Program Structuring Techniques

Great software isn’t accidental — it’s designed. 🧠💻 Here’s a quick breakdown of key Design Principles & Patterns, with real-world examples 👇 🔹 SRP – Single Responsibility Principle One class, one job. 📌 Example: A UserService handles user logic, while EmailService only sends emails. If email rules change, user logic stays untouched. 🔹 OCP – Open/Closed Principle Open for extension, closed for modification. 📌 Example: Adding a new payment method (UPI, Card, Wallet) by creating a new class instead of changing existing payment code. 🔹 LSP – Liskov Substitution Principle Child classes should work wherever parent classes are used. 📌 Example: ElectricCar should not break behavior expected from Car (like calling drive()). 🔹 ISP – Interface Segregation Principle Small, specific interfaces are better than big ones. 📌 Example: A printer interface shouldn’t force a scanner to implement print(). 🔹 DIP – Dependency Inversion Principle Depend on abstractions, not concrete classes. 📌 Example: Injecting a PaymentGateway interface instead of directly using Razorpay or Stripe. 🟢 Creational Patterns How objects are created. • Singleton – One instance only 📌 Example: Database connection manager • Factory / Abstract Factory – Centralized object creation 📌 Example: Creating UI components based on platform (Web / Mobile) • Builder – Step-by-step object creation 📌 Example: Building a complex order or HTTP request • Prototype – Clone existing objects 📌 Example: Copying document templates 🟠 Structural Patterns How objects are structured. • Adapter – Makes incompatible systems work together 📌 Example: Adapting a legacy API to a new interface • Decorator – Add behavior dynamically 📌 Example: Adding logging or caching without modifying core logic • Facade – Simplified interface 📌 Example: A single service handling multiple microservice calls • Composite – Tree-like structure 📌 Example: Folder–file system • Proxy – Control access 📌 Example: Lazy loading images or authorization checks 🔵 Behavioral Patterns How objects communicate. • Observer – Notify on change 📌 Example: Email/SMS alerts after order status update • Strategy – Swap algorithms at runtime 📌 Example: Different discount strategies • Command – Encapsulate actions 📌 Example: Undo/Redo functionality • Iterator – Sequential access 📌 Example: Looping through a collection 🔸 DRY – Don’t Repeat Yourself 📌 Example: Shared validation logic instead of copying code everywhere 🔸 KISS – Keep It Simple 📌 Example: Clear if-else logic instead of over-engineered abstractions 🔸 MVC Architecture 📌 Model: Business logic 📌 View: UI 📌 Controller: Handles requests 🔸 Repository Pattern 📌 Example: Abstracting database logic away from business logic 🔸 Unit of Work 📌 Example: Commit multiple DB changes as one transaction Strong fundamentals = scalable, clean, and maintainable code 🚀 #SoftwareEngineering #DesignPatterns #SOLID #CleanCode #SystemDesign #Developers #Programming #Architecture

If your PLC program looks like a tornado of rungs and tags… it’s time to talk code organization. One of the most overlooked (but most important) skills in automation is how you structure your logic. A good program isn’t just functional, it’s readable, maintainable, and scalable. Here’s how I like to structure mine: READ INPUTS FIRST At the top of the scan, I read and preprocess all inputs. That means: - Scaling analog values - Bit summing statuses - Conditioning values that come in externally to the respectivecomponent This makes sure everything below is based on reliable, real-time, and clean data. CONTROL LOGIC IN THE MIDDLE This is where the brain lives, sequences, states, fault conditions, timers, and logic that drives the system. I group this by function or subsystem (motors, valves, conveyors, etc.), often with clearly labeled rungs or section headers. OUTPUTS LAST At the bottom, I drive outputs based on the control decisions made above. No logic calculations down here, just clean writes like: MotorStart := Motor1.RunCommand; Minimize the logic out of the output section. It should be transparent. BIT GROUPING = SANITY SAVER If you’ve got the same 6 conditions checked 20 times across the program, wrap them into a single BOOL like SystemReady. Then everywhere else, you just check: IF SystemReady AND AutoMode THEN This avoids copy-paste errors, simplifies debugging, and makes logic more readable. REUSABILITY & NAMING - Use descriptive tag names. - Use UDTs and AOIs to encapsulate data/logic for repeated devices. - Group tags in structured ways: Motor1.b Running, Motor1.Fault, etc. Make it easy to search, comment, and troubleshoot. WHY IT MATTERS: - Faster startup & commissioning - Easier troubleshooting in the field - Smoother handoffs to other engineers - Less chance of “spaghetti logic” biting you later Clean logic doesn’t just help the machine run better. It helps the people who work on it. What’s your go-to structure when building out PLC code? #PLCProgramming #StructuredText #LadderLogic #ControlsEngineer #CodeOrganization #AutomationEngineering #IndustrialAutomation #FunctionBlocks #SmartManufacturing #SystemDesign #EngineeringBestPractices #innovation #technology #futurism #engineering

𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 𝗣𝗮𝘁𝘁𝗲𝗿𝗻𝘀 Software design defines a system's architecture to meet requirements, creating blueprints for development teams. Over time, reusable architecture patterns have emerged that reduce complexity, increase maintainability, and speed development. The most crucial software architecture patterns are: 𝟭. 𝗟𝗮𝘆𝗲𝗿𝗲𝗱 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲: Divides applications into logical layers (Presentation, Business, Data Access) with specific responsibilities. Promotes separation of concerns and easier maintenance. 𝟮. 𝗠𝗶𝗰𝗿𝗼𝘀𝗲𝗿𝘃𝗶𝗰𝗲𝘀: Decomposes applications into small, independent services communicating via APIs. Each implements a single business capability and can be independently deployed, enabling team autonomy and continuous delivery. 𝟯. 𝗘𝘃𝗲𝗻𝘁-𝗗𝗿𝗶𝘃𝗲𝗻: Uses events for asynchronous communication between components. The system doesn't wait for event handling to complete before continuing, making it ideal for real-time applications requiring high scalability. 𝟰. 𝗦𝗽𝗮𝗰𝗲-𝗯𝗮𝘀𝗲𝗱: Uses independent "spaces" as autonomous units across multiple servers. Eliminates single points of failure in high-volume systems and overcomes data bottlenecks and network latency. 𝟱. 𝗠𝗶𝗰𝗿𝗼𝗸𝗲𝗿𝗻𝗲𝗹 (𝗽𝗹𝘂𝗴-𝗶𝗻 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲): Provides minimal core functionality with additional services as separate modules. Developers can modify components without impacting core functionality, which is ideal for applications requiring customization. 𝟲. 𝗖𝗤𝗥𝗦 (𝗖𝗼𝗺𝗺𝗮𝗻𝗱-𝗤𝘂𝗲𝗿𝘆 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆 𝗦𝗲𝗴𝗿𝗲𝗴𝗮𝘁𝗶𝗼𝗻): Separates read and write operations into distinct models. Improves performance and scalability in complex domains by optimizing each path independently. 𝟳. 𝗛𝗲𝘅𝗮𝗴𝗼𝗻𝗮𝗹 (𝗣𝗼𝗿𝘁𝘀 𝗮𝗻𝗱 𝗔𝗱𝗮𝗽𝘁𝗲𝗿𝘀): Isolates business logic from external concerns. Allows applications to be driven by various sources and developed independently from runtime dependencies. Selecting the correct pattern depends on your specific requirements and constraints. Real-world applications often combine multiple patterns to address different aspects of system design. #technology #softwareengineering #programming #techworldwithmilan #softwarearchitecture

PLC Code Planning: 1. Define sequences: Before writing code, define the sequences and their triggers. 2. Use a programming ladder: Start building the program with a programming ladder. 3. Manage sequences: Work on sequences in manageable sizes. 4. Make it readable: Ensure sequences are clear and readable. 5. Avoid scattered code: Make sure the code isn't scattered. 6. Return to initial state: The program should be able to return to its initial state so it can run again. 7. Use a standard naming convention: Use a standard naming convention for inputs, outputs, variables, routines, and tags. 8. Use descriptive names: Use descriptive and consistent names for variables, functions, and modules. Avoid generic names like "x", "y", or "temp". 9. Document the project: Document the scope, inputs and outputs, logic and functionality, tests and results, and maintenance and support.

You inherit someone else’s bioinformatics code. No comments. No structure. Variable names like x1, foo, temp2. And now it’s your problem. Let’s talk about that experience—and how to do better. 1/ Ever opened someone’s script and felt instant regret? No README No comments Hard-coded paths Copy-pasted blocks No functions You’re not alone. Code without structure is like a freezer full of unlabelled tubes. Sure, it runs. But good luck figuring out what anything does. 3/ Bad practices hurt you the most. Even if you wrote the code. You: “I’ll remember this later.” Also you (6 weeks later): “Who wrote this garbage?” Still you. 4/ On the flip side: Well-structured code feels like a gift. Functions are defined. Comments explain the logic. Each section is modular. You can re-use it. You can trust it. 5/ Here’s what I’ve learned from writing and inheriting messy code: Bad code punishes future you. Good code rewards collaborators. 6/ What are some good coding practices in bioinformatics? Use clear variable names Comment your logic, not just what each line does Break repetitive steps into functions Keep a README and usage example Use relative paths and config files 7/ Avoid this: x1 <- read.table("data.txt") temp2 <- x1[which(x1[,3] > 10), ] Prefer this: expression_data <- read.table("data.txt", header=TRUE) high_expr <- subset(expression_data, expression > 10) Make it obvious what’s happening. 8/ Turn repeated blocks into functions: filter_by_threshold <- function(data, column, threshold) { subset(data, data[[column]] > threshold) } Now your code is DRY (Don’t Repeat Yourself) and reusable. 9/ Keep outputs organized: mkdir -p results/qc mkdir -p results/plots If your outputs are sprinkled across your desktop, it’s time to rethink. 10/ Bonus: write a run_pipeline.sh that chains all your steps. Use snakemake or nextflow if it gets too big. Even a bash script with clear comments beats scattered commands. 11/ Want to learn how to write better code? Read other people’s good code. You’ll learn tricks no tutorial teaches. 12/ Good code is a form of respect. For yourself. For your collaborators. For the person who inherits your project next. Write like someone else has to read it. Because they will. 13/ Bioinformatics isn’t just about solving problems. It’s about communicating how you solved them. Your code is your paper in progress. Write it like you’re proud of it. I hope you've found this post helpful. Follow me for more. Subscribe to my FREE newsletter chatomics to learn bioinformatics https://lnkd.in/erw83Svn