How do you handle software architecture complexity?

Handling software architecture should not start from design patterns but from the complex domain. Understanding the domain is the first step for handling complex architecture: 1) Analysis 2)Define proper paradigms for development such as OOP, Procedural, etc. 2) High-level design (High-level architectural patterns applying) 3) Detailed design ( the rest of the components and low-level patterns) 4) Test 5) Deploy In most cases, using patterns can be a shackle holding you back. Try first to implement functionality and then define which pattern will be better for you

I think design patterns are not here to solve complexity of the architecture. Purpose of design pattern is solve a specific problem. The article should add some examples for users as well for better understanding of the the purpose.

- The best approach to handle the system design complexity is to introduce modularity and keep each module as simple as it can be. - Identify the responsibilities of various modules and define contracts for communication among each other - Utilize design patterns to apply common reusable solutions to typical generalized problems thereby reducing complexity

Design patterns provide guidance and best practices for designing the overall structure and organization of software systems. They help address issues such as scalability, maintainability, flexibility, and modularity. If we take an example the Microservices design pattern or architecture, This pattern decomposes a system into a collection of small, independent services that communicate with each other through well-defined APIs. Each service focuses on a specific business capability, allowing for scalability, fault isolation, and independent deployment.

When handling software architecture is a concern I would understand the the business domain using techniques. I would divide the business domain into subdomains like Core, Generic, and supporting domains. I would draw boundaries between different business domain contexts and then decide what tactical design or architectural pattern I should use for each. Of course, it should not be one single architectural pattern for the whole system. There are too many deciding factors based on your subdomain needs. What kind of data store is an appropriate domain, Cloud base or On-premises, SAAS or PAAS bases system?, Costing, etc. Also needs to check what solution provides the best value in terms of productivity, maintainability, and revenue.

Learning from past experiences might help a lot. if you faced with side effects or weaknesses of previously designed software architecture, now, you could look for appropriate patterns to solve.

Begin by defining the problem and breaking it down in independent set of modules. For each module, identify the core concern- whether its object creation, composition or dynamic behaviours. Then identify design pattern which can applied and is best suited for your application. While evaluating consider consider simplicity & future needs to select the most appropriate pattern.

When it comes to selecting design patterns, there's no definitive "right" or "wrong." Instead, it's all about trade-offs. Every pattern comes with its strengths and limitations, and it's essential to align these with the specific needs of the system and business domain. Quality Attributes are the guiding star. Different patterns shine in different areas, be it performance, scalability, or security. And with every choice, there's a cost, whether that's in terms of performance, maintainability, or some other aspect. The role of an architect isn't just about picking a pattern. It's about weaving together a tapestry of decisions to achieve our end goal, while always being mindful of the trade-offs at play.

Choosing the right design pattern is crucial. Begin by understanding the problem domain, architectural style, and system type. Evaluate trade-offs, considering factors like code complexity, flexibility, performance, and maintainability. Assess how patterns impact quality attributes and processes. Leverage team skills and consult pattern catalogs. Prototype and document your choice. For instance, use Singleton for single instances, Factory Method for flexible object creation, Observer for notifications, Strategy for interchangeable algorithms, Adapter for interface compatibility, MVC/MVVM for UI structure, and Decorator for dynamic responsibilities. Tailor your choice to your project's unique needs.

In most cases, you don't choose design patterns upfront. You refactor your code towards design patterns. Even the original authors have said that 10 years after releasing the book. If you start out with design patterns, I've experienced that most people tend to overengineer.

Im my opinion there are two primary steps when it comes to design patterns. 1- What is the problem a design patterns is trying to solve. 2- Implement the best fit pattern If someone gets this process right they will be successful

Design patterns are guidelines to solve specific problem, If you are not facing that problem, there is no need to apply design patterns. So design patterns should be applied to solve problems not to align with architecture.

Agreed. I would add that Software Systems aren't just about code. While they touch on business and servers, at their core, they're about people. We're building socio-technical systems propelling businesses. When using design patterns, the "who" matters just as much as the "what" and "how." A crucial question is, “Who will maintain and grow this system?”. I've faced choices between a high-tech solution that no one could manage and a simpler one fitting the team's skills. The challenge lies in balancing. At times, team dynamics may take precedence over technical perfection. Our ultimate aim? Deliver value reliably.

First of all, don't use the diagram from Google to apply exactly what you're planning. There are a lot of cases you should consider when applying them: 1) The programming languages you're using -> Your language can have different keywords and vocabulary for it. 2) The paradigms in your programming languages-> For multi-paradigm languages, most classical patterns may not fit into the context properly. There will be more than one way to implement the pattern. so be careful. 3) Some patterns may be applied using libraries. There is no need to "invent" them from scratch. 4)When you start to integrate them, make your pattern project bounded. Don't try to make it as a library. Only a few of them ( not more than 4) can be moved to a separate lib.

Identify the problem. Select an appropriate pattern. Study the pattern thoroughly. Customize it to fit your needs. Integrate it into your design. Follow pattern guidelines. Test and validate. Document usage. Review and refactor. Ensure consistency. Plan for future changes. Learn from experience.

The pattern evaluation process: 1) Oh, cool, I understand this pattern 2) Oh, oh, I applied it by refactoring my code. 3) Well, I started to confused with this Abstract Factory, Decorator, and Chain of Responsibility stuff. 4) Patterns are good but in all cases, your mind/thinking is better. I don't need these patterns, I need to resolve the issue with the following attributes: 1) maintainabiliity 2)extensibility 3)reusability 4)understandability

To evaluate design patterns: 1. Identify the specific problem in software design. 2. Know various design patterns and their purposes. 3. Match the problem with a suitable pattern (e.g., Singleton, Factory). 4. Consider the pattern's pros and cons, including its impact on code complexity. 5. Assess scalability, flexibility, and maintainability. 6. Example: For creating game characters, consider the Factory pattern for simplifying character creation and accommodating future additions. 7. Choose the pattern that best fits our problem, considering its long-term suitability.

Regularly assess the impact of design patterns on your project. Evaluate whether they simplify code, enhance scalability, and improve maintainability. Monitor for any performance bottlenecks or unexpected consequences. Be open to refactoring if a pattern no longer serves your project's evolving needs. Ultimately, the success of a design pattern lies in its ability to make your architecture more robust and adaptable.

While I value reviews, metrics, and tests, the key question is: what are we measuring? Evaluations should focus on quality attributes specific to the system segment, And each attribute needs a fitness function to assess implementation efficiency in context. Believing that merely using design patterns ensures simplicity and excellence is a stretch. Patterns are tools that will account for most scenarios, but our main aim should be to optimize for crucial quality attributes in context. If a tailored solution meets our needs better than a standard pattern, that's a win in my book. We should prioritize actual needs over just following established norms.

When evaluating design patterns, it's vital to follow a structured approach. Start by pinpointing the specific problem in the software design. Then, familiarize yourself with various design patterns and their purposes. Match the problem with a suitable pattern, considering factors like scalability and maintainability. For example, in game development, the Factory pattern may simplify character creation and accommodate future additions. Choose the pattern that best suits the problem, while also assessing its long-term suitability.

This article should more focus on handling complexity on large systems rather than talking about design patterns. Design patterns are not the ultimate solution for handling complexity. Mostly the systems getting complex in time even design patterns applied in the beginning. A good architect should consider removing moving parts as much as possible. And make the system simpler for the current situation. KISS approach is the best but the hardest for all engineers.

In my experience nearly all software complexity comes from solving poorly understood problems. Often it implies over-engineering (solving a bigger problem than you had to), but I find just as much complexity in under-engineering… thinking too simplistically about a larger problem. If there is complexity inherent to a domain then a simplistic codebase will be unable to tame it, and it will come out somehow. Design patterns generally feel like a hammer looking for a nail, and to that end I believe contribute to complexity by trying to shoe-horn a problem into a predetermined solution.

My biggest learning after 27 years of professional software development is to group code in a functional folder. It'll make it easier to refactor related code, reassign responsibilities, will help you to apply DRY within boundaries and find the right scope for unit tests.

My views: 1. Domain/requirement understanding is mandatory or prerequisite to define design patterns. 2. Considering possible future enhancements are also important while designing architecture which may bring up few design patterns. 3. Always keep in mind are system security, availablity, performance, scalability, testability, extensibility and resiliency. 4. Consider how components to be interacted i.e. whether API based or Event driven while designing systems. 5. Consider debugging, access patterns, Observablity, which helps to identify what database to choose, how your application should be resilient, etc. 6. Considering Disaster recovery options. 7. Avoid a single point of failure.

The fundamental law of problem solving is that you can only solve simple problem and then use them in tandem. The approach to handling complex scenarios starts from identifying simple problems and analyzing the pros and cons of all the known solution for that simple problem. The next step would be to understand how well a particular solution work with each other