🚀 Build a Complete Selenium Automation Framework from Scratch – Step-by-Step!

If you’ve ever wanted to build a powerful, scalable, and industry-level automation framework, this is your ultimate guide! 💡

Whether you’re a QA Engineer, Test Automation Enthusiast, or Developer, this hands-on framework walkthrough will take you from zero to automation hero — covering everything you need to know to design, implement, and maintain a robust Selenium Framework.

🎥 Watch the complete framework video here:

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💻 What You’ll Learn

In this session, I’ll show you how to build a hybrid, data-driven Selenium Framework using the latest tools and practices.
This framework is built using:

• Java + Selenium + TestNG + Maven

• Log4j for Logging

• Extent Reports for Beautiful Reporting

• Docker + Jenkins + Selenium Grid for CI/CD and distributed testing

• REST Assured integration for API validation

• Parallel Execution, Retry Logic, and Thread-Safe Drivers

You’ll also understand how to:

• Configure and execute your tests in Jenkins Pipelines

• Run your tests in Docker containers

• Perform cross-platform testing with Selenium Grid

• Automate build notifications and email reports

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📘 Framework Documentation (Exclusive Bundle)

Want to follow along with complete documentation and setup guides?
I’ve created a comprehensive bundle that includes everything you need to replicate the framework end-to-end, plus extra resources for CI/CD and Docker integration.

🧾 Course Bundle Includes:

1. Automation Framework Build – Complete Guide

2. Jenkins Setup & First Selenium Job (Freestyle Project)

3. Send Auto Email When Build is Done in Jenkins

4. Run Jenkins Job Automatically on Git Push

5. Selenium Grid Setup

6. Docker for Selenium Grid – Run Tests in Containers

7. Run Selenium Grid using Docker & Jenkins Pipeline

8. Selenium – Top 100 Questions and Answers

💰 Get full documentation access for just ₹299
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🎯 Why You’ll Love This Framework

✅ End-to-end setup from scratch
✅ Easy to customize and reuse for any web app
✅ Covers both UI and API testing
✅ Real-time CI/CD and Docker integration
✅ Perfect for interviews and real-world projects

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🔗 Get Started Now!

1️⃣ Watch the detailed video tutorial:
🎥 https://youtu.be/CpbuG3P9z7g?si=0_Jy18AVRSsoTF2a

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🔥 Turn your automation skills into real project experience and master the tools top QA teams use every day.
If you find this helpful, don’t forget to like, share, and subscribe to my YouTube channel for more upcoming tutorials on Jenkins, Docker, API testing, and CI/CD pipelines.

Keywords: Selenium Framework, Java Selenium, Automation Framework, Test Automation Framework, Jenkins CI/CD, Selenium Grid, Docker for Selenium, Log4j, Extent Reports, REST Assured, TestNG, QA Automation, Selenium Tutorial, Automation Testing, End-to-End Testing, Selenium Framework Documentation.

API Terminologies Explained – HTTP, HTTPS, Methods, and Endpoints

🌐 1️⃣ HTTP & HTTPS

🔸 What is HTTP?

HTTP (HyperText Transfer Protocol) is the foundation of communication on the web.
It defines how data is requested and delivered between a client (like Postman or browser) and a server.

When you type a URL or send an API request:

• The client sends an HTTP request.

• The server processes it and returns a response (data, status code, headers).

🧩 Example:

Request →  GET https://jsonplaceholder.typicode.com/posts/1
Response → 200 OK

🔸 What is HTTPS?

HTTPS (HTTP Secure) is the secure version of HTTP, where communication between client and server is encrypted using SSL/TLS.
This ensures:

• 🔒 Data privacy (cannot be intercepted easily)

• ✅ Authentication (verifies server identity)

• 🛡️ Integrity (data not altered in transit)

💡 In short:
HTTP = plain communication
HTTPS = secure & encrypted communication

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📦 2️⃣ Resource & Payload

🔹 Resource

In an API, everything is treated as a resource — users, posts, products, or orders.
Each resource is identified by a unique URL (endpoint).

🧠 Example:

• /users → represents a collection of users

• /users/5 → represents a single user with ID = 5

So when you make a request:

GET https://dummyjson.com/users/5

You’re requesting the resource “User 5.”

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🔹 Payload

The payload is the data sent to the server in the body of an HTTP request — usually with POST or PUT methods.

🧾 Example (POST request payload):

{
  "name": "Hitendra",
  "email": "hitendra@test.com",
  "role": "admin"
}

Here, this JSON object is the payload that the API receives and processes.

Tip:

• GET requests don’t usually have payloads.

• POST/PUT requests do.

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🧮 3️⃣ HTTP Methods

HTTP methods define what action you want to perform on a resource.
Here are the most common methods used in API testing 👇

Method	Description	Example
GET	Retrieve data from a server	GET /users
POST	Send new data to the server (create resource)	POST /users
PUT	Update an existing resource	PUT /users/3
PATCH	Partially update a resource	PATCH /users/3
DELETE	Remove a resource	DELETE /users/3
HEAD	Same as GET but without body (for metadata)	HEAD /users

💬 Real-life analogy:

Action	Example	HTTP Method
View list of customers	“Show me all users”	GET
Add new customer	“Register a new user”	POST
Update user details	“Change email of user 3”	PUT/PATCH
Remove user	“Delete user 3”	DELETE

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Sample HTTP post request:

🔗 4️⃣ URI, URL, URN, and Endpoint

These four terms often confuse beginners, so let’s simplify them 👇

🧱 URI (Uniform Resource Identifier)

A URI is a general term for identifying a resource — it can be a name, location, or both.
It’s the umbrella term that covers both URL and URN.

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🌍 URL (Uniform Resource Locator)

A URL tells you where a resource is located on the web.
It includes the protocol, domain, and path.

🧾 Example:

https://api.github.com/users/hitendra

Here:

• https → Protocol

• api.github.com → Domain

• /users/hitendra → Path to the resource

So this URL locates the user resource named “hitendra” in GitHub’s API.

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🧾 URN (Uniform Resource Name)

A URN identifies a resource by name, not by its location.
It doesn’t include protocol or domain.

Example:

urn:isbn:9780141033570

This refers to a book by its ISBN number — not where it is stored.

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📍 Endpoint

An Endpoint is the specific URL where an API resource can be accessed.
It’s the address you hit when making API calls.

Example:

Base URL: https://dummyjson.com
Endpoint: /products/10
Full URL: https://dummyjson.com/products/10

📊 Visual Summary Diagram

[Client] → [HTTP/HTTPS Request] → [Server]
        ↘ Resource (e.g., /users/5)
          ↘ Payload (if POST/PUT)
          ↘ Endpoint = Base URL + Resource Path

URI, URL, URN, Endpoint

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🧠 Quick Recap

✅ HTTP – defines communication protocol
✅ HTTPS – secure version of HTTP
✅ Resource – entity (user, post, etc.)
✅ Payload – data sent to server
✅ HTTP Methods – actions on resources
✅ URI = identifier
✅ URL = locator
✅ URN = name
✅ Endpoint = actual callable address

API Testing – What to Verify, Its Advantages & Difference from Web Services

🚀 API Testing – What to Verify, Its Advantages & Difference from Web Services

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🧩 What Exactly Needs to Be Verified in API Testing?

When performing API Testing, the goal isn’t just to check if an endpoint works — it’s to validate how reliably and efficiently the API behaves under various conditions.

Here are the key elements every tester should verify:

1️⃣ Response Status Codes

Each API response carries an HTTP status code that tells you if the request was successful or failed.
Examples:

• ✅ 200 OK – Request successful

• ❌ 400 Bad Request – Invalid request

• 🔒 401 Unauthorized – Authentication required

• 🚫 404 Not Found – Resource doesn’t exist

• 💥 500 Internal Server Error – Server-side issue

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2️⃣ Response Body Validation

Validate whether:

• The data returned matches expected values.

• Field names, data types, and structures align with the API specification.

• No missing or extra fields are returned.

Example:
If the API should return:

{
  "id": 101,
  "name": "John Doe",
  "email": "john@example.com"
}

You must confirm all keys and data types (int, string, etc.) are accurate.

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3️⃣ Response Time & Performance

APIs must respond quickly and consistently.
⏱️ Ideally, response times should be under 1–2 seconds for most business APIs.
You can measure this in Postman or automation frameworks like RestAssured.

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4️⃣ Authentication & Authorization

APIs often use tokens or keys to ensure secure access.
Verify that:

• Unauthorized requests are rejected.

• Valid tokens grant correct access levels.

• Session expiry or token invalidation works properly.

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5️⃣ Error Handling

Good APIs fail gracefully.
Ensure error messages are:

• Readable and consistent.

• Contain useful information without exposing sensitive data.

Example:
❌ Avoid → "SQL Exception: syntax error near 'user_id'"
✅ Prefer → "Invalid input: user_id must be a number"

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6️⃣ Schema & Contract Validation

Use schema validation tools to confirm the API structure remains consistent even after new releases — helping you catch breaking changes early.

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📊 API Verification Flow (Conceptual Diagram)

[Request Sent] 
      ↓
[Server Receives Request]
      ↓
[Process Business Logic]
      ↓
[Generate Response → Validate:
  ✓ Status Code
  ✓ Response Body
  ✓ Headers
  ✓ Time
  ✓ Schema]
      ↓
[Return Response to Client]

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⚡ Advantages of API Testing

API testing provides early and fast feedback before UI layers are even built.
Here’s why every QA professional should focus on API-level validation:

Advantage	Description
1️⃣ Faster Execution	No GUI needed — APIs run directly at the service layer.
2️⃣ Early Bug Detection	You can test logic before the UI exists, reducing rework.
3️⃣ Language Independent	APIs exchange data in JSON/XML — any client can test them.
4️⃣ Reusable Test Automation	Once automated, API tests can run in CI/CD pipelines easily.
5️⃣ Improved Coverage	You can test scenarios difficult to perform via UI.
6️⃣ Better Stability	APIs rarely change compared to frontend elements, giving stable tests.

🧠 Tip: Combine API and UI testing to create a hybrid automation framework, ensuring both layers are verified for complete application coverage.

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🌐 Difference Between API and Web Services

Many testers use “API” and “Web Service” interchangeably — but there’s a subtle difference.

Feature	API	Web Service
Definition	Interface that allows communication between two software components.	A specific type of API that operates over the web (HTTP, SOAP, REST).
Communication Medium	Can use any protocol — HTTP, HTTPS, TCP, etc.	Works only via the web using HTTP/HTTPS.
Data Format	Can exchange data in JSON, XML, or any format.	Usually XML (SOAP) or JSON (RESTful).
Dependency	Can exist without the internet (e.g., OS APIs, Library APIs).	Requires internet/network to communicate.
Example	Java SDK API, Database API, REST API.	SOAP-based weather service, RESTful booking service.

In short:
👉 Every Web Service is an API, but not every API is a Web Service.

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💬 Summary

✔ API testing verifies status codes, data, schema, performance, and security.
✔ It helps detect defects early, ensures data consistency, and supports faster releases.
✔ Understanding the difference between APIs and Web Services helps you design better testing strategies.

API Testing Introduction

 🧪 What is API Testing?

API Testing is the process of verifying whether APIs work as expected — focusing on functionality, reliability, performance, and security.

Unlike UI testing, it doesn’t involve a browser or frontend.
Instead, you directly send requests (GET, POST, PUT, DELETE) and validate responses (status codes, response time, and data).

Key checks during API testing:

• ✅ Is the response status code correct? (e.g., 200, 404, 401)

• ✅ Is the response time within the limit?

• ✅ Are all fields and data types correct?

• ✅ Is authentication/authorization working properly?

• ✅ Are error messages meaningful?

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⚙️ How to Perform API Testing?

You can perform API Testing using manual tools or automation frameworks.

🔹 Manual API Testing

Tools like Postman, Swagger, or Insomnia help testers send requests and analyze responses without writing code.

Basic flow:

1. Launch Postman

2. Create a new request

3. Enter the API endpoint (URL)

4. Select the method (GET/POST/PUT/DELETE)

5. Add headers or authentication if needed

6. Click Send

7. Validate the response body, status code, and time

🔹 Automated API Testing

Automation tools like:

• RestAssured (Java)

• Requests + Pytest (Python)

• Karate DSL

• Postman + Newman

These help run regression suites, integrate with CI/CD (Jenkins, GitHub Actions), and generate reports automatically.

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🔍 Types of APIs

Type	Description	Example
Open APIs (Public APIs)	Available to everyone; used by third parties.	Google Maps, OpenWeather API
Internal APIs (Private APIs)	Used only within an organization for internal systems.	HRMS ↔ Payroll System
Partner APIs	Shared between specific business partners; require access tokens.	Travel site ↔ Airline partner
Composite APIs	Combine multiple endpoints in one call.	Fetch order + shipping + payment info in one response

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📘 Quick Recap

✅ API = Communication Bridge between two systems
✅ API Testing = Validating request & response
✅ Can be done manually (Postman) or automated (RestAssured, Python, etc.)
✅ Focus on status codes, response data, time, and security
✅ APIs can be Public, Private, Partner, or Composite

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🧠 Pro Tip

Start practicing with free APIs like:
🔹 https://reqres.in
🔹 https://jsonplaceholder.typicode.com
🔹 https://dummyjson.com
These are perfect for learning GET, POST, PUT, DELETE methods.

Latest Technology Trends in Software Testing

Software testing is an essential part of the software development process, and it has evolved significantly over the years as new technologies and approaches have emerged. Here are some of the latest technology trends in software testing:

1. Artificial intelligence (AI) and machine learning (ML): AI and ML are being increasingly used in software testing to improve the efficiency and effectiveness of the testing process. For example, AI can be used to analyze test results and identify patterns that may indicate defects or other issues. ML can be used to create and execute test cases based on machine learning algorithms, which can help to identify previously unknown defects or test scenarios that may have been overlooked by human testers.
2. Continuous testing: Continuous testing is an approach that involves running automated tests continuously throughout the software development process. This helps to identify and fix defects early in the development process, which can reduce the overall cost of testing and improve the quality of the software. Continuous testing requires the use of automation tools and a culture of collaboration and continuous integration.
3. Test-driven development (TDD): TDD is a software development approach in which tests are written before the code is written. The goal of TDD is to ensure that the code meets the specified requirements and is of high quality. TDD can help to improve the quality of the software and accelerate the development process by identifying and fixing defects early in the development process.
4. Agile and DevOps: Agile and DevOps are software development methodologies that emphasize rapid iteration and continuous delivery of software. They both rely on automation to accelerate the development and testing process. Agile development is based on short development cycles (called "sprints") in which teams work to deliver incremental improvements to the software. DevOps is a culture and set of practices that emphasizes collaboration and communication between software developers and IT operations teams.
5. Cloud-based testing: Cloud-based testing involves using cloud-based platforms and tools to conduct software testing. This can help to reduce the cost and complexity of testing by eliminating the need to maintain on-premises testing infrastructure. Cloud-based testing also enables organizations to scale their testing efforts up or down as needed and to access a wide range of testing environments and configurations.
6. Mobile testing: The increasing use of mobile devices has led to the development of specialized tools and approaches for testing mobile applications. Mobile testing involves verifying that the software functions correctly on different mobile devices and operating systems. It may also involve testing the software's performance and usability on different mobile networks and under different conditions.
7. Internet of Things (IoT) testing: IoT testing involves verifying the functionality and performance of software that runs on IoT devices. This may include testing the software's ability to communicate with other devices and systems, as well as its ability to handle large volumes of data. IoT testing may also involve testing the security and privacy of the software.

Overall, these are just a few examples of the latest technology trends in software testing. It is important for organizations to stay up-to-date on these trends and to evaluate which ones are the best fit for their specific testing needs. By adopting the latest technologies and approaches, organizations can improve the efficiency and effectiveness of their testing efforts and deliver high-quality software to their customers.

Agile and DevOps, test automation, artificial intelligence for testing

Agile and DevOps are software development methodologies that emphasize rapid iteration and continuous delivery of software. They both rely on automation to accelerate the development and testing process.

Agile is a project management approach that emphasizes flexibility and rapid iteration. It is based on the Agile Manifesto, which values "individuals and interactions over processes and tools" and "working software over comprehensive documentation." Agile development is often characterized by short development cycles (called "sprints") in which teams work to deliver incremental improvements to the software.

DevOps is a culture and set of practices that emphasizes collaboration and communication between software developers and IT operations teams. It aims to reduce the time and effort required to deliver software by automating and streamlining the build, test, and deployment process.

Test automation is the use of software to automate the process of testing software. It involves creating and executing automated test cases to validate the functionality and performance of the software. Test automation can help to accelerate the testing process and improve the accuracy and reliability of test results.

There are many benefits to using test automation in the context of Agile and DevOps. For example:

Speed: Automated test cases can be run much faster than manual tests, which can help to accelerate the development and testing process.

Accuracy: Automated test cases are less prone to human error than manual tests, which can help to improve the accuracy and reliability of test results.

Coverage: Automated test cases can be designed to test a wide range of scenarios and edge cases, which can help to improve the coverage of the testing process.

Repeatability: Automated test cases can be run multiple times without the need for human intervention, which can help to ensure that the software is tested consistently and thoroughly.

Artificial intelligence (AI) can be used to enhance the process of testing software in a number of ways. For example, AI can be used to analyze test results and identify patterns that may indicate defects or other issues. This can help to improve the efficiency and effectiveness of the testing process by identifying potential issues more quickly and accurately.

AI can also be used to create and execute test cases based on machine learning algorithms. These algorithms can analyze the software and identify test scenarios that may have been overlooked by human testers. This can help to identify previously unknown defects and improve the coverage of the testing process.

In the context of Agile and DevOps, test automation and AI can be used to support the rapid iteration and continuous delivery of software. By automating the testing process and using AI to analyze and optimize test results, organizations can reduce the time and effort required to test software and accelerate the development and delivery process.

However, it is important to note that test automation and AI are not a substitute for human testing. While they can be very useful tools, they are not able to replicate the creativity and critical thinking skills of human testers. As such, it is important to use a combination of automated and manual testing to ensure that the software is thoroughly tested and of high quality.

Overall, the combination of Agile and DevOps, test automation, and AI can help organizations to develop and deliver high-quality software more efficiently and effectively. By leveraging these technologies, organizations can improve their ability to respond to changing market needs and deliver value to customers more quickly. However, it is important to carefully evaluate the suitability of these technologies for a given project and to use them in combination with human testing to ensure the best results.

What is Codeless Automated Testing?

Codeless automated testing is a testing approach that allows testers to create and execute automated test cases without the need to write code. Instead of writing code, testers use a visual interface or a set of pre-defined commands to create and execute test cases.

One of the main benefits of codeless automated testing is that it allows testers with limited coding skills to create and execute automated tests. This can help to accelerate the testing process and make it more accessible to a wider range of testers. For example, a tester who is not familiar with programming languages can still create and run automated tests using a codeless testing tool.

Another benefit of codeless automated testing is that it can reduce the time and effort required to maintain test cases. Since no code needs to be written, there is less need to update and maintain test cases as the software changes. This can help to reduce the overall cost of testing and make it more efficient.

There are several different tools and platforms available for codeless automated testing. These tools typically provide a visual interface or a set of pre-defined commands that testers can use to create and execute test cases. Some common features of codeless automated testing tools include:

Record and playback functionality: This allows testers to record their actions as they test the software manually, and then play them back automatically to create an automated test case.

Object recognition: This allows the tool to identify and interact with specific elements on the screen, such as buttons or input fields.

Test case management: This allows testers to organize and manage their test cases, including the ability to create and edit test cases, view test results, and track defects.

Test data management: This allows testers to create and manage test data, including the ability to create and edit test data, view test results, and track defects.

Integration with other tools: Many codeless automated testing tools can be integrated with other tools and platforms, such as defect tracking systems, continuous integration systems, and test management systems. This can help to streamline the testing process and make it more efficient.

While codeless automated testing can offer many benefits, it is important to note that it may not be suitable for all testing scenarios. In some cases, writing custom code may be necessary to fully test the software. For example, custom code may be required to test complex logic or to interact with third-party systems or APIs. Additionally, codeless automated testing may not provide the same level of flexibility and control as code-based automated testing.

Despite these limitations, codeless automated testing can be a useful approach for testers who want to create and execute automated tests without the need to write code. It can help to accelerate the testing process and make it more accessible to a wider range of testers, while also reducing the time and effort required to maintain test cases.

In conclusion, codeless automated testing is a valuable tool for testers who want to create and execute automated tests without the need to write code. It can help to accelerate the testing process and make it more efficient, while also making it more accessible to a wider range of testers. However, it is important to carefully evaluate the suitability of codeless automated testing for a given testing scenario, as it may not always be the best fit.

There are several codeless automation tools available in the market, each with its own unique features and capabilities. Some of the more popular codeless automation tools include:

Selenium IDE: This is an open-source browser extension that allows testers to record and play back test cases in the browser. It supports a wide range of browsers, including Chrome, Firefox, and Safari.

TestComplete: This is a commercial automated testing tool that allows testers to create and execute test cases for desktop, web, and mobile applications. It features an easy-to-use visual interface and supports a wide range of programming languages.

TestProject: This is an open-source automated testing platform that allows testers to create and execute test cases for web, mobile, and API applications. It features a visual interface and integrations with popular defect tracking and continuous integration tools.

UiPath: This is a commercial robotic process automation (RPA) platform that allows users to automate repetitive tasks by creating and executing automated workflows. It features a visual interface and integrations with a wide range of applications and systems.

Katalon Studio: This is a free, open-source automated testing platform that allows testers to create and execute test cases for web, mobile, and API applications. It features a visual interface and supports a wide range of programming languages.

Testim: This is a commercial automated testing platform that allows testers to create and execute test cases for web and mobile applications. It features a visual interface and integrations with popular defect tracking and continuous integration tools.

These are just a few examples of the many codeless automation tools available in the market. It is important to carefully evaluate the features and capabilities of each tool to determine which one is the best fit for your specific testing needs.

Defect/Bug Life Cycle

Defect Life Cycle:

• Defect life cycle, also known as Bug Life cycle is the journey of a defect cycle, which a defect goes through during its lifetime.
• It varies from organization to organization and also from project to project as it is governed by the software testing process and also depends upon the tools used.
• Defect Life Cycle is a cyclic process, which describes how a defect or bug passes through different stages from the identification stage to the Fixing stage. it begins when a tester finds or logs a bug and it ends when the bug is fixed.
• If Developer reject a defect understand the reason why defect is rejected , if developer is correct we can close the defect or else we can discuss it with test lead or project lead and than reopen the defect.

Some of the familiar values used for defects, during their life cycle are :

• New : New defect is reported.
• Open : The developer is currently working on the defect.
• Fixed : The code changes are completed and the defect is resolved .
• Deferred : Developers will fixed the defect later.
• Duplicate : The defect is same like one of the previous defect. When previous is fixed it also fixed.
• Retest : the tester starts the task of retesting the defect to verify if the defect is fixed or not.
• Rejected : Developers did not accept the defect .
• Close : After re test if defect is working correctly .
• Reopen : After re test if defect is still exist then we reopen the defect.
• Not a Bug : If the defect does not have an impact on the functionality of the application, then the status of the defect gets changed to “Not a Bug”.
• There are others of course, and some groups might use combinations of these values (such as Closed-Fixed, Closed-WontFix, etc.).