Aspect-Oriented Programming (AOP) is a programming paradigm focused on modularizing cross-cutting concerns—aspects of a program that affect multiple parts of the codebase and don't fit neatly into object-oriented or functional structures.

💡 Goal:

Typical cross-cutting concerns include logging, security checks, error handling, transaction management, or performance monitoring. These concerns often appear in many classes and methods. AOP allows you to write such logic once and have it automatically applied where needed.

🔧 Key Concepts:

• Aspect: A module that encapsulates a cross-cutting concern.

• Advice: The actual code to be executed (e.g., before, after, or around a method call).

• Join Point: A point in the program flow where an aspect can be applied (e.g., method execution).

• Pointcut: A rule that defines which join points are affected (e.g., "all methods in class X").

• Weaving: The process of combining aspects with the main program code—at compile-time, load-time, or runtime.

🛠 Example (Java with Spring AOP):

@Aspect
public class LoggingAspect {
    @Before("execution(* com.example.service.*.*(..))")
    public void logBeforeMethod(JoinPoint joinPoint) {
        System.out.println("Calling method: " + joinPoint.getSignature().getName());
    }
}

This code automatically logs a message before any method in the com.example.service package is executed.

✅ Benefits:

• Improved modularity

• Reduced code duplication

• Clear separation of business logic and system-level concerns

❌ Drawbacks:

• Can reduce readability (the flow isn't always obvious)

• Debugging can become more complex

• Often depends on specific frameworks (e.g., Spring, AspectJ)

Design by Contract (DbC) is a concept in software development introduced by Bertrand Meyer. It describes a method to ensure the correctness and reliability of software by defining clear "contracts" between different components (e.g., methods, classes).

Core Principles of Design by Contract

In DbC, every software component is treated as a contract party with certain obligations and guarantees:

1. Preconditions
   Conditions that must be true before a method or function can execute correctly.
   → Responsibility of the caller.

2. Postconditions
   Conditions that must be true after the execution of a method or function.
   → Responsibility of the method/function.

3. Invariant (Class Invariant)
   Conditions that must always remain true throughout the lifetime of an object.
   → Responsibility of both the method and the caller.

Goal of Design by Contract

• Clear specification of responsibilities.

• More robust and testable software.

• Errors are detected early (e.g., through contract violations).

Example in Pseudocode

class BankAccount {
    private double balance;

    // Invariant: balance >= 0

    void withdraw(double amount) {
        // Precondition: amount > 0 && amount <= balance
        if (amount <= 0 || amount > balance) throw new IllegalArgumentException();

        balance -= amount;

        // Postcondition: balance has been reduced by amount
    }
}

Benefits

• Clear contracts reduce misunderstandings.

• Easier debugging, as violations are detected immediately.

• Supports defensive programming.

Drawbacks

• Requires extra effort to define contracts.

• Not directly supported by all programming languages (e.g., Java and C++ via assertions, Python with decorators; Eiffel supports DbC natively).

SLD (Styled Layer Descriptor) is an XML-based standard developed by the Open Geospatial Consortium (OGC). It is used to define the styling of geospatial data in web mapping services like WMS (Web Map Service).

What does SLD do?

SLD describes how certain geospatial features should be rendered on a map — meaning it defines colors, lines, symbols, labels, and more. With SLD, you can specify things like:

• Roads should appear red.

• Water bodies in blue, with a certain transparency.

• Points should have symbols that vary depending on attribute values (e.g., population).

• Text labels over features.

Technically:

• SLD is an XML file with a defined structure.

• It can be read by WMS servers like GeoServer or MapServer.

• The file includes Rules, Filters, and Symbolizers like LineSymbolizer, PolygonSymbolizer, or TextSymbolizer.

Example of a simple SLD snippet:

<Rule>
  <Name>Water Bodies</Name>
  <PolygonSymbolizer>
    <Fill>
      <CssParameter name="fill">#0000FF</CssParameter>
    </Fill>
  </PolygonSymbolizer>
</Rule>

Why is it useful?

• To create custom-styled maps (e.g., thematic maps).

• To define styling server-side, so the map is rendered correctly regardless of the client.

• For interactive web GIS applications that react to attribute values.

If you're working with geospatial data — for example in QGIS or GeoServer — you'll likely come across SLD when you need fine-grained control over how your maps look.

A hyperscaler is a company that provides cloud services on a massive scale — offering IT infrastructure such as computing power, storage, and networking that is flexible, highly available, and globally scalable. Common examples of hyperscalers include:

• Amazon Web Services (AWS)

• Microsoft Azure

• Google Cloud Platform (GCP)

• Alibaba Cloud

• IBM Cloud (on a somewhat smaller scale)

Key characteristics of hyperscalers:

1. Massive scalability
   They can scale their services virtually without limits, depending on the customer's needs.

2. Global infrastructure
   Their data centers are distributed worldwide, enabling high availability, low latency, and redundancy.

3. Automation & standardization
   Many operations are automated (e.g., provisioning, monitoring, billing), making services more efficient and cost-effective.

4. Self-service & pay-as-you-go
   Customers usually access services via web portals or APIs and pay only for what they actually use.

5. Innovation platform
   Hyperscalers offer not only infrastructure (IaaS), but also platform services (PaaS), as well as tools for AI, big data, or IoT.

What are hyperscalers used for?

• Hosting websites or web applications

• Data storage (e.g., backups, archives)

• Big data analytics

• Machine learning / AI

• Streaming services

• Corporate IT infrastructure

A Materialized View is a special type of database object that stores the result of a SQL query physically on disk, unlike a regular view which is computed dynamically every time it’s queried.

Key Characteristics of a Materialized View:

• Stored on disk: The result of the query is saved, not just the query definition.

• Faster performance: Since the data is precomputed, queries against it are typically much faster.

• Needs refreshing: Because the underlying data can change, a materialized view must be explicitly or automatically refreshed to stay up to date.

Comparison: View vs. Materialized View

Example:

-- Creating a materialized view in PostgreSQL
CREATE MATERIALIZED VIEW top_customers AS
SELECT customer_id, SUM(order_total) AS total_spent
FROM orders
GROUP BY customer_id;

To refresh the data:

REFRESH MATERIALIZED VIEW top_customers;

When to use it?

• For complex aggregations that are queried frequently

• When performance is more important than real-time accuracy

• In data warehouses or reporting systems

Vite is a modern build tool and development server for web applications, created by Evan You, the creator of Vue.js. It is designed to make the development and build processes faster and more efficient. The name "Vite" comes from the French word for "fast," reflecting the primary goal of the tool: a lightning-fast development environment.

The main features of Vite are:

1. Fast Development Server: Vite uses modern ES modules (ESM), providing an ultra-fast development server. It only loads the latest module, making the initial startup much faster than traditional bundlers.

2. Hot Module Replacement (HMR): HMR works extremely fast by updating only the changed modules, without needing to reload the entire application.

3. Modern Build System: Vite uses Rollup under the hood to bundle the final production build, enabling optimized and efficient builds.

4. Zero Configuration: Vite is very user-friendly and doesn’t require extensive configuration. It works immediately with the default settings, supporting many common web technologies out-of-the-box (e.g., Vue.js, React, TypeScript, CSS preprocessors, etc.).

5. Optimized Production: For production builds, Rollup is used, which is known for creating efficient and optimized bundles.

Vite is mainly aimed at modern web applications and is particularly popular with developers working with frameworks like Vue, React, or Svelte.

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.

Salesforce Apex is an object-oriented programming language specifically designed for the Salesforce platform. It is similar to Java and is primarily used to implement custom business logic, automation, and integrations within Salesforce.

Key Features of Apex:

• Cloud-based: Runs exclusively on Salesforce servers.

• Java-like Syntax: If you know Java, you can learn Apex quickly.

• Tightly Integrated with Salesforce Database (SOQL & SOSL): Enables direct data queries and manipulations.

• Event-driven: Often executed through Salesforce triggers (e.g., record changes).

• Governor Limits: Salesforce imposes limits (e.g., maximum SOQL queries per transaction) to maintain platform performance.

Uses of Apex:

• Triggers: Automate actions when records change.

• Batch Processing: Handle large data sets in background jobs.

• Web Services & API Integrations: Communicate with external systems.

• Custom Controllers for Visualforce & Lightning: Control user interfaces.

Memcached is a distributed in-memory caching system commonly used to speed up web applications. It temporarily stores frequently requested data in RAM to avoid expensive database queries or API calls.

Key Features of Memcached:

• Key-Value Store: Data is stored as key-value pairs.

• In-Memory: Runs entirely in RAM, making it extremely fast.

• Distributed: Supports multiple servers (clusters) to distribute load.

• Simple API: Provides basic operations like set, get, and delete.

• Eviction Policy: Uses LRU (Least Recently Used) to remove old data when memory is full.

Common Use Cases:

• Caching Database Queries: Reduces load on databases like MySQL or PostgreSQL.

• Session Management: Stores user sessions in scalable web applications.

• Temporary Data Storage: Useful for API rate limiting or short-lived data caching.

Memcached vs. Redis:

• Memcached: Faster for simple key-value caching, scales well horizontally.

• Redis: Offers more features like persistence, lists, hashes, sets, and pub/sub messaging.

Installation & Usage (Example for Linux):

sudo apt update && sudo apt install memcached
sudo systemctl start memcached

It can be used with PHP or Python via appropriate libraries.

A spider (also called a web crawler or bot) is an automated program that browses the internet to index web pages. These programs are often used by search engines like Google, Bing, or Yahoo to discover and update content in their search index.

How a Spider Works:

1. Starting Point: The spider begins with a list of URLs to crawl.

2. Analysis: It fetches the HTML code of a webpage and analyzes its content, links, and metadata.

3. Following Links: It follows the links found on the page to discover new pages.

4. Storage: The collected data is sent to the search engine’s database for indexing.

5. Repetition: The process is repeated regularly to keep the index up to date.

Uses of Spiders:

• Search engine optimization (SEO)

• Price comparison websites

• Web archiving (e.g., Wayback Machine)

• Automated content analysis for AI models

Some websites use a robots.txt file to specify which areas can or cannot be crawled by a spider.