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

๐ŸŒ 1️⃣ HTTP & HTTPS

๐Ÿ”ธ 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).

๐Ÿงฉ Example:

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

๐Ÿ”ธ 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:

๐Ÿ’ก In short:
HTTP = plain communication
HTTPS = secure & encrypted communication


๐Ÿ“ฆ 2️⃣ Resource & Payload

๐Ÿ”น Resource

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

๐Ÿง  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.”


๐Ÿ”น Payload

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

๐Ÿงพ 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.


๐Ÿงฎ 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 ๐Ÿ‘‡

MethodDescriptionExample
GETRetrieve data from a serverGET /users
POSTSend new data to the server (create resource)POST /users
PUTUpdate an existing resourcePUT /users/3
PATCHPartially update a resourcePATCH /users/3
DELETERemove a resourceDELETE /users/3
HEADSame as GET but without body (for metadata)HEAD /users

๐Ÿ’ฌ Real-life analogy:

ActionExampleHTTP 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

Sample HTTP post request:


๐Ÿ”— 4️⃣ URI, URL, URN, and Endpoint

These four terms often confuse beginners, so let’s simplify them ๐Ÿ‘‡

๐Ÿงฑ 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.


๐ŸŒ URL (Uniform Resource Locator)

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

๐Ÿงพ 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.


๐Ÿงพ 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.


๐Ÿ“ 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

๐Ÿ“Š 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




๐Ÿง  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

๐Ÿš€ API Testing – What to Verify, Its Advantages & Difference from Web Services


๐Ÿงฉ 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:


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.


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.


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.


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"


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.


๐Ÿ“Š API Verification Flow (Conceptual Diagram)

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

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:

AdvantageDescription
1️⃣ Faster ExecutionNo GUI needed — APIs run directly at the service layer.
2️⃣ Early Bug DetectionYou can test logic before the UI exists, reducing rework.
3️⃣ Language IndependentAPIs exchange data in JSON/XML — any client can test them.
4️⃣ Reusable Test AutomationOnce automated, API tests can run in CI/CD pipelines easily.
5️⃣ Improved CoverageYou can test scenarios difficult to perform via UI.
6️⃣ Better StabilityAPIs rarely change compared to frontend elements, giving stable tests.

๐Ÿง  Tip: Combine API and UI testing to create a hybrid automation framework, ensuring both layers are verified for complete application coverage.


๐ŸŒ Difference Between API and Web Services

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

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

In short:
๐Ÿ‘‰ Every Web Service is an API, but not every API is a Web Service.


๐Ÿ’ฌ 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

 ๐Ÿงช 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?


⚙️ How to Perform API Testing?

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

๐Ÿ”น 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

๐Ÿ”น Automated API Testing

Automation tools like:

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


๐Ÿ” Types of APIs

TypeDescriptionExample
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 APIsShared between specific business partners; require access tokens.Travel site ↔ Airline partner
Composite APIsCombine multiple endpoints in one call.Fetch order + shipping + payment info in one response

๐Ÿ“˜ 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


๐Ÿง  Pro Tip

Start practicing with free APIs like:
๐Ÿ”น https://reqres.in
๐Ÿ”น https://jsonplaceholder.typicode.com
๐Ÿ”น 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.).

Defect Report | Priority and Severity

Defect Report: 

  • If application is not working as expected we can report that as defect in defect report. 
  • A defect report is a document that has concise details about what defects are identified, what action steps make the defects show up, and what are the expected results instead of the application showing error (defect) while taking particular step by step actions.
  • Defect Reporting, Defect Tracking, and Status Tracking is called Defect Management. Some companies use Manual Process (Excel workbook), and some companies use Tool-based processes for Defect Management. 
  • Defect Management Tools Examples: Bugzilla / Issue-Tracker / PR-Tracker etc.
    Important fields of a Defect Report template:
  • Defect Id :  It is a unique number for every defect we found while testing.
  • Summary :  Full description of the defect .
  • Detected By : Name of the tester who found the defect .
  • Assigned to :  Currently the defect is assign to whom. When a tester found a defect the it has to assign to any developer.
  • Severity : Severity defines how impactful a bug can be to the system. It can values either high or medium or low specifies the seriousness of the defect.
  • Priority : Priority indicates how soon the bug should be fixed. It can values either high or medium or low specifies the importance of the defect or functionality. The defect are fixed based on priorities.

    Defect Status in defect life cycle is the present state from which the defect or a bug is currently undergoing. The goal of defect status is to precisely convey the current state or progress of a defect in order to better track and understand the actual progress of the defect lifecycle. 
  • Build version : It show currently build version in which we are testing. We  can check this from release note document. 
  • Module : In which module the defect is found.
  • Environment :  The defect is found in which environment like : Test environment, UAT or Production environment.
  • Defect Type :  Specify the type of defect like functional , network , data , performance or UI ( User Interface) etc.
  • Reproduceable : It has value either YES or NO:
                YES: Every time the defect is occurring .
                NO: Most of the time its working correctly, only few cases it is failing and not able to reproduce  
  • ( If the defect is non reproduceable we can take screen shot of the defect and report it along with the defect.)
  • Reproduce Steps : Specify the navigation steps to reproduce the defect.


Test Execution Process | Environment setup

Test Execution:

  • Test execution is the process of executing the test cases and comparing the expected and actual results.
  • After developers finish the coding and give the build to the tester , tester will conduct the testing and validate the application as per the requirement.
  • The developers will prepare the below document and give to the testing team during the build release :
SRN (software release note)
DD (Deployment Document)
  • Tester deploy the build in test environment a per the instruction in the release document note .
  • The build is deployed in the test environment either by tester or developer or n/w team. 

  • As we know after build release 1st test should be performed is sanity test .
  • After Sanity test is pass we will continue test execution and validate all the functionality.
  • Test execution can be done either manual aur automation.
  • Testing performed by tester without using any tools is called manual testing.
  • Testing conducted with the help of tool is called automation testing.
  • During execution validate all the test cases and specify actual result and status.
  • If the status is fail we can report that as defect to the developers.

SRN (software release note)

  • A release note refers to the technical documentation produced and distributed alongside the launch of a new software product or a product update.
  • It briefly describes a new product or specific detail level changes included in a product update.
  • A software release notes template is a simple document that companies use to document any changes to their product. Elements of release notes template are like : 
  • Build version , build location , requirement in build , Precondition , environment , deployment steps , known issue , defect files , prepare by.

Requirement Traceability Matrix

Traceability Matrix:

  • In this document the test cases are mapped to the corresponding requirement to ensure the coverage of test cases, to find any gap between requirement and test cases.
  • It is also known as Requirement Traceability Matrix (RTM) or Cross Reference Matrix (CRM).
  • It is prepared before the test execution process.
  • This document is designed to make sure that each requirement has a test case. 
  • The test engineer will prepare TM for their respective assign modules, and then it will be sent to the Test Lead. Then test lead consolidate all and prepare one TM document for project.

Goals of Traceability Matrix:

  • It allows you to see if a requirement is fully documented or not. A requirement traceability matrix can even call attention to missing requirements. 
  • It ensures that the software completely meets the customer's requirements.
  • A traceability matrix can help in the effort to provide proper and consistent documentation for your team. 
  • It helps in detecting the root cause of any bug.

Types of Traceability Matrix:

The traceability matrix can be classified into three different types which are as follows:  

  • Forward Traceability
  • Backward or reverse Traceability
  • Bi-directional Traceability

Forward Traceability:

Forward traceability is used to map the requirements to the test cases.

  • Not only this will establish that every requirement is being tested from top to bottom, but it will also assist in confirming that a project’s trajectory is sound. 
  • The main objective of this is to verify whether the product developments are going in the right direction.

Backward or reverse Traceability:

You can make a backward traceability matrix by mapping test cases with the requirements. 

  • The reverse or backward traceability is used to check that we are not increasing the space of the product by enhancing the design elements, code, test other things which are not mentioned in the business needs. 
  • The main objective of this that the existing project remains in the correct direction.

Bi-directional Traceability:

Bidirectional traceability essentially combines forward and backward traceability into one document. 

  • This type is useful because it establishes that each requirement has relating test cases. 
  • It also evaluates the modification in the requirement which is occurring due to the bugs in the application.