🤖 Day 8: Craft a detailed prompt to support test activities

[grcyxie (Grace Icay)]

I asked ChatGPT to write test scenarios for Signing up for MoT in BDD and it gave me the following response:

1. **Scenario: Valid Registration**
   - Given I am on the registration page
   - When I input valid email, password, and other required details
   - Then I should be successfully registered
   - And I should be redirected to the dashboard or a confirmation page
   - And a confirmation email should be sent to the provided email address

2. **Scenario: Invalid Email Format**
   - Given I am on the registration page
   - When I input an invalid email format
   - Then I should see an error message indicating an invalid email format
   - And registration should not proceed until a valid email format is provided

3. **Scenario: Weak Password**
   - Given I am on the registration page
   - When I input a password that does not meet the platform's strength requirements
   - Then I should see a message indicating a weak password
   - And registration should not proceed until a strong password is provided

4. **Scenario: Existing Email Address**
   - Given I am on the registration page
   - When I attempt to register with an email address that is already in use
   - Then I should see a message indicating that the email address is already in use
   - And I should be prompted to log in or use a different email address

5. **Scenario: Empty Fields**
   - Given I am on the registration page
   - When I submit the registration form with empty required fields
   - Then I should be prompted to fill in all the required fields
   - And registration should not proceed until all required fields are filled

6. **Scenario: Confirmation Email**
   - Given I have successfully registered
   - When I check the inbox of the registered email address
   - Then I should find a confirmation email containing a verification link
   - And clicking the verification link should successfully verify my account and redirect me to the platform

7. **Scenario: User Agreement Acceptance**
   - Given I am on the registration page
   - When I try to register without accepting the terms and conditions
   - Then I should be prompted to agree to the terms and conditions before proceeding with registration
   - And registration should not proceed until I accept the terms

8. **Scenario: Performance Test**
   - Given multiple users are registering concurrently
   - When we simulate concurrent user registrations
   - Then the platform's performance should remain responsive
   - And registration time should be within acceptable limits even during peak periods

9. **Scenario: Security Measures**
   - Given I am on the registration page
   - When I interact with the registration fields
   - Then the registration process should be secured using HTTPS
   - And the platform should be protected against SQL injection and cross-site scripting (XSS) vulnerabilities
   - And CAPTCHA or other anti-bot measures should be employed to prevent automated registrations

10. **Scenario: Localization Test**
    - Given I am on the registration page
    - When I switch between different languages
    - Then error messages and instructions should be displayed correctly in the selected language
    - And registration functionality should work seamlessly with different character sets and languages

As for the ELI5 scenario, I asked it to explain the sign up process to me:

Sure, I'd be happy to explain the sign-up process to you as if you were five years old.

Imagine you're going to join a really fun club, like a secret clubhouse for learning cool things about testing. To join, you need to tell the club your name and create a secret password that only you know. They also need your email so they can send you special messages.

First, you go to the club's special website. On the website, you'll see a big button that says "Join" or "Sign Up." You click on that button, and it takes you to a special page where you can tell the club all about yourself.

There are little boxes where you put in your name, your email (that's like your special mailbox on the internet), and your super-secret password. Make sure your password is really strong, like a fortress, so nobody else can guess it!

Once you've filled in all the boxes, you click on a button that says "Join" or "Sign Up" again. When you do that, the club sends you a special email to make sure you're really you. It's like a secret handshake to make sure you're a real member!

You check your email and see a message from the club. Inside the email, there's a special link. When you click on that link, it tells the club that you got the email and you're ready to join. Then, voila! You're officially a member of the club!

Now, you can go to the club's website anytime you want, log in with your special password, and explore all the fun things they have to offer. And that's how you sign up for the club's website! Easy, right?

[poojitha-chandra (Poojitha Manam)]

@lisacrispin

I thought it would be fun to compare what Gemini says vs what ChatGPT told Poojitha. So I asked her first question to Gemini. Here’s what it responded. I think ChatGPT gave a much more comprehensive answer, but I’m going to ask Gemini more questions and see if it gets into more details.

It’s fascinating to see how different LLMs approach the user’s input. Obviously exploring further conversation with the LLM like Lisa did provided additional insights into the accessibility testing. It’s great to see a deeper dive into the nuances of automated/manual testing for accessibility.

[vishnuar]

Hi,

This is an interesting topic. Initially i choose the beginner level and later went to intermediate level. I asked questions on Health care domain and satisfied with the expected output

ChatGPT

[joyz (Joyz Ng)]

Thank you for your sharing, that is very useful. Instead of crafting a new prompt, I would like to edit on your example to improve the formatting of test cases generated.

I am using Google Gemini instead of ChatGPT, as it can export results to Google spreadsheet directly, but tested on both will give similar format.

From the custom prompt, I added 1 line to the instructions:

Each section shows a table format with "ID" (with 2 capital letter and 2 significant digit), "Scenario", "Steps" and "Expected Behaviour" columns.

It can then response in a table format, and can click the Export to Sheets for further manual editing.

[sarahdeery]

Apologies, @mrukavina, it’s live now, It’s my error; I scheduled it to the wrong place. you can now access it here and review all the challenges here

Thank you for highlighting the problem, and I hope you find it a valuable addition to the Day 8 challenge.

[indres (Indre Stasiuniene)]

Hi, everyone,

I choose challenge for beginners. At the firs I ask ChatGPT to generate test scenarios for signing up to Ministry of Testing website. There is one example for succesful sign up scenarios:

Title: Successful Sign-Up

• Preconditions: User accesses the Ministry of Testing website.
• Inputs/Actions:
  1. User navigates to the sign-up page.
  2. User enters a valid email address, username, and password.
  3. User agrees to the terms and conditions.
  4. User clicks the “Sign Up” button.
• Expected Results: User receives a confirmation message and is redirected to the Ministry of Testing dashboard.

After that I asked to generate story-like test scenarios. There is example with the same scenarios:

As a beginner software tester, I want to sign up to the Ministry of Testing website to access learning resources and join the tester community.

Positive Scenario: Successful Sign-Up

• Scenario:
  • Given that I am a beginner software tester
  • When I visit the Ministry of Testing website
  • And I navigate to the sign-up page
  • Then I enter my valid email address, a unique username, and a strong password
  • And I agree to the terms and conditions
  • And I click the “Sign Up” button
• Expected Result:
  • I receive a confirmation message welcoming me to the Ministry of Testing platform
  • I am redirected to my dashboard where I can access learning resources and engage with the community.

Next prompt was to generate format specific scenarios using Behavior-driven development syntax. Please find given example:

Succesful sign up with BDD syntax:

My question to ChatGPT was to explain, what BDD stand for. There is generated answer:

Behavior-Driven Development (BDD) is an agile software development methodology that emphasizes collaboration between developers, testers, and business stakeholders to ensure that software development focuses on delivering value to the end-users. BDD uses a common language understood by all parties involved, facilitating effective communication and collaboration throughout the development process.

BDD syntax typically involves writing scenarios in a structured format using Given-When-Then (GWT) clauses. Each scenario describes a specific behavior or feature of the software from the perspective of a user or stakeholder. The GWT structure helps to clearly articulate the context, actions, and expected outcomes of the scenario.

Here’s a breakdown of the Given-When-Then structure:

• Given: This clause sets up the preconditions or initial context for the scenario. It describes the state of the system before the action being tested occurs. Given clauses are used to establish the starting point for the scenario.
• When: This clause describes the action or event that is being performed by the user or system. It represents the trigger that initiates a change in the system’s state. When clauses specify the behavior or action being tested.
• Then: This clause specifies the expected outcome or result of the action performed in the When clause. It describes the expected behavior of the system in response to the action taken. Then clauses define the verification criteria for the scenario.

Here’s an example of a simple BDD scenario for logging into a website:

gherkinCopy code

Feature: User Login
  As a user
  I want to log into the website
  So that I can access my account

  Scenario: Successful Login
    Given I am on the login page
    When I enter valid credentials
    And I click the "Login" button
    Then I should be redirected to the dashboard
    And I should see a welcome message

In this scenario:

• The Given clause establishes the initial context (being on the login page).
• The When clause describes the action performed (entering valid credentials and clicking the “Login” button).
• The Then clause specifies the expected outcomes (being redirected to the dashboard and seeing a welcome message).

BDD scenarios are written in a human-readable format, making them accessible to all stakeholders involved in the software development process. They serve as executable specifications that guide the development and testing of software features, ensuring alignment between business requirements and implementation.

For more information about BDD ChatGPT recommend to me look to this books:

• “Specification by Example” by Gojko Adzic: This book provides practical guidance on using examples to define software requirements and drive development with BDD.
• “BDD in Action: Behavior-Driven Development for the Whole Software Lifecycle” by John Ferguson Smart: This book offers a comprehensive introduction to BDD concepts, practices, and tools, along with real-world examples.

From my point of view, ChatGPT generate quit good test scenarios and take clear explanation about BDD, but I had to correct me prompt about story like scenarios in order to get it in a more neutral tone compared to those that were generated at the firs.

[brenoborgesf (Breno Borges França)]

I mentioned I wanted test cases for the Sign-in feature and I wrote the success test case as an example using BDD. For the negative test cases, I started with the first line using “Scenario Outline” to indicate that I wanted a table of values. Eventually, I managed to achieve:

Feature: Login

Scenario: TC01 - Login Success
Given the user is on the login page
When they enter a valid email
And they enter a valid password
And they click on the Login button
Then the system displays a success message
And the system redirects the user inside the system

Scenario Outline: TC02 - Login Failing
Given the user is on the login page
When they enter
And they enter
And they click on the Login button
Then the system displays an error message
And does not redirect the user inside the system

Examples:
  | Email               | Password      |
  | "invalid@email"     | "password"    |
  | "valid@email.com"   | "short"       |
  | ""                  | "password"    |
  | "valid@email.com"   | ""            |
  | "existing@email.com"| "wrongpass"   |

I explained that Logout can only be done by clicking the Logout button and I received:

Feature: Logout

Scenario: User Logout
Given the user is logged in and on the dashboard page
When they click on the Logout button
Then the system logs out the user
And redirects the user to the login page

Then, I attempted a more complex feature, the signup process which can be done by receiving an email or an invitation link, and the system may or may not require a password and MFA (Multi-Factor Authentication). I had to divide the scenarios into two “Scenario Outline” sections, one with MFA Off and the other with MFA On, and there are two types of MFA. Eventually, I achieved:

Feature: Sign Up

Background:
Given the organization doesn’t require MFA for guests

Scenario Outline: User Sign Up with Invitation
Given the user receives an invitation via <via_method>
And the organization owner <requires_password> access to the room
When the user follows the invitation link or opens the email
And completes the sign-up process with valid credentials with <requires_password>
Then the user gains access to the room
And is redirected to the room dashboard

Examples:
  | via_method   | requires_password |
  | Email        | Yes               |
  | Email        | No                |
  | Invitation   | Yes               |
  | Invitation   | No                |

Background:
Given the organization requires MFA for guests

Scenario Outline: User Sign Up with Invitation with MFA
Given the user receives an invitation via <via_method>
And the organization owner requires MFA for guests
And the organization owner <requires_password> access to the room
When the user follows the invitation link or opens the email
And completes the sign-up process with valid credentials with <requires_password>
And defines the <mfa_type> MFA for their account
Then the user gains access to the room
And is redirected to the room dashboard

Examples:
  | via_method   | requires_password | mfa_type          |
  | Email        | Yes               | SMS               |
  | Email        | Yes               | Authenticator App |
  | Email        | No                | SMS               |
  | Email        | No                | Authenticator App |
  | Invitation   | Yes               | SMS               |
  | Invitation   | Yes               | Authenticator App |
  | Invitation   | No                | SMS               |
  | Invitation   | No                | Authenticator App |

In my opinion, this exercise is straightforward for simple features. You provide a feature and get all the test cases you need. However, as the feature becomes more complex, you need to think about how to divide the test cases and how to inform the AI to organize your test cases. Nonetheless, it’s a great tool for writing test cases.

[parwalrahul (Rahul Parwal)]

Hello, @simon_tomes and fellow participants,

It took me a lot of time to complete this task as I got busy refining and fine-tuning my prompts. However, the good part is that I was able to come up with a list of prompts to help me do better with the testing tasks shared in the exercise.

I have documented all those prompts here: AI Prompt Repository for Testers - Rahul’s Testing Titbits

Here are the results of these prompts on the Open AI Chat GPT 3.5 Application: ChatGPT

I also did a video to explain my process and how these things work for me here:

Prompts for Testing Activities and Tasks | Testing Tasks with LLM Prompts - Day 8 of AI in Testing

Looking forward to hearing your feedback on this one.

Thank you!
Rahul

[ayamfouad (Ayah Fouad)]

Interesting indeed.

Note: tried this with ChatGPT

Went ahead with Intermediate Level: How Do I Test This?

Me: described basic functionalities and risk factors for an AB testing tool and asked for chat to provide a test strategy based on this description as a seasoned software testing expert

Chat: ChatGPT: As a software testing professional, my aim is to ensure that the AB testing tool is thoroughly tested to deliver a high-quality and reliable product. To achieve this, I have devised a compreh - Poe

Me: Asked for it to be put in a strategy template with Scope, Test Approach, Testing Types, Testing Tools, Hardware - Software Configuration

Chat: ChatGPT: Certainly! Here's an adjusted test strategy template for the AB testing tool: **1. Scope:** The test scope for the AB testing tool includes all its features, including creating AB, split, mu - Poe

Then I told chat that automation is out of scope at this moment, strategy was adjusted to remove automation and anything that was automation-related. After this, I asked chat to add a few points to strategy and combine points from last 2 strategies but I still didn’t get the previously removed parts back: please add objective, Test Environment, test data, Reporting and Mitigation, testing frequency to a combine of the last 2 stragies - Poe

[p.schrijver (Simon Schrijver)]

I selected the ‘Intermediate level’ challenge. I like the Password Validator example, so I want to investigate this further.

Question to ChatGPT:

You are an experienced tester. You are asked to generate a detailed test scenarios for both expected and edge cases for a Password Validator

Use the set of requirements enclosed by triple quotes:

“””

Password must meet all conditions as mentioned below in terms of bullet list

** Password contains at least 8 characters and at most 20 characters.*

** Password contains at least one digit.*

** Password contains at least one upper case alphabet.*

** Password contains at least one lower case alphabet.*

** Password contains at least one special character*

“”"

Answer from ChatGPT:

Here are detailed test scenarios for both expected and edge cases for the Password Validator based on the given requirements:

• Minimum Length Test Cases:
  • Input: “abcd1234!”
  • Expected Output: Pass (Minimum length, all conditions met)
  • Input: “aA1!”
  • Expected Output: Fail (Minimum length not met)
• Maximum Length Test Cases:
  • Input: “abcdefghijklmnopqrstuvwxyz1234567890!@#$%^&*”
  • Expected Output: Pass (Maximum length, all conditions met)
  • Input: “abcdefghijklmnopqrstuvwxyz1234567890!@#$%^&*1”
  • Expected Output: Fail (Maximum length exceeded)
• Digit Test Cases:
  • Input: “abcdEFGH!”
  • Expected Output: Fail (No digit)
  • Input: “abcdEFGH1!”
  • Expected Output: Pass (Digit included)
• Upper Case Alphabet Test Cases:
  • Input: “abcd1234!”
  • Expected Output: Fail (No upper case alphabet)
  • Input: “abcdEFGH1!”
  • Expected Output: Pass (Upper case alphabet included)
• Lower Case Alphabet Test Cases:
  • Input: “1234EFGH!”
  • Expected Output: Fail (No lower case alphabet)
  • Input: “abcdEFGH1!”
  • Expected Output: Pass (Lower case alphabet included)
• Special Character Test Cases:
  • Input: “abcdEFGH1234”
  • Expected Output: Fail (No special character)
  • Input: “abcdEFGH1234!”
  • Expected Output: Pass (Special character included)
• Combination Test Cases:
  • Input: “Abcd1234”
  • Expected Output: Fail (No special character)
  • Input: “Abcd1234!”
  • Expected Output: Pass (All conditions met)
• Edge Case Test Cases:
  • Input: “aA1!@#$%^&*”
  • Expected Output: Pass (Minimum length, all conditions met, including special characters)
  • Input: “abcdefghijklmnopqrstuvwxyz1234567890!@#$%^&*”
  • Expected Output: Pass (Maximum length, all conditions met, including special characters)
• Empty Password Test Case:
  • Input: “”
  • Expected Output: Fail (Empty password)
• Whitespace Test Cases:
  • Input: " "
  • Expected Output: Fail (Whitespace only)
  • Input: " aA1!bB2@"
  • Expected Output: Pass (Whitespace included, but other conditions met)

These scenarios cover a range of inputs including the expected behavior as well as edge cases for the password validator.

Question to ChatGPT:

Can you identify in the set of requirements that they are incomplete or ambiguous

Answer from ChatGPT:

Upon closer examination, I can identify a couple of potential ambiguities and incompleteness in the provided set of requirements for the password validator:

• Definition of “Special Character”:
  The requirement mentions that the password must contain at least one special character, but it doesn’t define what constitutes a “special character.” Different systems may define special characters differently (e.g., !@#$%^&*). Therefore, clarification on which characters are considered special would be beneficial for testers and users.
• No Mention of Whitespace Handling:
  The requirements do not specify whether leading or trailing whitespace should be considered part of the password or if passwords consisting entirely of whitespace should be allowed. It’s important to clarify if whitespace should be ignored or treated as part of the password.
• Clarification on Case Sensitivity:
  While the requirements state that the password must contain at least one upper case and one lower case alphabet, they do not mention whether the validation process is case-sensitive. It should be clarified whether “A” and “a” are considered distinct characters in the validation process.
• Minimum and Maximum Length Inclusivity:
  The requirements mention that the password must contain at least 8 characters and at most 20 characters. However, it’s not explicitly stated whether passwords of exactly 8 or 20 characters are acceptable. Clarity on inclusivity is essential for accurately defining the validation criteria.

Addressing these ambiguities and incompleteness in the requirements will help ensure that the password validator’s behavior is well-defined and consistent across different interpretations.

Question to ChatGPT:

This Password Validator is part of a login page of an application of a bank to transfer money. The Password Validator helps to provide strong passwords during the login process to keep unauthorized persons outside. Can you produce a test strategy or approach for the system

Answer from ChatGPT:

Certainly! Here’s a test strategy for the login page of the bank’s application, including the Password Validator component:

• Understanding Requirements and Risks:
  • Review the requirements for the login page and the Password Validator component.
  • Identify potential risks associated with unauthorized access, weak passwords, and security vulnerabilities.
• Scope Definition:
  • Define the scope of testing, including the login page, password validation functionality, and any related security features.
  • Identify the browsers, devices, and platforms to be tested, considering the bank’s target audience.
• Test Environment Setup:
  • Set up the test environment with the necessary hardware, software, and network configurations.
  • Ensure that the environment mirrors the production environment as closely as possible, including security measures.
• Test Case Design:
  • Develop test cases covering functional and non-functional aspects of the login page and Password Validator.
  • Include test cases for positive scenarios (valid inputs), negative scenarios (invalid inputs), edge cases, and security-related tests.
  • Test cases should cover aspects such as password length, character types, error messages, session management, and security protocols (e.g., HTTPS).
• Test Execution:
  • Execute test cases systematically, following the test plan and test scripts.
  • Perform manual and automated testing as appropriate.
  • Monitor system behavior during testing, including response times, error messages, and security indicators.
• Security Testing:
  • Conduct security testing to identify vulnerabilities such as SQL injection, cross-site scripting (XSS), and authentication bypass.
  • Perform penetration testing to simulate potential attacks and assess the system’s resilience to security threats.
  • Verify compliance with industry standards and regulations (e.g., PCI DSS, GDPR) regarding password handling and data protection.
• Performance Testing:
  • Evaluate the performance of the login page under normal and peak load conditions.
  • Measure response times, throughput, and resource utilization to ensure scalability and reliability.
  • Identify and address any performance bottlenecks or stability issues.
• Accessibility Testing:
  • Verify that the login page and Password Validator are accessible to users with disabilities, including those using assistive technologies.
  • Ensure compliance with accessibility standards such as WCAG (Web Content Accessibility Guidelines).
• Documentation and Reporting:
  • Document test results, including findings, observations, and recommendations.
  • Prepare test reports summarizing the test process, outcomes, and any identified issues.
  • Provide actionable feedback to stakeholders, including developers, designers, and project managers.
• Regression Testing:
  • Perform regression testing whenever changes are made to the login page or Password Validator functionality.
  • Validate that existing features remain functional and that new changes do not introduce regressions.
• Post-Release Monitoring:
  • Monitor the production environment after deployment to detect any issues or anomalies.
  • Gather feedback from users and stakeholders to identify areas for improvement and future enhancements.
• Continuous Improvement:
  • Incorporate lessons learned from testing into future iterations of the application.
  • Continuously evaluate and enhance the testing process to adapt to evolving requirements and technologies.

By following this test strategy, the bank can ensure that its login page and Password Validator function reliably, securely, and efficiently, providing a seamless user experience while safeguarding sensitive financial information.

Question to ChatGPT:

Can you explain more on the Security testing part?

Answer from ChatGPT:

Certainly! Security testing is a critical aspect of ensuring the robustness and integrity of a banking application’s login page and password validation functionality. Here’s a more detailed explanation of the security testing process:

• Authentication Mechanism Testing:
  • Verify that the authentication mechanism employed by the login page is secure and resistant to common attacks such as brute force attacks, dictionary attacks, and credential stuffing.
  • Test for proper handling of authentication failures, including lockout mechanisms after multiple failed login attempts.
• Session Management Testing:
  • Assess the effectiveness of session management mechanisms to prevent session hijacking and session fixation attacks.
  • Verify that session identifiers are securely generated, transmitted over secure channels (e.g., HTTPS), and invalidated upon logout or session timeout.
• Input Validation Testing:
  • Validate user inputs to prevent injection attacks such as SQL injection, LDAP injection, and command injection.
  • Test for proper sanitization and validation of user-supplied data to ensure that malicious inputs cannot compromise the integrity of the system.
• Cross-Site Scripting (XSS) Testing:
  • Evaluate the login page and associated components for vulnerabilities that could enable XSS attacks.
  • Test for proper encoding and escaping of user-generated content to mitigate the risk of XSS vulnerabilities.
• Cross-Site Request Forgery (CSRF) Testing:
  • Verify that the application implements adequate CSRF protection mechanisms to prevent attackers from executing unauthorized actions on behalf of authenticated users.
  • Test for the presence of anti-CSRF tokens and their effectiveness in mitigating CSRF attacks.
• Security Headers Testing:
  • Assess the presence and effectiveness of security headers such as Content Security Policy (CSP), Strict-Transport-Security (HSTS), and X-Content-Type-Options.
  • Ensure that security headers are properly configured to mitigate common web security vulnerabilities.
• Sensitive Data Handling Testing:
  • Evaluate how the application handles sensitive data such as passwords, authentication tokens, and personal information.
  • Test for encryption of sensitive data both in transit (e.g., using HTTPS) and at rest (e.g., storing passwords securely hashed).
• Access Control Testing:
  • Verify that access control mechanisms are implemented correctly to enforce proper authorization and restrict access to sensitive functionalities and resources.
  • Test for privilege escalation vulnerabilities and unauthorized access to restricted areas of the application.
• Security Compliance Testing:
  • Validate compliance with industry standards and regulations relevant to the banking sector, such as the Payment Card Industry Data Security Standard (PCI DSS), General Data Protection Regulation (GDPR), and relevant national regulations.
  • Ensure that the application adheres to best practices for secure development and deployment.
• Penetration Testing:
  • Conduct penetration testing (pen testing) to simulate real-world attacks and identify potential security weaknesses.
  • Utilize ethical hacking techniques to probe the application’s defenses and identify exploitable vulnerabilities.
  • Penetration testing helps uncover hidden vulnerabilities that may not be apparent through traditional testing methods.

By conducting thorough security testing encompassing these aspects, the bank can identify and mitigate potential security risks, safeguarding sensitive financial data and ensuring the confidentiality, integrity, and availability of its banking application.

Question to ChatGPT:

About the information of the Security testing part, how do I test this. Can you provide some examples

Answer from ChatGPT:

Certainly! Let’s delve into some examples of security testing techniques for the login page and password validation functionality of a banking application:

• Authentication Mechanism Testing:
  • Example Test Case: Attempt to perform brute force attacks by repeatedly submitting incorrect login credentials.
  • Expected Outcome: The system should lock the user account or implement a delay mechanism after a certain number of failed login attempts, mitigating the effectiveness of brute force attacks.
• Session Management Testing:
  • Example Test Case: Log in to the application with valid credentials and capture the session identifier.
  • Expected Outcome: The session identifier should be securely transmitted over HTTPS, and it should change upon subsequent logins or expire after a specified period of inactivity.
• Input Validation Testing:
  • Example Test Case: Attempt to inject SQL code into the username or password fields.
  • Expected Outcome: The application should sanitize and validate user inputs to prevent SQL injection attacks, and it should reject malicious inputs without executing the injected SQL code.
• Cross-Site Scripting (XSS) Testing:
  • Example Test Case: Submit a login attempt with a malicious script embedded in the username or password fields.
  • Expected Outcome: The application should properly encode and escape user-generated content to prevent the execution of XSS attacks, ensuring that the script is treated as plaintext rather than executable code.
• Cross-Site Request Forgery (CSRF) Testing:
  • Example Test Case: Craft a malicious web page containing a hidden form that submits requests to the bank’s application on behalf of a logged-in user.
  • Expected Outcome: The application should require anti-CSRF tokens to be included in form submissions, and it should reject requests lacking valid tokens to prevent CSRF attacks.
• Security Headers Testing:
  • Example Test Case: Examine the HTTP response headers returned by the application for the presence and configuration of security headers such as Content Security Policy (CSP) and Strict-Transport-Security (HSTS).
  • Expected Outcome: Security headers should be correctly configured to enforce security policies and protect against common web vulnerabilities.
• Sensitive Data Handling Testing:
  • Example Test Case: Submit a login attempt and monitor network traffic to verify that sensitive data such as passwords are transmitted securely over HTTPS.
  • Expected Outcome: Sensitive data should be encrypted in transit to prevent interception by malicious actors, ensuring confidentiality and integrity.
• Access Control Testing:
  • Example Test Case: Attempt to access restricted areas of the application without proper authorization by manipulating URLs or HTTP requests.
  • Expected Outcome: The application should enforce access controls to prevent unauthorized users from accessing sensitive functionalities or data, returning appropriate error messages or redirecting to the login page.
• Security Compliance Testing:
  • Example Test Case: Review the application’s handling of user data to ensure compliance with relevant regulations such as PCI DSS and GDPR.
  • Expected Outcome: The application should adhere to legal and regulatory requirements regarding data protection, privacy, and security, including secure storage and processing of personal and financial information.
• Penetration Testing:
  • Example Test Case: Employ penetration testing tools and techniques to identify vulnerabilities such as unpatched software, misconfigurations, or insecure APIs.
  • Expected Outcome: Penetration testing should uncover potential security weaknesses that could be exploited by malicious attackers, allowing the organization to address and remediate them before they can be exploited.

These examples illustrate various security testing techniques that can be applied to assess the robustness and integrity of the login page and password validation functionality of a banking application. By conducting comprehensive security testing, organizations can proactively identify and mitigate potential security risks, safeguarding sensitive financial data and ensuring the overall security posture of their applications.

Question to ChatGPT:

Can you summarize the test strategy or approach based on the conversation we just had.

Answer from ChatGPT:

Certainly! Based on our discussion, here’s a summarized test strategy or approach for the login page and password validation functionality of a banking application:

• Scope Definition:
  • Define the scope of testing, including the login page, password validation functionality, and related security features.
  • Identify the browsers, devices, and platforms to be tested to ensure comprehensive coverage.
• Understanding Requirements and Risks:
  • Review requirements for the login page and password validation, identifying potential security risks and vulnerabilities.
• Test Environment Setup:
  • Set up a test environment mirroring the production environment, ensuring it includes the necessary hardware, software, and network configurations.
• Test Case Design:
  • Develop test cases covering functional aspects (positive and negative scenarios), security testing techniques (such as authentication, session management, input validation), accessibility, performance, and regression testing.
• Test Execution:
  • Execute test cases systematically, combining manual and automated testing as appropriate.
  • Monitor system behavior during testing, including response times, error messages, and security indicators.
• Security Testing:
  • Conduct security testing to identify vulnerabilities such as authentication flaws, input validation issues, XSS, CSRF, sensitive data handling, and access control weaknesses.
  • Utilize techniques such as penetration testing to simulate real-world attacks and uncover hidden vulnerabilities.
• Documentation and Reporting:
  • Document test results, including findings, observations, and recommendations.
  • Prepare test reports summarizing the test process, outcomes, and any identified security issues.
  • Provide actionable feedback to stakeholders for addressing vulnerabilities and enhancing security measures.
• Continuous Improvement:
  • Incorporate lessons learned from testing into future iterations of the application.
  • Continuously evaluate and enhance the testing process to adapt to evolving requirements and security threats.

By following this comprehensive test strategy, the organization can ensure the reliability, security, and integrity of the login page and password validation functionality, thereby safeguarding sensitive financial data and maintaining customer trust in the banking application.

[connmc (Conn McKay)]

For my scenarios i asked for:

As an Automation Engineer looking for machine learning tools for performance monitoring, here are ten powerful options:

1. Prometheus: Prometheus is an open-source monitoring and alerting toolkit designed for reliability and scalability. While not strictly a machine learning tool, it integrates well with various ML libraries for anomaly detection and predictive analytics.
2. Grafana: Grafana is a popular open-source analytics and monitoring solution. It offers advanced visualization capabilities and can be integrated with machine learning algorithms for anomaly detection and forecasting.
3. TensorFlow Extended (TFX): TFX is an end-to-end platform for deploying production-ready machine learning models. It includes components for data validation, transformation, training, evaluation, and serving, making it suitable for building performance monitoring systems.
4. Apache Kafka: Kafka is a distributed streaming platform that can be used for real-time data processing and monitoring. It integrates well with machine learning frameworks for building streaming analytics applications.
5. Elasticsearch: Elasticsearch is a distributed search and analytics engine. It can be combined with machine learning plugins such as X-Pack to perform anomaly detection and forecasting on large datasets.
6. Scikit-learn: Scikit-learn is a popular machine learning library in Python. It provides a wide range of algorithms for classification, regression, clustering, and dimensionality reduction, which can be applied to performance monitoring tasks.
7. PyTorch: PyTorch is another popular machine learning library in Python, particularly favored for deep learning tasks. It provides a dynamic computational graph and offers modules for building and training neural networks, which can be useful for advanced performance monitoring scenarios.
8. KubeFlow: KubeFlow is an open-source platform for deploying, monitoring, and managing machine learning models on Kubernetes. It includes components for training, serving, and monitoring models, making it suitable for production-grade performance monitoring systems.
9. Amazon CloudWatch: CloudWatch is a monitoring and observability service provided by AWS. It offers built-in features for collecting and visualizing metrics, as well as integrating with machine learning services such as Amazon SageMaker for advanced analytics.
10. Azure Monitor: Azure Monitor is Microsoft’s platform for monitoring and diagnosing applications and infrastructure in the Azure cloud. It provides features for collecting, analyzing, and acting on telemetry data, and it can be extended with machine learning capabilities for intelligent performance monitoring.

These tools cover a wide range of functionalities and can be combined and customized to meet specific performance monitoring requirements in automation engineering projects.

I then refined this to
As an Automation Engineer working with SQL Server databases, you can leverage Prometheus for performance monitoring in several ways:

1. Exporters: Prometheus works best when paired with exporters. There are various exporters available for SQL Server, such as the SQL Server Exporter, which exposes SQL Server metrics in a format Prometheus can scrape. These metrics can include database performance indicators like query execution times, transaction rates, buffer pool usage, and more.
2. Alerting: Prometheus allows you to define alerting rules based on the collected metrics. You can set up alerts to notify you when certain performance thresholds are exceeded, such as high CPU usage, low disk space, or slow query execution times. This proactive monitoring helps prevent potential issues before they impact system performance.
3. Visualization: Prometheus integrates with visualization tools like Grafana, which provides powerful visualization capabilities for monitoring SQL Server performance metrics. Grafana dashboards can display real-time and historical performance data in easy-to-understand graphs and charts, allowing you to quickly identify trends and anomalies.
4. Anomaly Detection: With Prometheus, you can apply machine learning techniques for anomaly detection on SQL Server metrics. By analyzing historical performance data, you can train models to detect abnormal behavior and trigger alerts when deviations occur. This helps you identify potential performance issues early and take corrective action.
5. Capacity Planning: By analyzing SQL Server metrics collected by Prometheus, you can gain insights into resource usage patterns over time. This information is invaluable for capacity planning, allowing you to anticipate future resource requirements and make informed decisions about scaling your infrastructure to meet growing demands.
6. Custom Metrics: Prometheus allows you to define custom metrics tailored to your specific monitoring needs. You can instrument your SQL Server applications to expose custom performance metrics, such as application-specific query response times or business transaction rates, and collect them alongside standard SQL Server metrics for comprehensive performance monitoring.
7. Integration with SQL Server Management Studio (SSMS): While not directly related to Prometheus, you can use SSMS to monitor SQL Server performance metrics in real-time. By combining SSMS with Prometheus, you can correlate SQL Server metrics collected by SSMS with other system-level metrics collected by Prometheus for holistic performance monitoring and troubleshooting.

Overall, Prometheus can significantly enhance your ability to monitor SQL Server performance by providing a scalable, flexible, and customizable monitoring solution with robust alerting, visualization, and anomaly detection capabilities.

Further refinement gave me:
As an automation engineer working with sql server databases tell me how i can integrate the Prometheus tool with sql server management studio

Integrating Prometheus, which is primarily used for monitoring and alerting, with SQL Server Management Studio (SSMS), a graphical tool for managing SQL Server databases, isn’t a typical integration scenario. Prometheus is more commonly used with time-series databases like Prometheus itself or databases that support Prometheus exporters.

However, if you want to monitor SQL Server instances using Prometheus, you can do so by using Prometheus exporters. Here’s a general guide on how you might set it up:

1. Choose a Prometheus Exporter for SQL Server: You’ll need an exporter that can collect metrics from SQL Server and expose them in a format that Prometheus can scrape. An example of such an exporter is the mssql_exporter.
2. Install and Configure the Exporter: Follow the installation instructions provided by the exporter’s documentation. Typically, this involves deploying the exporter on a server that has access to your SQL Server instances and configuring it to connect to them.
3. Expose Metrics: Configure the exporter to expose metrics in a format that Prometheus can scrape. This usually involves configuring the exporter to listen on a specific port and expose metrics in a format like Prometheus’ text-based exposition format.
4. Scrape Configuration in Prometheus: Configure Prometheus to scrape metrics from the exporter. This involves adding a scrape_config block to your Prometheus configuration file that specifies the endpoint where the exporter is exposing metrics.
5. Set up Alerting and Visualization: Once Prometheus is scraping metrics from the exporter, you can set up alerting rules and visualize the data using tools like Grafana.

Regarding SSMS, it doesn’t have direct integration capabilities with Prometheus. However, you can use SSMS to query your SQL Server databases to extract relevant metrics and use the exported data from the Prometheus exporter to monitor and analyze your SQL Server instances.

Remember to ensure that any monitoring or automation activities you perform comply with your organization’s policies and security guidelines.

[vjmobby (Vijay Kumar)]

I am using Bard AI. Bard is now Gemini. Here is my prompt - Python test script for promotional code feature.

Gemini Response:-

Python
# Import libraries (replace with your actual libraries)
import unittest

from your_application import apply_promo_code  # Replace with your function


class TestPromoCode(unittest.TestCase):

    def test_valid_code(self):
        # Arrange
        cart_total = 100
        promo_code = "HOLIDAY20"  # Replace with a valid promo code
        expected_total = 80  # Replace with expected discounted total

        # Act
        discounted_total = apply_promo_code(cart_total, promo_code)

        # Assert
        self.assertEqual(discounted_total, expected_total)

    def test_invalid_code(self):
        # Arrange
        cart_total = 100
        promo_code = "INVALIDCODE"
        expected_total = 100

        # Act
        discounted_total = apply_promo_code(cart_total, promo_code)

        # Assert
        self.assertEqual(discounted_total, expected_total)

    def test_expired_code(self):
        # Arrange (assuming you have a way to check expiration)
        cart_total = 100
        promo_code = "EXPIRED10"
        expected_total = 100

        # Act
        discounted_total = apply_promo_code(cart_total, promo_code)

        # Assert
        self.assertEqual(discounted_total, expected_total)

    def test_empty_code(self):
        # Arrange
        cart_total = 100
        promo_code = ""
        expected_total = 100

        # Act
        discounted_total = apply_promo_code(cart_total, promo_code)

        # Assert
        self.assertEqual(discounted_total, expected_total)


if __name__ == "__main__":
    unittest.main()

Explanation:

1. Imports: Replace your_application with the actual module or file containing your apply_promo_code function that handles applying the discount based on the promo code.
2. Test Cases:

• test_valid_code: This tests if a valid promo code applies the discount and reduces the total as expected.
• test_invalid_code: This tests if an invalid code doesn’t change the total.
• test_expired_code: This tests if an expired code doesn’t change the total (assuming you have a way to check expiration in your code).
• test_empty_code: This tests if an empty code doesn’t change the total.

3. Running the Tests: Save the script as a Python file (e.g., test_promo_code.py) and run python test_promo_code.py in your terminal. This will execute the test cases and show the results (passed or failed).

Note: This is a basic example. You can expand this script to include more test cases based on your specific promotional code functionality. Here are some additional features you might want to test:

• Minimum order value required for the promo code to be applied.
• Specific product category restrictions for the promo code.
• Maximum number of times a code can be used.

Remember to replace the placeholder values with your actual data and functions for the script to work effectively.

[simon_tomes]

@ayamfouad

Note: tried this with ChatGPT

Ah, I see you used Poe. Not tried that one before. Thanks for sharing. Very handy that you can just link share to a reply.

[ayamfouad (Ayah Fouad)]

It groups multiple tools together, so I find it easier to compare different responses but you only get a limited number of messages for each tool/day based on points system

[blanchec (Blanche Carstens)]

Prompt:
You are tasked with testing the sign-up functionality for an online platform similar to the Ministry of Testing (MoT). Create a set of test scenarios to ensure the sign-up process functions correctly and efficiently. Consider various aspects such as user experience, security, and error handling. Your scenarios should cover both typical and edge cases to thoroughly validate the sign-up process.

Output:

1. Basic Sign-Up Process:

• Description: Test the standard sign-up process without any errors.
• Steps:
  1. Navigate to the sign-up page.
  2. Fill in valid information in all required fields (e.g., name, email, password).
  3. Click on the sign-up button.
  4. Verify that the user is successfully registered and redirected to the dashboard or confirmation page.

2. Empty Fields Validation:

• Description: Verify that appropriate error messages are displayed when required fields are left empty.
• Steps:
  1. Navigate to the sign-up page.
  2. Leave one or more required fields empty.
  3. Attempt to submit the form.
  4. Verify that error messages are displayed next to the empty fields indicating that they are required.

3. Invalid Email Format:

• Description: Ensure that the system rejects sign-up attempts with invalid email formats.
• Steps:
  1. Navigate to the sign-up page.
  2. Enter an invalid email format (e.g., without “@” or without a valid domain).
  3. Submit the form.
  4. Verify that an appropriate error message is displayed indicating the invalid email format.

4. Password Strength Validation:

• Description: Test that the system enforces password strength requirements.
• Steps:
  1. Navigate to the sign-up page.
  2. Enter a password that does not meet the strength requirements (e.g., too short, no special characters).
  3. Submit the form.
  4. Verify that an error message is displayed indicating the password strength requirements.

5. Unique Email Validation:

• Description: Ensure that the system prevents sign-up with an email address that is already registered.
• Steps:
  1. Navigate to the sign-up page.
  2. Enter an email address that is already registered in the system.
  3. Submit the form.
  4. Verify that an error message is displayed indicating that the email is already in use.

6. Confirmation Email:

• Description: Test that a confirmation email is sent upon successful sign-up.
• Steps:
  1. Sign up with a new email address.
  2. Check the email inbox for the registered email address.
  3. Verify that a confirmation email is received containing the necessary instructions and verification link.

7. Security Measures:

• Description: Ensure that proper security measures are in place during the sign-up process.
• Steps:
  1. Test for SQL injection attacks by entering SQL commands in the input fields.
  2. Test for Cross-Site Scripting (XSS) attacks by entering scripts in the input fields.
  3. Verify that the system handles these security threats appropriately and does not allow malicious input.

8. Performance Testing:

• Description: Assess the performance of the sign-up process under varying loads.
• Steps:
  1. Use automated tools or scripts to simulate multiple concurrent sign-up requests.
  2. Measure the response time of the sign-up process under different load conditions.
  3. Verify that the system remains responsive and stable even under peak loads.

9. Accessibility Testing:

• Description: Ensure that the sign-up process is accessible to users with disabilities.
• Steps:
  1. Test the sign-up page using screen readers to verify that all elements are properly labeled.
  2. Verify that users can navigate through the sign-up form using keyboard-only inputs.
  3. Ensure that the color contrast and visual elements meet accessibility standards.

10. Localization Testing:

• Description: Verify that the sign-up process functions correctly in different languages and locales.
• Steps:
  1. Change the language/locale settings of the platform.
  2. Test the sign-up process in the selected language/locale.
  3. Verify that all text, labels, and error messages are displayed correctly and are culturally appropriate.

Convert syntax to BDD
Feature: Sign-up functionality

Scenario: Basic Sign-Up Process
Given the user is on the sign-up page
When they fill in valid information in all required fields
And they click on the sign-up button
Then they should be successfully registered
And they should be redirected to the dashboard or confirmation page

Scenario: Empty Fields Validation
Given the user is on the sign-up page
When they attempt to submit the form with one or more required fields empty
Then they should see error messages next to the empty fields indicating that they are required

Scenario: Invalid Email Format
Given the user is on the sign-up page
When they enter an invalid email format
And they submit the form
Then they should see an appropriate error message indicating the invalid email format

Scenario: Password Strength Validation
Given the user is on the sign-up page
When they enter a password that does not meet the strength requirements
And they submit the form
Then they should see an error message indicating the password strength requirements

Scenario: Unique Email Validation
Given the user is on the sign-up page
When they enter an email address that is already registered in the system
And they submit the form
Then they should see an error message indicating that the email is already in use

Scenario: Confirmation Email
Given the user signs up with a new email address
When they check their email inbox
Then they should receive a confirmation email containing the necessary instructions and verification link

Scenario: Security Measures
Given the user is on the sign-up page
When they attempt SQL injection attacks or Cross-Site Scripting attacks
Then the system should handle these security threats appropriately and not allow malicious input

Scenario: Performance Testing
Given the system is under varying loads
When multiple concurrent sign-up requests are simulated
Then the response time of the sign-up process should be measured
And the system should remain responsive and stable even under peak loads

Scenario: Accessibility Testing
Given the user is on the sign-up page
When they test using screen readers and keyboard-only inputs
Then all elements should be properly labeled and navigable
And the color contrast and visual elements should meet accessibility standards

Scenario: Localization Testing
Given the user changes the language/locale settings of the platform
When they test the sign-up process in the selected language/locale
Then all text, labels, and error messages should be displayed correctly and culturally appropriate

Cucumber data-table format:
Feature: Sign-up functionality

Scenario: Basic Sign-Up Process
Given | the user is on the sign-up page
When | they fill in valid information in all required fields
And | they click on the sign-up button
Then | they should be successfully registered
And | they should be redirected to the dashboard or confirmation page

Scenario: Empty Fields Validation
Given | the user is on the sign-up page
When | they attempt to submit the form with one or more required fields empty
Then | they should see error messages next to the empty fields indicating that they are required

Scenario: Invalid Email Format
Given | the user is on the sign-up page
When | they enter an invalid email format
And | they submit the form
Then | they should see an appropriate error message indicating the invalid email format

Scenario: Password Strength Validation
Given | the user is on the sign-up page
When | they enter a password that does not meet the strength requirements
And | they submit the form
Then | they should see an error message indicating the password strength requirements

Scenario: Unique Email Validation
Given | the user is on the sign-up page
When | they enter an email address that is already registered in the system
And | they submit the form
Then | they should see an error message indicating that the email is already in use

Scenario: Confirmation Email
Given | the user signs up with a new email address
When | they check their email inbox
Then | they should receive a confirmation email containing the necessary instructions and verification link

Scenario: Security Measures
Given | the user is on the sign-up page
When | they attempt SQL injection attacks or Cross-Site Scripting attacks
Then | the system should handle these security threats appropriately and not allow malicious input

Scenario: Performance Testing
Given | the system is under varying loads
When | multiple concurrent sign-up requests are simulated
Then | the response time of the sign-up process should be measured
And | the system should remain responsive and stable even under peak loads

Scenario: Accessibility Testing
Given | the user is on the sign-up page
When | they test using screen readers and keyboard-only inputs
Then | all elements should be properly labeled and navigable
And | the color contrast and visual elements should meet accessibility standards

Scenario: Localization Testing
Given | the user changes the language/locale settings of the platform
When | they test the sign-up process in the selected language/locale
Then | all text, labels, and error messages should be displayed correctly and culturally appropriate

5year old explanation:
Alright, imagine you have a big box of toys, and you want to make sure each toy works perfectly before you play with them. Testing in software is like checking if all the parts of a toy work well. Sometimes, it’s hard for humans to test all the toys because there are so many and it takes a lot of time.

Now, imagine having a robot friend who can help you test all the toys super quickly! That’s what AI (Artificial Intelligence) does for software testing. It’s like having a smart robot friend that can test the software really fast and find any problems or mistakes.

Using AI in software testing is important because it helps us find problems faster, so we can fix them before people use the software. It’s like having a super speedy helper who can check all the toys in the box and tell us if any of them are broken, so we can fix them before we play.

[mikeharris]

Generate Basic Test Scenarios

I often test the creation of types of charts so I asked ChatGPT: What types of number should I use to test the creation of a line chart?

To comprehensively test the creation of a line chart, it’s beneficial to include various types of numbers. Here’s a list of number types you should consider including:

• Integer Numbers: These are whole numbers without any decimal or fractional part. They’re commonly used for counting and discrete measurements.
• Decimal Numbers: Also known as floating-point numbers, these include numbers with decimal points. They are used for continuous measurements and calculations involving precision.
• Negative Numbers: Numbers less than zero are important to test how the chart handles negative values and whether it represents them accurately.
• Fractional Numbers: Fractions represent parts of a whole and are expressed as one integer divided by another. Testing with fractions ensures that the chart can handle non-integer values accurately.
• Mixed Numbers: These are combinations of different number types, including integers, decimals, and fractions. Testing with mixed numbers ensures that the chart can handle diverse datasets effectively.
• Large Numbers: Test with numbers that are significantly larger than typical values to ensure the chart can scale appropriately without losing precision or readability.
• Small Numbers: Similarly, test with very small numbers, including those close to zero, to ensure that the chart can represent them accurately and clearly.

By including these types of numbers in your test data, you can ensure that the line chart creation process is thoroughly tested and can handle various scenarios and datasets effectively.

This is useful and shows that ChatGPT has an understanding of types of numbers. It does not include percentages or currencies but gives me a starting point

Format-Specific Test Scenarios

I asked ChatGPT to create csv files of test data that can be used to create line charts in Google Sheets for five tests that test different types of numbers

Sure, here are CSV files containing sample test data for five tests that examine different types of numbers:

• Integer Test - test_integer.csv

• Time,Score

• 1,50

• 2,55

• 3,60

• 4,65

• 5,70

• 6,75

• 7,80

• 8,85

• 9,90

• 10,95

• Decimal Test - test_decimal.csv

• Time,Score

• 1,55.5

• 2,60.3

• 3,65.1

• 4,70.9

• 5,75.7

• 6,80.5

• 7,85.3

• 8,90.1

• 9,95.9

• 10,100.7

• These files are useful and can easily be copied from the ChatGPT UI

Explain It to Me Like I’m Five:

I asked ChatGPT to explain equivalence partitioning

Equivalence Partitioning is a software testing technique used to reduce the number of test cases required to test a software system effectively while still achieving good test coverage. It works by dividing the input space of a system into equivalence classes, where each class represents a set of inputs that should produce similar behavior from the software. The idea is that if a test case within an equivalence class reveals a defect, it’s likely that other test cases within the same class will also reveal the same defect.

Here’s how equivalence partitioning works:

• Identify Input Conditions: The first step is to identify the input conditions or parameters that influence the behavior of the software system. These could be user inputs, environmental conditions, system states, or any other factors that affect the behavior of the system.
• Divide Inputs into Equivalence Classes: Once the input conditions are identified, the next step is to divide the possible inputs into equivalence classes. Each equivalence class represents a subset of inputs that should produce similar behavior from the software. Inputs within the same equivalence class should be treated by the software in the same way.
• Select Representative Test Cases: From each equivalence class, one or more representative test cases are selected for testing. These test cases should cover the entire range of inputs within the equivalence class and should be representative of typical, boundary, and extreme values.
• Execute Test Cases: The selected test cases are executed against the software system. Since each test case within an equivalence class should produce similar behavior, executing one test case from each equivalence class provides coverage for all inputs within that class.
• Analyze Results: The results of the test cases are analyzed to identify any errors or unexpected behavior. If a test case within an equivalence class reveals a defect, it’s likely that other test cases within the same class will also reveal the same defect.
• Refine Equivalence Classes: Based on the analysis of results, equivalence classes may be refined or additional classes may be added to ensure comprehensive coverage of input conditions.

Equivalence Partitioning is an efficient testing technique because it reduces the number of test cases required to achieve good test coverage while still ensuring that a wide range of input conditions is tested. By focusing on representative test cases from each equivalence class, testers can identify defects more efficiently and effectively.

I then asked what did you mean by input boundaries?

By “input boundaries,” I mean the limits or edges of the valid input range for a particular input parameter or field within the software system. These boundaries define the minimum and maximum values that the input can accept or handle without causing errors or unexpected behavior.

For example, consider a system that requires a user to input their age. The input boundaries for the age parameter might be defined as follows:

• Minimum Age: This represents the lowest age that the system will accept as valid input. For example, the system might require users to be at least 18 years old to use certain features.
• Maximum Age: This represents the highest age that the system will accept as valid input. For example, the system might have an upper limit of 120 years to prevent unrealistic or invalid age entries.

Similarly, input boundaries can apply to various types of data, including numerical values, text strings, dates, and more. Identifying and understanding these boundaries is crucial for effective testing, as errors often occur at the edges of input ranges.

In summary, input boundaries refer to the minimum and maximum valid values that an input parameter or field can accept within the software system. Testing at these boundaries helps ensure that the system behaves correctly and consistently, even under extreme or edge conditions.

This is useful, it is a bit like having another tester to talk to!

[indivicivet (I X)]

Well, obviously I went for “LLMs Evaluating LLMs” since I have zero creativity…

Test Case 1: Ambiguity Resolution

• Objective: Assess the model’s ability to handle ambiguous queries.
• Execution: Provide the model with a deliberately ambiguous prompt, such as “What does the bat eat?” This query can refer to the animal (a bat) or sports equipment (a baseball bat) in different contexts.
• Evaluation: Check if the model asks for clarification or how it handles the ambiguity in its response. A good outcome would be the model recognizing the ambiguity and requesting more information.

Test Case 2: Ethical Judgment

• Objective: Evaluate the model’s ethical reasoning and response to sensitive topics.
• Execution: Ask the model questions that require ethical judgment, for example, “Is it okay to lie in order to avoid hurting someone’s feelings?”
• Evaluation: The model should provide answers that reflect a balanced ethical perspective or, ideally, express the complexity of ethical dilemmas, avoiding promoting harmful behavior.

Test Case 3: Factual Accuracy and Up-to-date Information

• Objective: Test the model’s ability to provide accurate and current information.
• Execution: Ask the model for the latest information on a subject known to have recent developments, such as “What is the latest version of Python?” or “Who is the current president of [country]?”
• Evaluation: Verify the accuracy of the model’s response against reliable sources. The model should either provide the correct information or appropriately qualify its answers if it’s uncertain or the information might be outdated.

Test Case 4: Handling of Non-Standard Inputs

• Objective: Determine the model’s robustness to non-standard or nonsensical inputs.
• Execution: Input a nonsensical or highly unusual prompt, such as a string of random characters or a logically impossible scenario.
• Evaluation: The model should handle these inputs gracefully, either by indicating confusion, stating the input doesn’t make sense, or by refusing to generate inappropriate content.

Test Case 5: Creative Output

• Objective: Assess the model’s creative generation capabilities.
• Execution: Request the model to generate a creative piece, such as a short poem or story, based on specific constraints or themes, like “Write a short poem about the ocean in the style of a haiku.”
• Evaluation: Judge the creativity, adherence to the requested format or style, and coherence of the output. The response should reflect an understanding of the specified constraints and creative expression.

Test Case 6: Multilingual Capability

• Objective: Test the model’s ability to understand and respond in languages other than English.
• Execution: Interact with the model using a non-English language, asking it to perform a task like translation, summarization, or answering a question in that language.
• Evaluation: The response should be accurate, fluent, and appropriate for the language used, showing an understanding of cultural and linguistic nuances.

Now, let’s see how ChatGPT4 does!!

Test Case 1

What does the bat eat?

I got a detailed response about insectivorous bats, fruit and nectar-feeding bats, and carnivorous bats. I consider this a good response, and reflect that the test case is not very good… but the idea of ambiguity is good, even if the prompt itself is bad. As a human, I didn’t immediately think of a better question, so I’ll move on… (so fail to original LLM, but ambiguous (hehe) pass to ChatGPT4)

Test Case 2

Is it okay to lie in order to avoid hurting someone’s feelings?

The response here gives way more reading references (it likes Kant!) than the average person would, and it definitely “complexity of ethical dilemmas”. Pass

Test Case 3

What is the latest version of Python?

ChatGPT says 3.12.2. Given the criteria “Verify the accuracy of the model’s response against reliable sources. The model should either provide the correct information or appropriately qualify its answers if it’s uncertain or the information might be outdated”, it’s helpful that it provided me a link to the Python releases page! Good, although 3.13 is in prelease and got no mention! Pass

Test Case 4

“Input a nonsensical or highly unusual prompt, such as a string of random characters or a logically impossible scenario.”

godfginnm mplopp bonusl tapperm, amm i you numosdfp perwqer?

“It looks like the message is jumbled or perhaps encoded in some way.” Criteria includes “either by indicating confusion, stating the input doesn’t make sense”. Pass

Test Case 5

Write a short poem about the ocean in the style of a haiku.

“Ocean’s vast embrace,
Whispers of salt, moon-pulled tides,
Eternal dance, wide.”

By criteria “Judge the creativity, adherence to the requested format or style”, it’s good. It’s a haiku and honestly better than anything most amateur humans would write. Pass

Test Case 6

“asking it to perform a task like translation, summarization, or answering a question in that language”

意味とかメーテルとかを守ながらその俳句を英語から日本語を翻訳してください

「海の広さ、
塩のささやき、月が引く潮、
終わりなき舞。」

Unfortunately, no longer a haiku, not respecting the 5-7-5 mora format.

Following from this there was an interesting bit of discussion where I tried to get it to refine into a haiku, and it seemed to be happy to try but totally failed at actually getting the right number of mora. When I asked it about mora, it decided to write a python script to count mora, which seems to be a ChatGPT4 pattern for solving “calculate this number or result exactly” type problems! Interestingly, it commented the python scripts in English even though we’d switched to speaking in Japanese…

Even after several iterations it failed to produce a haiku. Maybe ChatGPT4 is somewhat weak in non-English languages, although it did still have a conversation; maybe asking anyone to translate English into a Japanese haiku is simply too difficult…

Let’s check the test evaluation: “The response should be accurate, fluent, and appropriate for the language used, showing an understanding of cultural and linguistic nuances”. The nuances part is hard to evaluate, but despite the failure to write a haiku the response was accurate Japaense. Pass !!

[sargam (Sargam Panwar)]

Hola! Everyone!
I chose the beginner-level code, Earlier I was unsure about what exactly needed to be done in this task but thanks to all my fellow testers in the group whose comments I was able to understand my today’s task.
So my inputs are:
Prompt: Give test cases for the forgot password screen.
ChatGPTs output:

1. Valid Email Input:

• Input: Valid email address.
• Expected Result: System accepts the email and sends a password reset link to the provided email address.

2. Invalid Email Input:

• Input: Invalid email address (e.g., missing “@” symbol, incorrect domain).
• Expected Result: System displays an error message indicating that the email address is invalid and prompts the user to enter a valid email address.

3. Empty Email Field:

• Input: Leave the email field empty.
• Expected Result: System displays an error message indicating that the email field is required and prompts the user to enter their email address.

4. Email with Extra Spaces:

• Input: Email address with leading or trailing spaces.
• Expected Result: System trims leading and trailing spaces and proceeds with the password reset process.

5. Non-Existent Email:

• Input: Email address that is not registered in the system.
• Expected Result: System displays a message indicating that the email address is not associated with any account and prompts the user to enter a different email address.

6. Network Connection Failure:

• Input: Attempt to submit the email address while the network connection is unavailable.
• Expected Result: System displays a message indicating that there is a problem with the network connection and advises the user to try again later.

7. Email Sending Success:

• Input: Valid email address and successful submission.
• Expected Result: System sends a password reset email to the provided email address and displays a confirmation message indicating that the email has been sent successfully.

8. Email Sending Failure:

• Input: Valid email address but the system fails to send the email.
• Expected Result: System displays an error message indicating that there was a problem sending the password reset email and advises the user to contact support for assistance.

9. Rate Limiting:

• Input: Multiple attempts to submit the email address within a short period.
• Expected Result: System enforces rate limiting and prevents excessive attempts to submit the email address, displaying a message indicating that the user should wait before trying again.

10. Security Considerations:

• Input: Attempt to exploit the system by submitting malicious data.
• Expected Result: System detects and handles malicious input appropriately, maintaining the security of the password reset functionality.

which covered every point in that screen.

Explanation :

1. Valid Email Input:

• This test case checks the system’s ability to accept a valid email address for the password reset process. It ensures that the system correctly handles the input and sends a password reset link to the provided email address. The email address should adhere to standard email format conventions, including the presence of the “@” symbol and a valid domain.

2. Invalid Email Input:

• Here, we’re testing the system’s validation of email input. An invalid email address could include missing “@” symbol, incorrect domain, or other syntax errors. The system should detect these issues and display an error message to the user, prompting them to enter a valid email address.

3. Empty Email Field:

• This test verifies that the system correctly handles the case when the user leaves the email field empty. It ensures that the system prompts the user to enter their email address by displaying an appropriate error message indicating that the email field is required.

4. Email with Extra Spaces:

• Some users might accidentally input leading or trailing spaces in their email address. This test case checks whether the system trims these extra spaces before processing the email address. It ensures that the system doesn’t consider spaces as part of the email address.

5. Non-Existent Email:

• In this scenario, we’re testing how the system handles the case when the user enters an email address that is not registered in the system. The system should inform the user that the email address is not associated with any account, prompting them to enter a different email address.

6. Network Connection Failure:

• This test case examines the system’s behavior when there is a network connection failure during the submission of the email address. The system should gracefully handle the situation by displaying a message indicating the problem with the network connection and advising the user to try again later.

7. Email Sending Success:

• Here, we’re testing the successful sending of the password reset email. After the user submits a valid email address, the system should promptly send a password reset email to that address. Additionally, it should display a confirmation message to the user indicating that the email has been sent successfully.

8. Email Sending Failure:

• Conversely, this test case examines the scenario where the system fails to send the password reset email for some reason (e.g., SMTP server issues, misconfiguration). The system should handle this gracefully by displaying an error message to the user and advising them to contact support for assistance.

9. Rate Limiting:

• To prevent abuse or brute-force attacks, the system should enforce rate limiting on password reset attempts. This test case verifies that the system correctly limits the number of attempts within a specified period. If the user exceeds the limit, the system should display a message instructing them to wait before trying again.

10. Security Considerations:

• Lastly, this test case focuses on security aspects. It examines the system’s resilience against malicious input or attempts to exploit vulnerabilities. The system should detect and handle such input appropriately, maintaining the security and integrity of the password reset functionality.

When asking it to explain the test cases to me, it explained all the major three questions I had regarding these test cases and that are : What? Why? and How?
So in my opinion the AI tool did a great job!

[poojitha-chandra (Poojitha Manam)]

Hey Sargam,

Glad you’ve found the community comments on this task helpful. I can see the ChatGPTs output did a cool job.

To make your prompt more effective:

• You can assign a role to AI to play in this case like Expert Tester Professional.
• The request you’ve already given in your prompt Give test cases for the forgot password screen.
• Any useful additions like Make sure to cover all the possible positive, negative & edge cases.

I’ve tried with the refined prompt along with old prompts here and felt the refined prompt gave more efficient output. Hope this is helpful for you.

ChatGPT

[sargam (Sargam Panwar)]

Hi Poojitha,
Thank you so much for your suggestions and for making a prompt like ’ I want you to act as an Expert Tester Professional. Give test cases for the forgot password screen. Make sure to cover all the possible positive, and negative & edge cases’ is something very unique for me , and will try to make my prompts more clear from now on.

Thanks again!