultant Group 6. Making Code Too Abstract Too Soon We're so heavily trained in college to build extensible, reusable code that we fall into the bad habit of overcomplicating code by making it too abstract too soon. I encourage my team to strike a good balance between concreteness and abstraction. For example, inheritance should be used carefully, not assumed as the default. DRY is great, but clarity matters more; repetition is okay using IDEs with AI. - Gabriel Labrada, Process Street 7. Writing 'Clever' Code One bad habit is writing 'clever' code that no one else can understand. This is a classic case of misplaced confidence, making the code brittle and hard to maintain. Instead, prioritize clarity over cleverness. Code is read far more than it's written. True seniority is shown by writing simple, explicit code that empowers your teammates. - Marcin Nowak, Decerto 8. Prioritizing Conciseness Over Clarity One common pitfall is prioritizing conciseness over clarity—writing overly compact or tightly packed code that's difficult to read or maintain. While it may function well, it creates friction for others. Instead, developers should favor clear, well-documented code with intuitive structure, making collaboration and future updates significantly smoother. - Shrushti Kenekar, Global Partners 9. Relying Too Heavily On Patching Developers often engage in patch coding, where they fix issues as they arise without considering scalability, reusability and long-term maintenance. Instead of focusing on short-term solutions, ask questions about requirements, identify potential for reuse, and adopt pattern-based thinking. These strategies can help reduce technical debt and ease future upkeep. Vibe coding will address this problem soon! - Buyan Thyagarajan, Eigen X 10. Creating Oversized Pull Requests One bad habit is pushing a large number of changes (lines of code and files changed) into one pull request. It is convenient for the developer writing the code to do this because it reduces the number of change iterations and test cycles. However, for the peers reviewing the pull request (and eventually when releasing the code), it's a nightmare to actually review the code meaningfully or debug when there's a failure. - Madhuri Sesha Sarma, Carta Inc. 11. Skipping Structure And Functional Clarity While doing code reviews, I have often noticed devs failing to outline what the code does and its functionality, as well as not maintaining consistency with established patterns. Decoupling functional from nonfunctional code, implementing modular design, organizing the structure, and aligning with defined enterprise standards will make it easier for anyone reviewing or trying to understand the code. - Ugandhar Dasi, T-Mobile US 12. Writing Without Comments One bad habit is writing code without comments or meaningful naming. It forces others to waste time deciphering logic. Instead, devs should use clear, descriptive names and concise comments to explain why (not just what) the code does. This makes collaboration and maintenance much easier. - Roshan Mahant, LaunchIT Corp. 13. Coding In Isolation One bad habit is coding in isolation, focusing only on what works rather than on how others will build on it. This leads to brittle, opaque systems that are hard to scale or maintain. Developers should think like system designers, not just problem solvers. Clear structure, contextual comments and consistent patterns turn code into a durable asset instead of a liability. - Satpreet Singh, Pinnacle Digital Advisors 14. Tightly Coupling Logic With UI Or Infrastructure With years in engineering, I have seen devs tightly couple logic with UI or infrastructure, making reuse and testing painful. Instead, they should design code with separation in mind so it is easier to extend, mock and hand off across teams without breaking everything. - Gopinath Kathiresan, Apple Inc. 15. Leaving Cryptic Or Outdated Comments One bad habit? Leaving cryptic comments like '// temporary fix' … from 2017. Instead, write clear, intent-driven comments and meaningful commit messages. Code is read more than it's written—treat it like a message in a bottle to your future teammates (and your sleep-deprived future self). - Sumit Bhatnagar 16. Using Hardcoded Values Or Ignoring Design Tokens Front-end devs using hardcoded values or ignoring design tokens make it harder for others to understand, update or extend the code. It forces extra guesswork and risks inconsistency. Instead, stick to shared design variables, as this keeps the codebase clear, scalable and aligned with the design system. - Aishwarya Suresh, Medtronic Inc. 17. Skipping Branch Strategy And Clear Commit Messages Skipping a clear branch strategy and writing vague commit messages causes major headaches during debugging and deployment. Without consistent naming conventions (like feature/ or hotfix/) or a defined model such as trunk-based development or GitFlow, CI/CD quickly becomes messy. Use clear branch names and descriptive commit messages to make reviews, merges and issue tracing much easier for everyone. - Jae Lee, MBLM 18. Failing To Document Design Decisions Sometimes the rationale for tricky design decisions is lost. Devs rely on verbal handoffs or assume that everyone on the team knows the context. Design decisions should be captured in design docs and decision logs so that future devs can see the 'why,' not just the 'what.' - Amy Gu, Dynamsoft 19. Writing For Machines, Not Humans A bad habit is writing code for machines, not humans, using clever shortcuts with no context. Instead, devs should treat code like a shared language that is clear, modular and self-documenting. Bonus move: Tokenize contributions so those who write the most valuable code build equity in the platform they help create. There is true value in competent participation. - Charles Morey, MobilEyes Inc. 20. Having Poor (Or Missing) Documentation And Logging Too many devs write cryptic code with poor documentation and bad logging (missing context, wrong levels or no logs at all)—making debugging a nightmare. Here's what to do instead: Use descriptive names, explain decisions in comments and log key events with proper context (user ID, request ID, error details and so on) to swiftly identify and resolve issues. Code should be readable; logs should tell the story. - Uttam Kumar, American Eagle Outfitters
