Testing Concepts
Q: Difference between 𝐓𝐞𝐬𝐭 𝐩𝐥𝐚𝐧 & 𝐓𝐞𝐬𝐭 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐲?
Test Plan:
Purpose: A test plan is a detailed document that outlines the approach, scope, objectives, resources, schedule, and deliverables for the testing effort. It provides a roadmap for how testing will be conducted throughout the project lifecycle.
Scope: Test plans typically cover the entire testing process, including test objectives, test deliverables, test environment setup, test execution approach, test schedules, and resource allocation.
Content: A test plan includes sections such as introduction, objectives, scope, approach, schedule, resources, risks, assumptions, dependencies, and exit criteria. It details the specific tests to be performed, the test environment configuration, the test data requirements, and the roles and responsibilities of team members.
Level of Detail: Test plans are usually more detailed and comprehensive, addressing specific aspects of the testing process and providing guidance for the testing team throughout the project.
Test Strategy:
Purpose: A test strategy is a high-level document that defines the overall approach to testing for a project. It outlines the testing objectives, methods, and techniques to be used to ensure that the testing effort aligns with the project goals and requirements.
Scope: Test strategy focuses on defining the overall testing approach, including the types of testing to be performed, the testing tools and techniques to be used, the test automation strategy, and the overall quality goals.
Content: A test strategy document typically includes sections such as introduction, objectives, scope, testing approach, testing types, testing tools, automation approach, resource requirements, and exit criteria. It provides guidelines for making decisions related to testing throughout the project lifecycle.
Level of Detail: Test strategy documents are less detailed compared to test plans and focus on providing high-level guidance and direction for the testing effort. They are often used to communicate the overall testing approach to stakeholders and to ensure that testing aligns with the project goals and objectives.
Q: What are different Test case design technique?
Ans:
Test case design techniques are strategies used to create effective and efficient test cases for verifying software functionality. Here are some common test case design techniques and how to use them:
1. Equivalence Partitioning
Objective: Divide input data into equivalent partitions where test cases can be derived from each partition. The idea is that if one value in a partition works, all values in that partition will work similarly.
Example: For an age input field that accepts values from 0 to 120:
Valid Partitions: 0-120
Invalid Partitions: Less than 0, Greater than 120
Test Cases:
Valid partition: 25
Invalid partition: -1
2. Boundary Value Analysis
Objective: Focus on the boundaries of input values, where errors are most likely to occur.
Example: For an age input field (0 to 120):
Boundary values: 0, 1, 119, 120
Test Cases:
Lower boundary: 0 (valid)
Just below lower boundary: -1 (invalid)
Just above lower boundary: 1 (valid)
Upper boundary: 120 (valid)
Just above upper boundary: 121 (invalid)
Just below upper boundary: 119 (valid)
3. Decision Table Testing
Objective: Create a table to represent combinations of conditions and actions, ensuring all possible combinations are tested.
Example: For a login form with the following rules:
Conditions: Valid username (Y/N), Valid password (Y/N)
Actions: Login success (Y/N)
Username Valid Password Valid Login Success
Y Y Y
Y N N
N Y N
N N N
Test Cases:
Valid username and password: Login succeeds.
Valid username, invalid password: Login fails.
Invalid username, valid password: Login fails.
Invalid username and password: Login fails.
4. State Transition Testing
Objective: Test the application’s behavior based on state changes and transitions between different states.
Example: For a user account with states like Active, Inactive, Locked, and transitions like Activate, Deactivate, Lock, Unlock:
Test Cases:
Initial State: Inactive
Transition: Activate → New State: Active
Initial State: Active
Transition: Lock → New State: Locked
Initial State: Locked
Transition: Unlock → New State: Active
5. Use Case Testing
Objective: Derive test cases from use cases that describe the functional requirements of the system.
Example: For a banking application with a use case for transferring money:
Precondition: User is logged in.
Main Flow:
User selects Transfer Funds.
User enters recipient details and amount.
User confirms the transfer.
System processes the transfer and displays a success message.
Test Cases:
User transfers money with valid details.
User transfers money with invalid recipient details.
User transfers money with insufficient balance.
6. Pairwise Testing
Objective: Test all possible pairs of input parameters to identify issues that may occur due to interactions between them.
Example: For a form with three fields: Color (Red/Blue), Size (Small/Medium/Large), and Material (Cotton/Wool), you test combinations of these pairs:
Test Cases:
(Red, Small, Cotton)
(Blue, Medium, Wool)
(Red, Large, Wool)
(Blue, Small, Cotton)
7. Exploratory Testing
Objective: Use tester’s experience and intuition to explore the application without predefined test cases, to uncover unexpected issues.
Example: Navigate through the application’s features, try various inputs, and use cases beyond the standard scenarios to find bugs.
8. Error Guessing
Objective: Use experience and intuition to guess where errors might occur, based on common mistakes and previous experience.
Example: Testing edge cases, invalid inputs, or unusual usage patterns that are not covered by other techniques.
Best Practices for Test Case Design:
Understand Requirements: Ensure test cases are derived from clear and complete requirements.
Keep Test Cases Simple: Each test case should focus on a single aspect or condition.
Use Test Case Management Tools: Tools like Jira, TestRail, or QTest can help manage and organize test cases effectively.
Prioritize Test Cases: Focus on high-risk areas and critical functionalities.
Review and Update: Regularly review and update test cases based on changes in requirements or discovered issues.
Q: What is Quality metrix ?
Quality metrics are standards or measurements used to assess and manage the quality of a product, process, or service. They are essential for evaluating performance, identifying areas for improvement, and ensuring that quality objectives are met. In the context of software development, quality metrics help measure the effectiveness and efficiency of development processes and the quality of software products.
Key Quality Metrics in Software Development
Defect Density
Definition: The number of defects per unit of software size, such as per thousand lines of code (KLOC) or function points.
Purpose: Helps in assessing the quality of the software by measuring how many defects are found in a given amount of code.
Test Coverage
Definition: The percentage of the codebase that is executed by automated tests.
Purpose: Ensures that a significant portion of the code is tested, which helps in identifying untested parts of the application.
Defect Detection Rate
Definition: The number of defects detected in a specific period or phase of development.
Purpose: Measures the efficiency of the testing process and helps in identifying whether defects are being caught early or late in the development cycle.
Defect Resolution Time
Definition: The average time taken to resolve and close a defect from the time it is reported.
Purpose: Helps in evaluating the efficiency of the defect resolution process and the responsiveness of the development team.
Customer Satisfaction
Definition: Measures how satisfied customers are with the software product.
Purpose: Provides insight into the user experience and the effectiveness of the software in meeting user needs.
Code Quality Metrics
Cyclomatic Complexity: Measures the complexity of a program by counting the number of linearly independent paths through the code.
Code Churn: The amount of code added, modified, or deleted over time. High code churn may indicate instability in the codebase.
Technical Debt: Measures the cost of additional rework caused by choosing an easy solution now instead of using a better approach that would take longer.
Error Rate
Definition: The number of errors or issues per unit of output or per time period.
Purpose: Helps in understanding the frequency of errors and identifying areas where the process might be failing.
Rework Percentage
Definition: The percentage of effort that is spent on fixing defects and redoing tasks.
Purpose: Indicates the effectiveness of the initial development and testing processes. High rework percentages suggest issues with initial quality.
Customer Reported Issues
Definition: The number of issues or complaints reported by customers after the software has been released.
Purpose: Helps in understanding the real-world impact of defects and areas where the software may not meet customer expectations.
Test Case Effectiveness
Definition: The ratio of the number of defects found by tests to the total number of defects found.
Purpose: Measures how effective the test cases are in catching defects and ensuring comprehensive testing.
Why Quality Metrics are Important
Improves Quality: Regularly monitoring quality metrics helps in identifying weaknesses and areas for improvement in the software development process.
Informs Decisions: Provides objective data that can be used to make informed decisions about process changes and resource allocation.
Enhances Communication: Helps in communicating quality issues and achievements with stakeholders and team members.
Supports Continuous Improvement: Provides a basis for continuous improvement by identifying trends and areas where changes are needed.
How to Implement Quality Metrics
Define Metrics: Identify which metrics are relevant to your project or organization.
Collect Data: Use tools and processes to gather data on the defined metrics.
Analyze Results: Review and analyze the data to understand the current quality levels and identify areas for improvement.
Act on Insights: Implement changes based on the analysis to improve quality.
Review and Adjust: Regularly review the metrics and adjust processes as necessary to continuously enhance quality.
By leveraging quality metrics effectively, organizations can enhance their software development processes, deliver better products, and achieve higher levels of customer satisfaction.
Q: Write a pipeline which we can use in project?
Ans:
pipeline {
agent any
stages {
stage('Checkout') {
steps {
git branch: 'master', url: 'https://github.com/djmishra2709/PlaywrightAutomation.git'
}
}
stage('Build and Test') {
steps {
// Build and execute your automation tests
sh 'mvn clean install'
}
}
}
post {
always {
// Archive the test report files
archiveArtifacts artifacts: '**/target/surefire-reports/*.xml', allowEmptyArchive: true
}
success {
script {
// Get the latest test report file
def reportFile = findFiles(glob: '**/target/surefire-reports/*.xml').first()
if (reportFile != null) {
// Define email parameters
def subject = "Test Automation Report - ${env.JOB_NAME} - Build #${env.BUILD_NUMBER}"
def body = "Attached is the test report for the ${env.JOB_NAME} build #${env.BUILD_NUMBER}."
// Send email with attachment
emailext subject: subject,
body: body,
to: 'djmishra2709@gmail.com',
attachLog: true,
attachmentsPattern: reportFile.path
} else {
echo "No test report file found."
}
}
}
}
}
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