Release Name: Inji Verify v0.10.0

Support: Developer

Release Date: 10th Oct, 2024

Overview

We are excited to announce the release of Inji Verify version 0.10.0, which brings significant improvements to the platform, including the implementation of OpenID for Verifiable Presentations (OpenID4VP) specifications, enhanced error handling scenarios, and support for new QR code sharing mechanisms. This release also includes crucial bug fixes, Docker Compose enhancements, and scanner library upgrades.

New Features

• QR Code Handling Enhancements

  • Previously, JSON-LD VCs embedded in QR codes were dense and difficult to scan. To address this, the QR codes now embed the URL of the VC storage instead of the entire VC. This allows for easier scanning and sharing of credentials. Additionally, a configuration-based approach has been introduced to manage QR code content per issuer and credential type.

  • The sharing of credentials via QR codes has been streamlined. Users can now scan the QR code from either a physical copy or a smartphone, which redirects to Inji Web to authorize and present the VP to Inji Verify.

    • User Flow for Sharing:

      • The user downloads a VC as a PDF or has a physical copy from Inji Web.

      • The user scans the QR code using Inji Verify.

      • Inji Verify redirects to Inji Web for authorization, retrieves the VC in VP format, and completes the verification.

• Error Handling Scenarios - OpenID4VP

  • Introduced comprehensive error handling scenarios as per the OpenID4VP specification to ensure robustness during Verifiable Presentation transactions. This ensures that issues such as invalid credentials or expired tokens are handled gracefully with informative error messages.

• Docker Compose

  • This release simplifies deployment with Docker Compose, allowing users to easily set up and configure the Inji Verify environment.

• React-scanner-lib Upgrade The React scanner library has been upgraded for improved performance and reliability in scanning QR codes.

  • ZXing-cpp library

  • PDF.js Integration

• Updation of Pixel Pass library for Sunbird QR Code

  • To properly manage binary data by unzipping it before sending it back, the Pixel pass library has been updated to ensure backward compatibility of Sunbird QR codes.

• Critical Bug Fixes

  • Several critical bugs have been resolved, including issues with QR code generation and scanning, ensuring a smoother verification experience.

Additional Improvements:

• Client & Redirect URI Support:

  • Inji Verify now includes extra fields (client_id & redirect_uri) to handle OpenID4VP requests, redirecting users for authorization through Inji Web.

• VC Validation Improvements:

  • Enhanced validation logic for Verifiable Credentials (VCs) in the VP token format, ensuring that credentials are properly authenticated and validated before presenting results to users.

Repositories: Released/Dependent

Compatible modules:

The following table outlines the tested and certified compatibility of Inji Verify 0.10.0 with other modules.

Known Issues

Below is the list of known issues. To read in detail and view all the issues related to Inji Verify please click here.

Bug Fixes

Below is the list of fixes as part of the 0.10.0 release:

Documentation

• Feature Documentation

• User guide

• QA Report

Testing Scope

The scope of testing is to verify fitment to the specification from the perspective of

● Functionality

● Deploy ability

● Configurability

● Customizability

Verification is performed not only from the end user perspective but also from the System Integrator (SI) point of view. Hence, the Configurability and Extensibility of the software is also assessed. This ensures the readiness of software for use in multiple countries. MOSIP is an “API First” product platform.

The testing scope has been focused on the following features:

● Inji Verify Home page

● Verify Scan Feature

● Verify Upload Feature

Below are the combinations that QA verified and Certified INJI Verify:

Upload feature Verification:

1. Windows using Edge, Firefox, and Chrome browsers.

2. Mac using Safari browser.

Scan functionality Verification:

1. MAC (Laptop) with a front camera of 2 megapixels and Safari browser.

2. Mobile phone Android with camera 16 megapixel using browsers Chrome.

3. iPhone with 24-megapixel camera using Safari browser.

Test Approach

Persona based approach has been adopted to perform the IV&V, by simulating test scenarios that resemble a real-time implementation.

A Persona is a fictional character/user profile created to represent a user type that might use a product/or service similarly. Persona based testing is a software testing technique that puts software testers in the customer's shoes, assesses their needs from the software, and thereby determines use cases/scenarios that the customers will execute. The persona's needs may be addressed through any of the following.

● Functionality

● deploy ability

● Configurability

● Customizability

The verification methods may differ based on how the need was addressed.

Verified configuration

Verification is performed on various configurations as mentioned below.

● Default configuration - with 1 Language.

1. English

Feature Health

Test execution statistics

Functional test results

Below are the test metrics by performing functional testing. The process followed was black box testing which based its test cases on the specifications of the software component under test. The functional test was performed in combination with individual module testing as well as integration testing. Test data were prepared in line with the user stories. Expected results were monitored by examining the user interface. The coverage includes GUI testing, System testing, End-To-End flows across multiple configurations. The testing cycle included the simulation of multiple identity schema and respective UI schema configurations.

Test Rate: 93%, With Pass Rate: 83%

Here is the detailed breakdown of metrics for each module:

Test results for Upload and Scan

Windows

MAC

iPhone

Android

Detailed Test metrics

Below are the detailed test metrics by performing manual/automation testing. The project metrics are derived from Defect density, Test coverage, Test execution coverage, test tracking, and efficiency.

The various metrics that assist in test tracking and efficiency are as follows:

● Passed Test Cases Coverage: It measures the percentage of passed test cases. (Number of passed tests / Total number of tests executed) x 100.

● Failed Test Case Coverage: It measures the percentage of all the failed test cases. (Number of failed tests / Total number of test cases executed) x 100.

Version: 0.10.0

• Name: Inji Verify v0.10.0 (Developer Release)

• Date: 10th Oct, 2024

Version: 0.9.0

• Name: Inji Verify 0.9.0

• Date: 5th July, 2024

Version: 0.8.1

• Name: Inji Verify 0.8.1 (Patch)

• Date: 22nd May, 2024

Version: 0.8.0

• Name: Inji Verify 0.8.0

• Date: 8th May, 2024

Testing Scope

The scope of testing is to verify fitment to the specification from the perspective of

• Functionality

• Deployability

• Configurability

• Customizability

Verification is performed not only from the end user perspective but also from the System Integrator (SI) point of view. Hence Configurability and Extensibility of the software is also assessed. This ensures readiness of software for use in multiple countries. Since MOSIP is an “API First” product platform.

Testing scope has been focused around the below features:

• Inji Verify Home page

• Verify Scan Feature

• Verify Upload Feature

• OVP Flow

Below are the combinations that QA verified and Certified INJI Verify:

Upload feature Verification:

1. Windows using Edge, Firefox and Chrome browsers.

2. Android using Edge, Firefox and Chrome browsers.

3. MAC using Safari Edge, Firefox and Chrome browsers. .

Scan functionality Verification:

1. MAC (Laptop) with a front camera of 2 megapixel using Chrome, edge, Firefox and Safari browsers.

2. Windows laptop with a front camera of 2 megapixel using Chrome, edge, and Firefox browsers.

3. Mobile phone Android with back camera 16 megapixel using browsers Chrome, Edge and Firefox browsers.

4. Mobile phone Android and Android Tablet with back camera 8 megapixel using browsers Chrome, Edge and Firefox browsers.

5. iPhone and iPad with 12 megapixel back camera Chrome, edge, Firefox and Safari browsers.

6. Verified in low light to scan the QR code

7. Verified scan with blur, cracked, low quality QR codes was verified

Testing results:

Below are the results for Upload and Scan functionality with Windows, Android phone, MAC, Android Tablet, iPad and iPhone with different browsers:

Note: The scan feature is not working with the QR code generated from INJI Mobile, but the QR code that is generated with INJI Web is working fine.

Test Approach

Persona based approach has been adopted to perform the IV&V, by simulating test scenarios that resemble a real-time implementation.

A Persona is a fictional character/user profile created to represent a user type that might use a product/or a service in a similar way. Persona based testing is a software testing technique that puts software testers in the customer's shoes, assesses their needs from the software and thereby determines use cases/scenarios that the customers will execute. The persona needs may be addressed through any of the following.

• Functionality

• Deployability

• Configurability

• Customizability

The verification methods may differ based on how the need was addressed.

Verified configuration

Verification is performed on various configurations as mentioned below

• Default configuration - with 1 Lang

  • English

Feature Health

Test execution statistics

Functional test results

Below are the test metrics by performing functional testing. The process followed was black box testing which based its test cases on the specifications of the software component under test. Functional test was performed in combination of individual module testing as well as integration testing. Test data were prepared in line with the user stories. Expected results were monitored by examining the user interface. The coverage includes GUI testing, System testing, End-To-End flows across multiple configurations. The testing cycle included simulation of multiple identity schema and respective UI schema configurations.

UI Automation results

Below section provides details on UI Automation by executing MOSIP functional automation Framework.

Functional and test rig code base branch which is used for the above metrics is:

Hash Tag:

SHA:sha256:5e1c2741b64cc729a29a6ac767d48eeef9a9e0a1942028f9d16a1e80c25c6719

Detailed Test metrics

Below are the detailed test metrics by performing manual/automation testing. The project metrics are derived from Defect density, Test coverage, Test execution coverage, test tracking and efficiency.

The various metrics that assist in test tracking and efficiency are as follows:

• Passed Test Cases Coverage: It measures the percentage of passed test cases. (Number of passed tests / Total number of tests executed) x 100

• Failed Test Case Coverage: It measures the percentage of all the failed test cases. (Number of failed tests / Total number of test cases executed) x 100

Git hub link for the xls file:

<TBD>

Release Name: Inji Verify 0.9.0

Support: Developer Release

Release Date: 5th July 2024

Overview

Release 0.9.0 of Inji Verify enhances usability with a mobile-responsive portal, adds support for CBOR QR code decoding, and includes critical bug fixes. It introduces UI improvements using Tailwind CSS, enables PDF scanning with QR codes, and enhances credential display, including expired credentials. These updates aim to improve overall user experience and system functionality.

New Features:

1. UI Enhancements

• The user interface of Inji Verify has been optimized for mobile devices, offering responsive views that adapt seamlessly to different screen sizes. Users can conveniently access and utilize the scan and upload feature across devices.

• Inji Verify has undergone user interface and user experience enhancements based on GenderMag principles, ensuring improved accessibility and usability.

2. CBOR QR Code Support

• Support for CBOR-encoded QR codes has been added, expanding compatibility and enabling broader usage scenarios. Inji Verify can now decode the CBOR QR code using the pixel pass library.

3. Tech Upgrades

• Inji Verify has transitioned from MaterialUI to the Tailwind CSS library, offering enhanced flexibility and customization options.

4. Critical Bug Fixes

• Several critical bugs related to the scan and upload functionalities have been identified and fixed, ensuring smoother user experiences.

5. Support for PDFs Containing QR Codes

• Inji Verify now supports various formats, including PDFs that contain QR codes, broadening the range of documents that can be scanned and verified.

6. Credential Display Enhancements

• Credential details retrieved from the issuer's well-known configuration include display properties, ensuring a consistent and accurate representation of credential information.

• Users can now view expired credentials within the Inji Verify portal.

7. Browser Support

• Chrome, Edge, Safari, and Firefox: Full support for both scan and upload features, ensuring a seamless user experience across these popular browsers.

Assumptions or Limitations:

• Verification Method: We are assuming the verification method currently only works with DID (Decentralized Identifier). However, it can also be a direct URL key reference. This distinction is crucial for correct implementation and usage. You can look at the specific code handling this verification method here.

This release represents a significant step forward in improving functionality, usability, and compatibility within Inji Verify.

Repository Released

Known Issues

Below is the list of known issues. To read in detail and view all the topics related to Inji Verify please click here.

Bug Fixes

Below is the list of fixes as part of the 0.9.0 release:

Documentation

• Feature documentation

• User guide

• QA Report

Release Name: Inji Verify 0.8.0

Support: Developer Release

Release Date: 8th May, 2024

Overview

We are excited to announce the release of Inji Verify version 0.8.0! This release introduces several new features like scanning QR code, uploading QR code, and error handling aimed at improving the user experience and functionality of the verification portal. Below are the key highlights of this release:

New Features:

1. QR Code Scanning: Users can now scan QR codes directly from their device cameras using the built-in scanning feature. This allows for quick and seamless verification of Verifiable Credentials without the need for manual data entry.

2. QR Code Upload: In addition to QR code scanning, users have the option to upload QR code files from their devices for verification. This provides flexibility for users who may have QR codes saved as digital files.

3. Error Handling: Error messages and prompts have been added to provide clearer guidance to users in case of issues such as unsupported QR code formats, unreadable QR codes, or scan session timeouts.

Scan Feature QR Code Compatibility:

• QR code versions supported for the scan feature range from v22 and below.

Camera Resolution Requirement:

• The device's front or web camera resolution must exceed 8 megapixels.

• Cameras should be used in well-lit environments without filters, ensuring proper alignment for optimal scanning.

Upload Feature QR Code Compatibility:

• QR code versions supported for the upload feature range from v32 and below.

Repositories: Released/Dependent

Known Issues

Documentation

• Feature Documentation

• User Guide

• QA Report

Testing Scope

The scope of testing is to verify fitment to the specification from the perspective of the following functions:

● Functionality

● Deployability

● Configurability

● Customizability

Verification is performed not only from the end user perspective but also from the System Integrator (SI) point of view. Hence Configurability and Extensibility of the software is also assessed. This ensures readiness of software for use in multiple countries. Since MOSIP is an “API First” product platform.

Testing scope has been focused around the below features:

● Inji Verify Home page

● Verify Scan Feature

● Verify Upload Feature

Below are the combinations that QA verified and Certified Inji Verify:

Upload feature Verification:

1. Windows using Edge, Firefox and Chrome browsers.

2. MAC using Safari browser.

Scan functionality Verification:

1. MAC (Laptop) with a front camera of 2 megapixel and Safari browser.

2. Mobile phone Android with front camera 16 megapixel using browsers Chrome.

3. Mobile phone Android with front camera 8 megapixel using browsers Chrome.

4. iPhone with 12 megapixel front camera using Safari browser.

Test Approach

Persona based approach has been adopted to perform the IV&V, by simulating test scenarios that resemble a real-time implementation.

A Persona is a fictional character/user profile created to represent a user type that might use a product/or a service in a similar way. Persona based testing is a software testing technique that puts software testers in the customer's shoes, assesses their needs from the software and thereby determines use cases/scenarios that the customers will execute. The persona needs may be addressed through any of the following functions.

● Functionality

● Deployability

● Configurability

● Customizability

The verification methods may differ based on how the need was addressed.

Verified configuration

Verification is performed on various configurations as mentioned below

● Default configuration - with 1 language which is English.

Feature Health

Test execution statistics

Functional test results

Below are the test metrics by performing functional testing. The process followed was black box testing which based its test cases on the specifications of the software component under test. The functional test was performed in combination with individual module testing as well as integration testing. Test data were prepared in line with the user stories. Expected results were monitored by examining the user interface. The coverage includes GUI testing, System testing, End-To-End flows across multiple configurations. The testing cycle included the simulation of multiple identity schema and respective UI schema configurations.

Here is the detailed breakdown of metrics for each module:

Detailed Test metrics

Below are the detailed test metrics by performing manual/automation testing. The project metrics are derived from Defect density, Test coverage, Test execution coverage, test tracking, and efficiency.

The various metrics that assist in test tracking and efficiency are as follows:

● Passed Test Cases Coverage: It measures the percentage of passed test cases. (Number of passed tests / Total number of tests executed) x 100.

● Failed Test Case Coverage: It measures the percentage of all the failed test cases. (Number of failed tests / Total number of test cases executed) x 100.

Inji-Verify 0.8.0 - Verification - Report

Release Name: Inji Verify 0.8.1 (Patch)

Support: Developer Release

Release Date: 22nd May 2024

Overview

Inji Verify 0.8.1 addresses critical installation issues by fine-tuning the installation script with minor corrections. Additionally, the update to the Helm chart name helm -n $NS install inji-verify mosip/injiverify in the install.sh script ensures seamless deployment.

Repositories: Released/Dependent

Documentation

• Feature documentation

• User guide