🛠️ What is GitHub Actions?

GitHub Actions is a feature of GitHub that lets you create automated workflows for your software projects—right inside your GitHub repository.

📌 What can you do with GitHub Actions?

You can build CI/CD pipelines (Continuous Integration / Continuous Deployment), such as:

• ✅ Automatically test code (e.g. with PHPUnit, Jest, Pytest)

• 🛠️ Build your app on every push or pull request

• 🚀 Automatically deploy (e.g. to a server, cloud platform, or DockerHub)

• 📦 Create releases (e.g. zip packages or version tags)

• 🔄 Run scheduled tasks (cronjobs)

🧱 How does it work?

GitHub Actions uses workflows, defined in a YAML file inside your repository:

• Typically stored as .github/workflows/ci.yml

• You define events (like push, pull_request) and jobs (like build, test)

• Each job consists of steps, which are shell commands or prebuilt actions

Example: Simple CI Workflow for Node.js

name: CI

on: [push]

jobs:
  build:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - uses: actions/setup-node@v3
        with:
          node-version: '20'
      - run: npm install
      - run: npm test

🧩 What are "Actions"?

An Action is a single reusable step in a workflow. You can use:

• Prebuilt actions (e.g. actions/checkout, setup-node, upload-artifact)

• Custom actions (e.g. shell scripts or Docker-based logic)

You can explore reusable actions in the GitHub Marketplace.

💡 Why use GitHub Actions?

• Saves time by automating repetitive tasks

• Improves code quality through automated testing

• Enables consistent, repeatable deployments

• Integrated directly in GitHub—no need for external CI tools like Jenkins or Travis CI

Assertions are programming constructs used to check assumptions about the state of a program. An assertion tests whether a specific condition is true—if it isn't, an error is typically raised and the program stops.

x = 10
assert x > 0   # passes
assert x < 5   # raises AssertionError, since x is not less than 5

Purpose of Assertions:

• They help with debugging: you can verify that certain conditions in code hold true during development.

• They document implicit assumptions, e.g., “At this point, the list must have at least one item.”

• They are mainly used during development—assertions are often disabled in production code.

Key Difference from Regular Error Handling:

Assertions are meant to catch programmer errors, not user input or external failures. For example:

• assert age > 0 → inappropriate if age comes from user input.

• Instead, use: if age <= 0: raise ValueError("Age must be positive.")

A Partial Mock is a testing technique where only certain methods of an object are mocked, while the rest of the object retains its real implementation. This is useful when you want to stub or mock specific methods but keep others functioning normally.

When to Use a Partial Mock?

• When you want to test a class but isolate certain methods.

• When some methods are difficult to test (e.g., they have external dependencies), but others should retain their real logic.

• When you only need to stub specific methods to control test behavior.

Example in PHP with PHPUnit

Suppose you have a Calculator class but want to mock only the multiply() method while keeping add() as is.

class Calculator {
    public function add($a, $b) {
        return $a + $b;
    }

    public function multiply($a, $b) {
        return $a * $b;
    }
}

// PHPUnit Test with Partial Mock
class CalculatorTest extends \PHPUnit\Framework\TestCase {
    public function testPartialMock() {
        // Create a Partial Mock for Calculator
        $calculator = $this->getMockBuilder(Calculator::class)
                           ->onlyMethods(['multiply']) // Only mock this method
                           ->getMock();

        // Define behavior for multiply()
        $calculator->method('multiply')->willReturn(10);

        // Test real add() method
        $this->assertEquals(5, $calculator->add(2, 3));

        // Test mocked multiply() method
        $this->assertEquals(10, $calculator->multiply(2, 3));
    }
}

Here, add() remains unchanged and executes the real implementation, while multiply() always returns 10.

Conclusion

Partial Mocks are useful when you need to isolate specific parts of a class without fully replacing it. They help make tests more stable and efficient by mocking only selected methods.

A SUT (System Under Test) is the system or component being tested in a testing process. The term is commonly used in software development and quality assurance.

Meaning and Application:

• In software testing, the SUT refers to the entire program, a single module, or a specific function being tested.
• In hardware testing, the SUT could be an electronic device or a machine under examination.
• In automated testing, the SUT is often tested using frameworks and tools to identify errors or unexpected behavior.

A typical testing process includes:

1. Defining test cases based on requirements.
2. Executing tests on the SUT.
3. Reviewing test results and comparing them with expected outcomes.

The Pyramid Web Framework is a lightweight, flexible, and scalable web framework for Python. It is part of the Pylons Project family and is ideal for developers looking for a minimalist yet powerful solution for web applications.

Key Features of Pyramid:

1. Minimalistic but Extensible

   • Pyramid provides a lean core architecture with only essential features, allowing developers to add extensions as needed.

2. Flexible

   • It supports various databases, authentication systems, and templating engines (e.g., Jinja2, Chameleon, Mako).

3. Traversal and URL Mapping

   • Pyramid allows both traditional URL routing (similar to Flask/Django) and a powerful traversal system, which is particularly useful for hierarchical data structures.

4. Powerful and Efficient

   • Due to its modular design, Pyramid is suitable for large projects while remaining resource-efficient.

5. First-Class Testing Support

   • Pyramid is built with testability in mind and includes built-in support for unit and integration testing.

6. Comprehensive Documentation & Community Support

   • The official documentation is extensive, and there is an active developer community.

When Should You Use Pyramid?

• If you need a lightweight yet scalable framework.
• If you want full control over your application architecture.
• If you’re developing a project with complex URL structures or hierarchical data.
• If Django feels too heavy and Flask feels too basic.

Comparison with Other Frameworks:

Conclusion

Pyramid is an excellent choice for developers looking for a balance between minimalism and power. It is particularly well-suited for medium to large web projects where scalability, flexibility, and good testability are essential.

A module in software development is a self-contained unit or component of a larger system that performs a specific function or task. It operates independently but often works with other modules to enable the overall functionality of the system. Modules are designed to be independently developed, tested, and maintained, which increases flexibility and code reusability.

Key characteristics of a module include:

1. Encapsulation: A module hides its internal details and exposes only a defined interface (API) for interacting with other modules.
2. Reusability: Modules are designed for specific tasks, making them reusable in other programs or projects.
3. Independence: Modules are as independent as possible, so changes in one module don’t directly affect others.
4. Testability: Each module can be tested separately, which simplifies debugging and ensures higher quality.

Examples of modules include functions for user management, database access, or payment processing within a software application.

Contract Driven Development (CDD) is a software development approach that focuses on defining and using contracts between different components or services. These contracts clearly specify how various software parts should interact with each other. CDD is commonly used in microservices architectures or API development to ensure that communication between independent modules is accurate and consistent.

Key Concepts of CDD

1. Contracts as a Single Source of Truth:

   • A contract is a formal specification (e.g., in JSON or YAML) of a service or API that describes which endpoints, parameters, data formats, and communication expectations exist.
   • The contract is treated as the central resource upon which both client and server components are built.

2. Separation of Implementation and Contract:

   • The implementation of a service or component must comply with the defined contract.
   • Clients (users of this service) build their requests based on the contract, independent of the actual server-side implementation.

3. Contract-Driven Testing:

   • A core aspect of CDD is using automated contract tests to verify compliance with the contract. These tests ensure that the interaction between different components adheres to the specified expectations.
   • For example, a Consumer-Driven Contract test can be used to ensure that the data and formats expected by the consumer are provided by the provider.

Benefits of Contract Driven Development

1. Clear Interface Definition: Explicit specification of contracts clarifies how components interact, reducing misunderstandings and errors.
2. Independent Development: Teams developing different services or components can work in parallel as long as they adhere to the defined contract.
3. Simplified Integration and Testing: Since contracts serve as the foundation, mock servers or clients can be created based on these specifications, enabling integration testing without requiring all components to be available.
4. Increased Consistency and Reliability: Automated contract tests ensure that changes in one service do not negatively impact other systems.

Use Cases for CDD

• Microservices Architectures: In complex distributed systems, CDD helps define and stabilize communication between services.
• API Development: In API development, a contract ensures that the exposed interface meets the expectations of users (e.g., other teams or external customers).
• Consumer-Driven Contracts: For consumer-driven contracts (e.g., using tools like Pact), consumers of a service define the expected interactions, and providers ensure that their services fulfill these expectations.

Disadvantages and Challenges of CDD

1. Management Overhead:

   • Maintaining and updating contracts can be challenging, especially with many services involved or in a dynamic environment.

2. Versioning and Backward Compatibility:

   • If contracts change, both providers and consumers need to be synchronized, which can require complex coordination.

3. Over-Documentation:

   • In some cases, CDD can lead to an excessive focus on documentation, reducing flexibility.

Conclusion

Contract Driven Development is especially suitable for projects with many independent components where clear and stable interfaces are essential. It helps prevent misunderstandings and ensures that the communication between services remains robust through automated testing. However, the added complexity of managing contracts needs to be considered.

CaptainHook is a PHP-based Git hook manager that helps developers automate tasks related to Git repositories. It allows you to easily configure and manage Git hooks, which are scripts that run automatically at certain points during the Git workflow (e.g., before committing or pushing code). This is particularly useful for enforcing coding standards, running tests, validating commit messages, or preventing bad code from being committed.

CaptainHook can be integrated into projects via Composer, and it offers flexibility for customizing hooks and plugins, making it easy to enforce project-specific rules. It supports multiple PHP versions, with the latest requiring PHP 8.0​.

In software development, a pipeline refers to an automated sequence of steps used to move code from the development phase to deployment in a production environment. Pipelines are a core component of Continuous Integration (CI) and Continuous Deployment (CD), practices that aim to develop and deploy software faster, more reliably, and consistently.

Main Components of a Software Development Pipeline:

1. Source Control:

   • The process typically begins when developers commit new code to a version control system (e.g., Git). This code commit often automatically triggers the next step in the pipeline.

2. Build Process:

   • The code is automatically compiled and built, transforming the source code into executable files, libraries, or other artifacts. This step also resolves dependencies and creates packages.

3. Automated Testing:

   • After the build process, the code is automatically tested. This includes unit tests, integration tests, functional tests, and sometimes UI tests. These tests ensure that new changes do not break existing functionality and that the code meets the required standards.

4. Deployment:

   • If the tests pass successfully, the code is automatically deployed to a specific environment. This could be a staging environment where further manual or automated testing occurs, or it could be directly deployed to the production environment.

5. Monitoring and Feedback:

   • After deployment, the application is monitored to ensure it functions as expected. Errors and performance issues can be quickly identified and resolved. Feedback loops help developers catch issues early and continuously improve.

Benefits of a Pipeline in Software Development:

• Automation: Reduces manual intervention and minimizes the risk of errors.
• Faster Development: Changes can be deployed to production more frequently and quickly.
• Consistency: Ensures all changes meet the same quality standards through defined processes.
• Continuous Integration and Deployment: Allows code to be continuously integrated and rapidly deployed, reducing the response time to bugs and new requirements.

These pipelines are crucial in modern software development, especially in environments that embrace agile methodologies and DevOps practices.

Inversion of Control (IoC) is a concept in software development that refers to reversing the flow of control in a program. Instead of the code itself managing the flow and instantiation of dependencies, this control is handed over to a framework or container. This facilitates the decoupling of components and promotes higher modularity and testability of the code.

Here are some key concepts and principles of IoC:

1. Dependency Injection (DI): One of the most common implementations of IoC. In Dependency Injection, a component does not instantiate its dependencies; instead, it receives them from the IoC container. There are three main types of injection:

   • Constructor Injection: Dependencies are provided through a class's constructor.
   • Setter Injection: Dependencies are provided through setter methods.
   • Interface Injection: An interface defines methods for providing dependencies.

2. Event-driven Programming: In this approach, the program flow is controlled by events managed by a framework or event manager. Instead of the code itself deciding when certain actions should occur, it reacts to events triggered by an external control system.

3. Service Locator Pattern: Another pattern for implementing IoC. A service locator provides a central registry where dependencies can be resolved. Classes ask the service locator for the required dependencies instead of creating them themselves.

4. Aspect-oriented Programming (AOP): This involves separating cross-cutting concerns (like logging, transaction management) from the main application code and placing them into separate modules (aspects). The IoC container manages the integration of these aspects into the application code.

Advantages of IoC:

• Decoupling: Components are less tightly coupled, improving maintainability and extensibility of the code.
• Testability: Writing unit tests becomes easier since dependencies can be easily replaced with mock objects.
• Reusability: Components can be reused more easily in different contexts.

An example of IoC is the Spring Framework in Java, which provides an IoC container that manages and injects the dependencies of components.