Merge pull request #444 from Abbhiishek/microservice-error-guessing-glossary-terms

feat: Add new glossary term for "Microservice Testing" & "Error Guessing"

Author: TvisharajiK

src/pages/concepts/reference/glossary.js

@@ -1,4 +1,4 @@
-import React, {useEffect, useState} from "react";
+import React, {useState} from "react";
 import Layout from "@theme/Layout";
 import useDocusaurusContext from "@docusaurus/useDocusaurusContext";
 
@@ -55,6 +55,10 @@ function Glossary() {
         name: "End To End Testing",
         link: "/docs/concepts/reference/glossary/end-to-end-testing",
       },
+      {
+        name: "Error Guessing",
+        link: "/docs/concepts/reference/glossary/error-guessing",
+      },
     ],
     F: [
       {
@@ -87,6 +91,10 @@ function Glossary() {
         name: "Mocks",
         link: "/docs/concepts/reference/glossary/mocks",
       },
+      {
+        name: "Microservice Testing",
+        link: "/docs/concepts/reference/glossary/microservice-testing",
+      },
     ],
     R: [
       {

versioned_docs/version-2.0.0/concepts/reference/glossary/error-guessing.md

@@ -0,0 +1,40 @@
+---
+id: error-guessing
+title: Error Guessing
+sidebar_label: Error Guessing
+description: This glossary has an explanation of all the terminologies that beginners find difficult to understand at first glance.
+tags:
+  - explanation
+  - glossary
+keywords:
+  - API
+---
+
+## What is Error Guessing?
+
+Error guessing is an intuitive and experience-based software testing technique that relies on developer and tester's knowledge and creativity to identify potential defects in a system. This method involves anticipating where errors are likely to occur based on past experiences, common programming mistakes, and an understanding of the system's architecture.
+
+## Key aspects
+
+- **Intuition:** Testers use their instincts and experience to predict where errors might lurk.
+- **Domain knowledge:** Understanding the application's purpose and typical user behavior helps in identifying potential issues.
+- **Historical data:** Past bugs and common error patterns inform the guessing process.
+- **Creativity:** Testers think outside the box to imagine scenarios that might cause failures.
+
+## Benefits
+
+- **Uncovers unique defects:** Can reveal issues missed by systematic testing approaches.
+- **Cost-effective:** Requires minimal setup and can be performed quickly.
+- **Improves over time:** The technique becomes more effective as testers gain experience.
+- **Adaptable:** Can be applied to various types of software and testing phases.
+
+## Challenges
+
+- **Subjectivity:** Relies heavily on individual tester's skills and experience.
+- **Lack of structure:** May not provide comprehensive coverage of all system aspects.
+- **Difficult to replicate:** Success varies between testers and isn't easily standardized.
+- **Time-consuming:** Can be inefficient if not guided by experience or historical data.
+
+## Conclusion
+
+While error guessing is not systematic like other testing methods, it can be highly effective when combined with more structured approaches. It allows testers to explore edge cases and unusual scenarios that might be overlooked by conventional test cases. However, the success of error guessing largely depends on the tester's expertise and familiarity with the system. As such, it's often used as a complementary technique rather than a standalone method in comprehensive testing strategies.

versioned_docs/version-2.0.0/concepts/reference/glossary/microservice-testing.md

@@ -0,0 +1,53 @@
+---
+id: microservice-testing
+title: Microservice Testing with Keploy
+sidebar_label: Microservice Testing
+description: This glossary has an explanation of all the terminologies that beginners find difficult to understand at first glance.
+tags:
+  - explanation
+  - glossary
+keywords:
+  - API
+---
+
+## What is Microservices Testing?
+
+Microservice testing is the process of validating individual components of a microservices architecture to ensure they function correctly both in isolation and as part of the larger system. Unlike monolithic applications, microservices present unique challenges in testing due to their distributed nature and complex interactions.
+
+## Benefits of Microservices Testing:
+
+- **Improved fault isolation**: Testing individual services allows for easier identification and resolution of issues.
+- **Faster deployment cycles**: Independent testing of services enables faster release cycles.
+- **Enhanced scalability**: Testing services in isolation helps identify bottlenecks and optimize performance.
+- **Easier maintenance and updates**: Testing microservices independently reduces the risk of regressions.
+- **Better support for continuous integration and delivery (CI/CD)** : Microservices testing enables automated testing and deployment pipelines.
+
+## Challenges in Microservices Testing:
+
+- **Complex service dependencies** :
+
+  - Microservices often rely on other services, databases, or third-party APIs, making it challenging to test in isolation.
+
+- **Difficulty in replicating production environments**
+  - Testing microservices in a production-like environment can be complex and resource-intensive.
+- **Increased network latency and failures**
+  - Inter-service communication can introduce latency and failures, making testing more challenging.
+- **Data consistency across services**
+  - Ensuring data consistency and integrity across multiple services can be difficult.
+- **Managing test data for multiple services**
+  - Creating and managing test data for multiple services can be time-consuming and error-prone.
+
+## Overcoming Challenges with Keploy
+
+Keploy is an innovative testing tool designed to address many of the challenges associated with microservices testing. Here's how it helps:
+<img src="https://keploy.io/docs/gif/record-replay.gif?raw=true"/>
+<br/>
+
+- **Automated Test Case Generation**: Keploy can generate test cases by recording your application's network calls. This automation significantly reduces the time and effort required to create comprehensive test suites.
+- **Dependency Mocking**: Keploy automatically generates dependency mocks based on recorded network interactions. This feature allows for faster and more efficient testing compared to traditional unit tests.
+- **Realistic Testing Environment**: With its built-in proxy setup, Keploy records system calls between services, creating a more accurate representation of the production environment in your tests.
+- **Efficient Integration Testing**: By capturing and replaying inter-service communications, Keploy enables more effective integration testing without the need to set up complex environments.
+- **Reduced Test Maintenance**: As Keploy generates tests based on actual system behavior, it helps keep tests up-to-date with changes in the microservices, reducing the maintenance burden.
+- **Performance Testing**: The recorded interactions can be used to simulate realistic load scenarios, aiding in performance testing of microservices.
+
+By leveraging Keploy's capabilities, development teams can overcome many of the traditional challenges associated with microservices testing, leading to more robust and reliable distributed systems.