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A class should have only one reason to change. For example, a class that handles logging should not also handle database operations, or, a User class handling user data storage but not also managing UI rendering.
A class should be open for extension but closed for modification. For example, a class that handles logging should be open for extension to support new logging types, but closed for modification to change existing logging behavior, or creating an abstract class for different payment methods, allowing new payment methods to be added as subclasses without modifying the existing code.
Objects of a superclass should be replaceable with objects of a subclass without affecting the correctness of the program. For example, a class that handles logging should be able to use a subclass that logs to a file instead of a database without changing the logging class, or if you have a class Rectangle and a subclass Square, a Square object should be able to replace a Rectangle object without causing any unexpected behavior.
A class should not be forced to implement interfaces it does not use. For example, a class that handles logging should not be forced to implement a UI rendering interface, or creating separate interfaces for different functionalities, such as one interface for reading data and another for writing data, instead of a single monolithic interface.
High-level modules should not depend on low-level modules. Both should depend on abstractions. For example, a class that handles logging should depend on an interface for logging, not a specific logging class, or depending on IRepository interface instead of specific database classes for data access.
SOLID is an acronym that represents five design principles in object-oriented programming and software development. These principles are guidelines to help create more maintainable, flexible, and scalable software solutions. Visit https://en.wikipedia.org/wiki/Robert_C._Martin for more information.
Creational patterns focus on object creation mechanisms, abstracting the instantiation process to make the system independent of how objects are created, composed, and represented.
Defines a one-to-many dependency between objects, ensuring that when one object changes state, all its dependents are notified and updated automatically.
Defines the skeleton of an algorithm in a method, deferring some steps to subclasses, allowing subclasses to redefine certain steps of the algorithm without changing its structure.
Decouples method execution from method invocation for objects whose operations are time-consuming. A file download manager that initiates downloads in separate threads and notifies the UI when they complete.
Only executes an action on an object when the object is in a particular state. A video player that only allows playback controls when a video is loaded and ready to play.
Allows multiple threads to synchronize and reach a barrier point, waiting for all threads to reach the barrier before proceeding. Used in parallel computing, where each thread performs a part of a larger computation and waits for all other threads to complete before combining the results.
Reduces the overhead of acquiring a lock by first testing a condition without a lock, and then acquiring the lock if the condition is true. Can be used to optimize the creation of a singleton instance, by first checking if it exists without a lock, and then creating it with a lock if it doesn't.
Manages operations that require both mutual exclusion and synchronization, such as when multiple threads are waiting for a resource to become available. A producer-consumer scenario, where the consumer thread waits for items to be added to a queue by the producer thread.
Allows a single thread to perform computations on behalf of other threads, avoiding redundant processing. Can be used in a multi-threaded web crawler, where one thread checks if a URL has already been visited, and if not, assigns it to a pool of worker threads.
An object whose methods are subject to mutual exclusion, ensuring that only one thread can execute a method at a time. Can be used to implement thread-safe data structures, such as a bounded queue.
Allows a series of operations to be executed atomically, without interference from other threads. Can be used in a banking application to ensure that a transfer between accounts is either completed entirely or not at all.
Allows concurrent event handling by demultiplexing and dispatching service requests in a synchronized manner. Commonly used in network servers and event-driven architectures.
Allows multiple threads to read shared data concurrently, but only one thread to write to the shared data at a time. Can be used in a caching system, where multiple threads can read from the cache, but updates to the cache are synchronized.
Allows tasks to be scheduled for execution at a later time or on a recurring basis. Can be used in a job scheduling system, where tasks are scheduled to run at specific times or intervals.
Maintains a pool of worker threads to increase performance and resource management for executing asynchronous or parallel tasks. Can be used in a web server, where a pool of threads handles incoming requests concurrently.
Allows each thread to have its own thread-specific data, avoiding the need for complex synchronization when accessing shared data. Can be used in a logging system, where each thread has its own log buffer to avoid contention.
Architectural patterns and styles provide guidelines and best practices for designing the overall structure of software systems, defining the relationships between components, and organizing the codebase for scalability, maintainability, and performance.
A software design pattern that enables the construction of event-driven systems by providing a way for components to communicate without explicit dependencies.
A variation of the MVC pattern that organizes the components into a hierarchical structure, often used in desktop or web applications.
Design patterns are reusable solutions to common problems in software design. They provide a template for solving issues that occur in different contexts, helping developers create more maintainable, scalable, and flexible software solutions.
Classes that have too many responsibilities or dependencies, violating the Single Responsibility Principle and making them difficult to maintain and test.
Using primitive data types (e.g., strings, integers) instead of creating custom classes to represent concepts, leading to code duplication and maintenance issues.
Classes that have too many responsibilities or dependencies, violating the Single Responsibility Principle and making them difficult to maintain and test.
Using hardcoded values in the code instead of constants or configuration settings, making it difficult to update or maintain the code.
Code smells are indicators of potential issues in software code that may lead to bugs, maintenance problems, or performance issues. Identifying and addressing code smells can help improve code quality, readability, and maintainability.
Managing multiple services and their interactions can introduce complexity, requiring additional tools and processes for monitoring, testing, and deployment.
Implementing service discovery mechanisms helps services locate and communicate with each other dynamically, supporting scalability and fault tolerance.
Monitoring and logging tools are essential for tracking the performance, availability, and reliability of microservices, enabling teams to identify and address issues quickly.
Implementing security measures, such as authentication, authorization, and encryption, is crucial to protect microservices and their data from unauthorized access and attacks.
Using a service mesh architecture helps manage the communication between services, providing features like load balancing, service discovery, and security.
Implementing event-driven patterns, such as message queues and pub/sub systems, enables services to communicate asynchronously and decouple their interactions.
Using container technologies, such as Docker and Kubernetes, simplifies the deployment and management of microservices, improving scalability and resource utilization.
Adopting serverless computing platforms, like AWS Lambda and Azure Functions, allows teams to focus on writing code without managing servers, reducing operational overhead and costs.
Microservices introduce challenges, such as distributed data management, service orchestration, and cross-service communication, that require careful planning and design to address effectively.
Microservices architecture is an approach to software development where a large application is divided into smaller, independent services that can be developed, deployed, and scaled separately. Each service focuses on a specific business function and communicates with other services through APIs.
Addressing skepticism and resistance towards citizen development from traditional IT teams or developers.
Citizen development refers to the practice of non-technical users creating applications or automating processes without the direct involvement of IT teams. While citizen development can empower users and improve productivity, it also presents challenges that organizations need to address to ensure security, governance, and scalability.
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