From 45b66e0e95aa62d469a8d192be45a3df179ffc8a Mon Sep 17 00:00:00 2001 From: Animesh Pathak <53110238+Sonichigo@users.noreply.github.com> Date: Mon, 29 Jul 2024 23:16:40 +0530 Subject: [PATCH] fix: installation in docker with linux/wsl (#431) Signed-off-by: Animesh Pathak --- .../reference/glossary/ai-test-completion.md | 69 ++++--- .../reference/glossary/black-box-testing.md | 87 +++++---- .../reference/glossary/cucumber-testing.md | 46 +---- .../reference/glossary/end-to-end-testing.md | 26 ++- .../glossary/software-testing-life-cycle.md | 4 +- .../reference/glossary/white-box-testing.md | 182 ++++++++---------- .../quickstart/python-flask-mongo-local.md | 171 ---------------- 7 files changed, 207 insertions(+), 378 deletions(-) delete mode 100644 versioned_docs/version-2.0.0/quickstart/python-flask-mongo-local.md diff --git a/versioned_docs/version-2.0.0/concepts/reference/glossary/ai-test-completion.md b/versioned_docs/version-2.0.0/concepts/reference/glossary/ai-test-completion.md index 39f157445..f40807969 100644 --- a/versioned_docs/version-2.0.0/concepts/reference/glossary/ai-test-completion.md +++ b/versioned_docs/version-2.0.0/concepts/reference/glossary/ai-test-completion.md @@ -13,17 +13,18 @@ keywords: - AI-driven testing --- -AI Test Completion refers to the application of Artificial Intelligence (AI) and GenAI techniques to automate and assist in the creation, execution, and maintenance of test cases. This approach aims to enhance testing efficiency, coverage, and accuracy by leveraging intelligent algorithms to predict and generate tests. +AI Test Completion refers to leveraging LLM's, and GenAI to either automate and assist in the creation or execution and maintenance of test cases. +It is used to enhance testing efficiency, coverage, and accuracy by leveraging AI to predict and generate tests which can help in increasing code coverage. -## How AI Test Completion Works +## How does testing with AI works ? -AI Test Completion typically involves the following steps: +Typically using AI for test involves the multiple steps, such as: -1. **Training Phase**: AI models are trained on historical test data, including past test cases, outcomes, and system behavior. +1. **Training Phase**: AI models are trained on historical test data including past test cases, outcomes, and behavior of application. -2. **Prediction and Generation**: AI algorithms analyze patterns in the data to predict potential test scenarios and generate test cases automatically. +2. **Prediction**: The AI analyze patterns in the source codebase to predict potential test scenarios as well as edge scenarios and then generate test cases automatically. -3. **Execution and Feedback**: Generated test cases are executed against the system under test. Feedback from these executions is used to refine and improve the AI models iteratively. +3. **Feedback**: Generated test cases are validated against the system under test and feedback from these executions is used to refine and improve the AI models. ## What are Advantages of AI Tests ? @@ -31,7 +32,7 @@ AI Test Completion typically involves the following steps: - **Enhanced Coverage**: AI can identify edge cases and scenarios that may be overlooked by human testers, improving test coverage. - **Improved Accuracy**: Reduces human error in testing by applying consistent and objective criteria to test case creation and execution. - **Cost-Effective**: Saves costs associated with manual testing efforts and allows testers to focus on more complex and critical tasks. -- **Scalability**: Easily scales to handle large and complex software systems, accommodating rapid changes and updates. +- **Scalability**: It can easily scales to handle large and complex software systems, accommodating rapid changes and updates. ## What are disadvantages of AI Tests ? @@ -42,37 +43,59 @@ AI Test Completion typically involves the following steps: - **Security Concerns**: Introducing AI into testing processes may raise security concerns related to data privacy and integrity. - **Integration Challenges**: Integrating AI-driven testing tools with existing CI/CD pipelines and workflows can present integration challenges. -## Why Keploy's AI based Testing is better ? +## Why Keploy AI based test cases are superior? + +Keploy's unit test generation feature leverages the power of LLMs to propose test cases that cover various code paths and edge cases. The generated tests are then validated and integrated into the existing test suite, aiming to increase code coverage and ensure the correctness of the code. Keploy's UTGen is designed in such a way which can reduce the manual effort required in writing unit tests, providing developers with a powerful tool to enhance their testing workflows. + +### Benefits of using Keploy's AI-based testing + +By using Keploy’s AI-based testing : + +- Developers: Save time and reduce the effort required for writing unit and integration tests. +- QA Teams: Achieve higher test coverage and more accurate testing results. +- Organizations: Improve overall software quality and reduce time-to-market. ## Conclusion AI Test Completion represents a significant advancement in software testing, leveraging AI and ML to automate and improve the testing process. By automating test case generation, predicting potential scenarios, and enhancing test coverage, AI Test Completion enables teams to achieve higher efficiency, accuracy, and scalability in their testing efforts. However, challenges such as data quality, setup complexity, and integration issues must be addressed to fully leverage the benefits of AI-driven testing. Integrating AI Test Completion into testing workflows can empower teams to deliver robust software solutions that meet user expectations and business requirements effectively. -## FAQ about AI Test Completion +## FAQ + +### How does AI test completion work? + +By analyzing the application's code, user behavior, and existing test cases to predict potential issues and generate new test cases. It uses large language models to identify patterns and optimize the testing process. + +### What are the benefits of AI test completion?\*\* + +The user usually have increased test coverage, faster test execution, reduced human error, improved defect detection, and more efficient use of testing resources. With AI, tests can also adapt to changes in the application, ensuring continuous quality assurance. + +### Can AI test completion replace manual testing? -1. **What is AI Test Completion?** +AI test completion is not a replacement for manual testing but a complementary tool. It can handle repetitive and complex tasks, allowing human testers to focus on exploratory testing, critical thinking, and understanding user experience. - - AI Test Completion uses AI and ML techniques to automate and assist in creating, executing, and maintaining test cases. +### What are the limitations of AI test completion?\*\* -2. **How does AI improve testing efficiency?** +Limitations include the need for high-quality data, the potential for false positives or negatives, the complexity of integrating AI tools with existing systems, and the requirement for skilled personnel to manage and interpret AI outputs. - - AI automates repetitive tasks, predicts potential test scenarios, and enhances test coverage, improving overall efficiency. +### How is AI test completion different from traditional testing methods?\*\* -3. **Can AI Test Completion replace human testers?** +Traditional testing methods rely heavily on human effort to create and execute test cases, whereas AI test completion automates these processes using algorithms. AI can analyze vast amounts of data quickly, adapt to changes, and continuously learn from new information. - - No, AI complements human testers by automating routine tasks. Human testers provide critical thinking and creativity. +### What are some popular AI testing tools? -4. **What are the challenges of implementing AI Test Completion?** +Popular tools include Testim, Applitools, Functionize, TestCraft, and mabl. These tools offer features like autonomous test case generation, visual validation, integration with CI/CD pipelines, and AI-driven test maintenance. - - Challenges include data quality dependency, setup complexity, maintenance overhead, and integration issues. +### What is Keploy's unit test generation (UTGen) feature? -5. **What types of testing can AI Test Completion assist with?** +Keploy's UTGen uses Large Language Models (LLMs) to automatically generate unit test cases. These test cases cover various code paths and edge cases, significantly reducing the manual effort required in writing unit tests. - - AI can assist with various testing types, including functional testing, regression testing, and performance testing. +### How are the generated tests validated and integrated? -6. **Is AI Test Completion suitable for Agile and DevOps environments?** +The proposed test cases are validated to ensure they accurately test the intended functionality. Once validated, these tests are integrated into the existing test suite, enhancing the overall testing process. - - Yes, AI Test Completion supports Agile and DevOps practices by enabling continuous testing and faster feedback loops. +### What are the benefits of using Keploy's AI-based testing? -7. **How can AI Test Completion benefit software development teams?** - - It enhances testing accuracy, scalability, and cost-effectiveness, allowing teams to deliver higher quality software faster. +- _Increased Code Coverage_: By generating tests that cover a wide range of scenarios, Keploy ensures higher code coverage. +- _Reduced Manual Effort_: Automating the test generation process saves significant time and effort for developers. +- _Enhanced Accuracy_: AI-generated tests can detect edge cases and potential issues that might be missed by manual testing. +- _Continuous Improvement_: Keploy continuously learns from new data and improves its test generation capabilities. diff --git a/versioned_docs/version-2.0.0/concepts/reference/glossary/black-box-testing.md b/versioned_docs/version-2.0.0/concepts/reference/glossary/black-box-testing.md index bd5c0371c..d2de55a2f 100644 --- a/versioned_docs/version-2.0.0/concepts/reference/glossary/black-box-testing.md +++ b/versioned_docs/version-2.0.0/concepts/reference/glossary/black-box-testing.md @@ -1,8 +1,8 @@ --- id: black-box-testing -title: What is Black Box Testing ? +title: Mastering Black Box Testing - Techniques, Benefits, and Best Practices sidebar_label: Black Box Testing -description: This glossary has an explanation of all the terminologies that beginners find difficult to understand at first glance. +description: Discover the fundamentals of black box testing. Learn about key techniques like equivalence partitioning, boundary value analysis, and decision table testing. Enhance your software's quality by focusing on external behavior without internal code knowledge. tags: - explanation - Glossary @@ -16,6 +16,8 @@ keywords: - black box testing techniques - black box testing - what is black box testing + - keploy + - regression testing --- Black-box testing is a software testing method where the tester evaluates the functionality of an application without having access to its internal code structure, algorithms, or implementation details. Instead, the tester interacts with the software through its user interface or exposed APIs, treating it as a "black box" whose internal workings are not visible or known. @@ -44,12 +46,14 @@ This testing approach is essential for several reasons: ## What are the Benefits of Black-Box Testing? -- Can be performed by testers with a variety of skill levels -- Can find a wide range of defects, including those that are related to the software's external behavior -- Can be used to verify the software's functionality, usability, and performance -- Can be used to identify potential security vulnerabilities +1. **Independence from Internal Implementation**: Allows unbiased and realistic assessment, mimicking end-user perspectives. +2. **User-Centric Perspective**: Aligns testing with user experience, identifying usability flaws and unexpected behaviors. +3. **Comprehensive Test Coverage**: Covers various scenarios, inputs, and usage patterns, uncovering defects not apparent during development. +4. **Validation of Requirements**: Ensures the software meets documented requirements and user expectations. +5. **Detection of Defects**: Identifies functional errors, security vulnerabilities, and performance bottlenecks. +6. **Accessibility**: Suitable for testers with diverse backgrounds and skill sets, adaptable to various software applications. -## Types of Black-Box Testing Techniques +## Whate are types of Black-Box Testing Techniques ? ![How Black Box testing Works?](https://www.imperva.com/learn/wp-content/uploads/sites/13/2020/03/thumbnail_Black-box.jpg) @@ -59,16 +63,17 @@ Equivalence partitioning is a black-box testing technique that divides the input **Example:** Consider a login screen for a web application that requires users to enter their username and password. In equivalence partitioning, we can identify three equivalence classes for each input: -- Valid username: Any valid username (e.g., "user123") -- Invalid username: Username that doesn't exist in the system (e.g., "invaliduser") -- Empty username: No username provided +- _Valid username_: Any valid username (e.g., "user123") +- _Invalid username_: Username that doesn't exist in the system (e.g., "invaliduser") +- _Empty username_: No username provided Similarly, for the password field, we can identify equivalence classes such as: -- Valid password: Correct password corresponding to the provided username -- Invalid password: Incorrect password for the provided username -- Empty password: No password provided - Test cases would then be designed to cover at least one scenario from each equivalence class, ensuring comprehensive test coverage while minimizing redundancy. +- _Valid password_: Correct password corresponding to the provided username +- _Invalid password_: Incorrect password for the provided username +- _Empty password_: No password provided + +Test cases would then be designed to cover at least one scenario from each equivalence class, ensuring comprehensive test coverage while minimizing redundancy. ### 2. Boundary Value Analysis: @@ -76,12 +81,13 @@ Boundary value analysis (BVA) is a black-box testing technique used to test the **Example:** Consider a software application that accepts user input for the age of a person, with the valid range defined as 18 to 65 years. In boundary value analysis, we would design test cases to evaluate the behavior of the application at the boundaries and just beyond them: -- Test case 1: Input age as 17 (just below the lower boundary) -- Test case 2: Input age as 18 (lower boundary) -- Test case 3: Input age as 19 (within the valid range) -- Test case 4: Input age as 65 (upper boundary) -- Test case 5: Input age as 66 (just above the upper boundary) - By testing at these boundary values, we can uncover potential issues such as off-by-one errors, boundary-related validation failures, and unexpected behaviors near the edges of the input range. +- _Test case 1_: Input age as 17 (just below the lower boundary) +- _Test case 2_: Input age as 18 (lower boundary) +- _Test case 3_: Input age as 19 (within the valid range) +- _Test case 4_: Input age as 65 (upper boundary) +- _Test case 5_: Input age as 66 (just above the upper boundary) + +By testing at these boundary values, we can uncover potential issues such as off-by-one errors, boundary-related validation failures, and unexpected behaviors near the edges of the input range. ### 3. Decision Table Testing: @@ -89,11 +95,12 @@ Decision table testing is a black-box testing technique used to test systems wit **Example:** Consider a shipping application that calculates shipping charges based on the weight and destination of a package. The decision table would list all possible combinations of inputs (weight and destination) and specify the corresponding shipping charges or actions. Test cases would then be derived to cover each combination: -- Test case 1: Package weight = 2 kg, Destination = Local (Domestic) -- Test case 2: Package weight = 5 kg, Destination = International -- Test case 3: Package weight = 10 kg, Destination = Local (Domestic) -- Test case 4: Package weight = 15 kg, Destination = International - By systematically testing each combination of inputs, decision table testing helps ensure that the software behaves correctly under various scenarios. +- _Test case 1_: Package weight = 2 kg, Destination = Local (Domestic) +- _Test case 2_: Package weight = 5 kg, Destination = International +- _Test case 3_: Package weight = 10 kg, Destination = Local (Domestic) +- _Test case 4_: Package weight = 15 kg, Destination = International + +By testing each combination of inputs, decision table testing helps us ensuring that the software behaves correctly under various scenarios. ### 4. State Transition Testing: @@ -101,15 +108,16 @@ State transition testing is a black-box testing technique used to test systems t **Example:** Consider a traffic light control system with three states: Green, Yellow, and Red. State transition testing would involve designing test cases to validate the transitions between these states based on predefined rules: -- Test case 1: Transition from Green to Yellow when the timer expires -- Test case 2: Transition from Yellow to Red when the timer expires -- Test case 3: Transition from Red to Green after a specified delay -- Test case 4: Validate that the system remains in the Red state during a power outage - By testing the transitions between states and verifying the system's behavior under different conditions, state transition testing helps ensure the reliability and correctness of state-based systems. +- _Test case 1_: Transition from Green to Yellow when the timer expires +- _Test case 2_: Transition from Yellow to Red when the timer expires +- _Test case 3_: Transition from Red to Green after a specified delay +- _Test case 4_: Validate that the system remains in the Red state during a power outage + +By testing the transitions between states and verifying the system's behavior under different conditions, state transition testing helps ensure the reliability and correctness of state-based systems. ## Comparison of Black-Box Testing and White-Box Testing -| Black-box testing | White-box testing | +| **Black-box testing** | **White-box testing** | | ----------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------- | | Does not require knowledge of the internal structure or implementation details of the software being tested | Requires knowledge of the internal structure or implementation details of the software being tested | | Focuses on the software's external behavior and how it interacts with users | Focuses on the software's internal logic and how it works | @@ -117,21 +125,22 @@ State transition testing is a black-box testing technique used to test systems t | Can find a wide range of defects | Can find defects that are related to the software's internal logic | | Can be used to verify the software's functionality, usability, and performance | Can be used to optimize performance, identify vulnerabilities, and ensure robust applications | -## **Black-Box testing with Keploy** +## How to use Keploy for black-Box testing? -- Installation and Integration: Install Keploy and integrate it into your testing environment. Keploy supports various platforms and CI tools like GitHub, GitLab, and Jenkins, making integration seamless. +Firstly, install [Keploy](https://keploy.io/), a testing tool that helps you automate the testing process. Here’s how you can perform black box +testing with Keploy: -- Record User Interactions: Use Keploy to record user interactions with your application. This includes actions such as clicking buttons, entering text, navigating menus, and submitting forms. +- **Record User Interactions**: Use Keploy to record user interactions with your application. This includes actions such as clicking buttons, entering text, navigating menus, and submitting forms. -- Generate Test Cases:Keploy automatically generates test cases based on the recorded user interactions. These test cases represent different scenarios and functionalities of your application from an external perspective. +- **Generate Test Cases**: Keploy automatically generates test cases based on the recorded user interactions. These test cases represent different scenarios and functionalities of your application from an external perspective. -- Customize and Expand Test Coverage: Customize the generated test cases to cover specific features, edge cases, or user scenarios. You can expand test coverage by adding additional test scenarios that may not have been captured during initial recording. +- **Customize and Expand Test Coverage**: Customize the generated test cases to cover specific features, edge cases, or user scenarios. You can expand test coverage by adding additional test scenarios that may not have been captured during initial recording. -- Execute Tests: Run the generated test cases using Keploy. It will simulate user interactions and validate the functionality of your application based on the recorded scenarios. +- **Execute Tests**: Run the generated test cases using Keploy. It will simulate user interactions and validate the functionality of your application based on the recorded scenarios. -- Analyze Results: Analyze the test results generated by Keploy. It provides detailed reports on test coverage, pass/fail status, and any errors encountered during testing. +- **Analyze Results**: Analyze the test results generated by Keploy. It provides detailed reports on test coverage, pass/fail status, and any errors encountered during testing. -- Regression Testing: Use Keploy to perform regression testing by re-running previously recorded test cases after making changes to your application. This ensures that new updates do not introduce unintended side effects or break existing functionality. +- **Regression Testing**: Use Keploy to perform regression testing by re-running previously recorded test cases after making changes to your application. This ensures that new updates do not introduce unintended side effects or break existing functionality. ## Conclusion diff --git a/versioned_docs/version-2.0.0/concepts/reference/glossary/cucumber-testing.md b/versioned_docs/version-2.0.0/concepts/reference/glossary/cucumber-testing.md index 0b09bfaf6..715fead28 100644 --- a/versioned_docs/version-2.0.0/concepts/reference/glossary/cucumber-testing.md +++ b/versioned_docs/version-2.0.0/concepts/reference/glossary/cucumber-testing.md @@ -13,11 +13,16 @@ keywords: - Gherkin --- -Cucumber is a popular tool used for Behavior-Driven Development (BDD) that allows you to write test cases in a simple, human-readable format. It bridges the gap between technical and non-technical stakeholders by enabling collaboration through executable specifications. This article explores how Cucumber works, its key components, and provides practical examples in JavaScript. +In few recent decades, Cucumber has become a popular tool as a BDD tool, allowing user to write test cases in a simple, human-readable format. Also, it has bridged the gap between technical and non-technical stakeholders by enabling collaboration by simplifying the test specifications. ## Key Components of Cucumber -Cucumber testing consists of three main components: feature files, step definitions, and runner configuration. These components work together to define, automate, and execute test scenarios in a BDD framework. Let's explore each component in detail: +Cucumber tests consist of 2 main components: + +1. feature files. +2. step definitions. + +These components work together to define, automate, and execute test scenarios in a BDD framework. Let's explore each component in detail: ### 1. **Feature Files** @@ -66,41 +71,6 @@ Then("the result should be {int} on the screen", function (expected) { }); ``` -### 3. **Runner Configuration** - -Runner configuration in Cucumber.js sets up Cucumber to execute feature files with corresponding step definitions. It integrates with testing frameworks like Mocha or Jasmine to run scenarios and generate test reports. - -Example of a Cucumber.js runner configuration (`cucumber.js`): - -```javascript -const {setWorldConstructor, BeforeAll, AfterAll} = require("cucumber"); -const {defineSupportCode} = require("cucumber"); -const {expect} = require("chai"); - -defineSupportCode(({setWorldConstructor, Before, After, Given, When, Then}) => { - // Global setup and teardown - BeforeAll(async function () { - // Code to run before all scenarios - }); - - AfterAll(async function () { - // Code to run after all scenarios - }); - - Given("I have entered {int} into the calculator", function (number) { - // Step definition implementation - }); - - When("I press add", function () { - // Step definition implementation - }); - - Then("the result should be {int} on the screen", function (expected) { - // Step definition implementation - }); -}); -``` - ## What are advantages of Cucumber Testing ? - **Collaboration**: Facilitates collaboration between technical and non-technical stakeholders through understandable feature files. @@ -138,7 +108,7 @@ Cucumber testing revolutionizes software testing by enabling teams to collaborat ### 1. **What is Cucumber testing used for?** -- Cucumber is used for Behavior-Driven Development (BDD) to write acceptance tests in a human-readable format. +- Cucumber is used for Behavior-Driven Development approach to write acceptance tests in a human-readable format. ### 2. **How does Cucumber enhance collaboration in software development?** diff --git a/versioned_docs/version-2.0.0/concepts/reference/glossary/end-to-end-testing.md b/versioned_docs/version-2.0.0/concepts/reference/glossary/end-to-end-testing.md index 04353ff4a..9f8d8b26e 100644 --- a/versioned_docs/version-2.0.0/concepts/reference/glossary/end-to-end-testing.md +++ b/versioned_docs/version-2.0.0/concepts/reference/glossary/end-to-end-testing.md @@ -10,9 +10,7 @@ keywords: - API --- -### What is end-to-end testing ? - -End-to-end testing or E2E testing is a software testing technique that verifies the functionality and performance of an entire software application from start to finish. This means that E2E tests simulate real-world user scenarios and replicate live data. The goal of E2E testing is to identify bugs that arise when all components are integrated, ensuring that the application delivers the expected output as a unified entity. +End-to-end testing or E2E testing is a testing technique that validates the functionality and performance of an entire software application from start to finish. This means that E2E tests simulate real-world user scenarios and replicate live data. The goal of E2E testing is to identify bugs that arise when all components are integrated, ensuring that the application delivers the expected output as a unified entity. E2E testing is typically performed by quality assurance (QA) teams, and are executed in dedicated test environments. This normally takes place after functional and system testing. End-to-end testing typically includes testing the following: @@ -62,3 +60,25 @@ Now, when the application starts: - Keploy will compare the API response to the previously captured response and a report will be generated on the Keploy console. Since you don't require to setup any test environment, Keploy can be used in any environment, be it local, staging, or production. Also, since the test cases are generated based on the real-time capturing of API calls from your application, they will be from real-world scenarios. + +## Conclusion + +End-to-end (E2E) testing is a important component of the software development process, as it ensures that applications function correctly and meet user expectations across all integrated components. While E2E testing presents challenges, such as time consumption and automation complexity, tools like Keploy offer powerful solutions to streamline the process. By capturing and replaying real-world API interactions, Keploy enhances the efficiency and effectiveness of end-to-end testing, contributing to the delivery of high-quality software. + +## FAQs + +### What is End-to-End Testing? + +End-to-end testing validates the complete functionality of a software application by simulating real-world scenarios and interactions from start to finish. + +### Why is End-to-End Testing Important? + +It ensures that all integrated components of an application work together as expected, helping to identify and fix bugs that might not be detected in isolated tests. + +### What Challenges are Associated with End-to-End Testing? + +Challenges include the time and cost involved, difficulty in automating tests, and creating comprehensive test cases that cover all possible scenarios. + +### How Does Keploy Simplify End-to-End Testing? + +Keploy simplifies E2E testing by recording API calls and generating test cases with built-in mocks or stubs. It provides a streamlined process for capturing and replaying real-world interactions, enhancing testing efficiency. diff --git a/versioned_docs/version-2.0.0/concepts/reference/glossary/software-testing-life-cycle.md b/versioned_docs/version-2.0.0/concepts/reference/glossary/software-testing-life-cycle.md index 5f6d58bfc..6ffe1864f 100644 --- a/versioned_docs/version-2.0.0/concepts/reference/glossary/software-testing-life-cycle.md +++ b/versioned_docs/version-2.0.0/concepts/reference/glossary/software-testing-life-cycle.md @@ -13,7 +13,7 @@ keywords: - testing --- -Software Testing Life Cycle (STLC) is a structured approach to testing software applications to ensure they meet quality standards, fulfill requirements, and perform reliably. This article explores the phases of STLC, common practices, and how tools like Keploy can enhance the testing process. +Software Testing Life Cycle, more commonly known as STLC, is a process to test software applications to ensure they meet quality standards, fulfill requirements, and perform as expected. STLC consists of several phases that guide the testing process from inception to completion, ensuring thorough testing and defect identification. ## What are the Phases of Software Testing Life Cycle (STLC) @@ -67,7 +67,7 @@ Software Testing Life Cycle (STLC) comprises several phases that guide the testi - **Risk-Based Testing**: Prioritize tests based on potential impact and likelihood of failure. - **Performance Testing**: Evaluate software performance under various conditions and loads. -## How Keploy Accelerates the Software Testing Life Cycle ? +## How Keploy helps in accelrating the Software Testing Life Cycle process? Keploy enhances the STLC with its advanced features tailored for modern software testing needs: diff --git a/versioned_docs/version-2.0.0/concepts/reference/glossary/white-box-testing.md b/versioned_docs/version-2.0.0/concepts/reference/glossary/white-box-testing.md index 4c93ea7f6..f32f0013a 100644 --- a/versioned_docs/version-2.0.0/concepts/reference/glossary/white-box-testing.md +++ b/versioned_docs/version-2.0.0/concepts/reference/glossary/white-box-testing.md @@ -1,8 +1,8 @@ --- id: white-box-testing -title: What is White Box Testing ? +title: Unlocking the Secrets of White Box Testing sidebar_label: White Box Testing -description: White box testing examines internal code structures for software integrity. Optimize performance, identify vulnerabilities, and ensure robust applications. +description: Discover the essentials of White Box Testing, including techniques, benefits, and practical examples. Learn how to optimize your testing strategy for better software quality. tags: - explanation - Glossary @@ -16,66 +16,69 @@ keywords: - black box testing techniques - black box testing - what is black box testing + - keploy --- -Whitebox testing is a software testing technique that examines the internal structures of a program or application, such as the code, internal logic, and data flow. This test happens when the tester understands how the system works inside and utilizes that understanding to create and run test scenarios. +## What is White Box Testing? -The primary goal of whitebox testing is to verify that the software performs as expected, that all expected pathways and situations have been verified, and that the code has been thoroughly optimized for speed and efficiency. +White box testing, also known as clear box or glass box testing, is a software testing technique that examines the internal structures of a program. It involves looking at the code, internal logic, and data flow to ensure the software behaves as expected. By understanding how the system works inside, testers can create and run more effective test scenarios. -![types of testing](../../../../../static/img/glossary/types-of-testing.jpeg) +## Why is White Box Testing Important? + +The primary goal of white box testing is to validate the software's internal operations, ensuring that it functions correctly and efficiently. This involves checking all pathways and conditions, optimizing code for speed and performance, and ensuring that there are no hidden errors. -## What are the Fundamentals of White Box Testing? +![types of testing](../../../../../static/img/glossary/types-of-testing.jpeg) -White box testing is a software testing technique that assesses the internal workings of an application. The primary goal is to validate the correctness of the code, ensuring that it behaves as expected and meets the specified requirements. +## Fundamentals of White Box Testing -**Key Objectives:** +White box testing is essential for verifying the correctness and efficiency of code. Here’s why it’s crucial: -- Identifying logical errors and coding mistakes -- Ensuring all code paths are executed -- Verifying the accuracy of calculations and data manipulation -- Assessing the quality of code structure and organization +- **Identify Logical Errors**: It helps in uncovering logical flaws in the code. +- **Ensure Path Coverage**: Every possible path through the code is tested. +- **Verify Calculations**: Ensures that calculations and data manipulations are correct. +- **Assess Code Quality**: Checks the structure and organization of the code for better maintainability. ![What is White box testing?](https://cdn.educba.com/academy/wp-content/uploads/2019/05/White-Box-Testing-1.jpg) -## Whitebox Testing Techniques +## Types of White Box Testing Techniques -whitebox testing techniques include: +White box testing involves various techniques to ensure comprehensive coverage: -1. **Statement coverage:** This method tests every code statement. This ensures all code statements are executed, and no dead code or inaccessible statements exist. -2. **Branch coverage:** Testing all code branches. It tests all conditional statements and considers all outcomes. -3. **Path coverage:** Testing all code pathways. It tests all potential inputs and circumstances. -4. **Condition coverage:** Testing all code conditions. -5. **Data flow coverage:** Testing data flow via code. It prevents data corruption, loss, and improper processing. -6. **Loop testing:** Testing programming loops. It helps prevent endless loops and other loop difficulties by executing loops the right number of times. -7. **Code reviews:** detect coding flaws, security vulnerabilities, and performance bottlenecks. +1. **Statement Coverage**: Ensures every line of code is executed. +2. **Branch Coverage**: Tests all possible paths, including if-else conditions. +3. **Path Coverage**: Ensures all potential paths in the code are tested. +4. **Condition Coverage**: Checks all logical conditions. +5. **Data Flow Coverage**: Tests the path of data through the code. +6. **Loop Testing**: Validates the functionality of loops. +7. **Code Reviews**: Detects flaws, security issues, and performance bottlenecks. -## Whitebox Testing Tools +## Tools for White Box Testing -Whitebox testing tools can help software developers and testers to automate testing and early detection of bugs. Some commonly used tools for whitebox testing include: +Using the right tools can streamline white box testing: -- **Code coverage tools**: These tools aid in measuring the testing suite's code coverage by determining which lines of code are run during testing. -- **Debuggers**: They assist developers in identifying and diagnosing code bugs by enabling them to walk through code and watch the program's behavior. -- **Static code analysis tools**: These tools analyze code without running it to find possible coding flaws, security vulnerabilities, and performance difficulties. -- **Profiling tools**: They aid in identifying performance bottlenecks in code by monitoring program execution and finding portions of code that use the most resources. -- **Frameworks for unit testing**: These tools assist in automating the testing of individual code units or modules, ensuring that each unit functions as intended. +- **Code Coverage Tools**: Measure how much of the code is covered by tests. +- **Debuggers**: Help in identifying and fixing bugs. +- **Static Code Analysis Tools**: Analyze code for potential issues without executing it. +- **Profiling Tools**: Identify performance issues by monitoring resource usage. +- **Unit Testing Frameworks**: Automate testing of individual units of code. ![White Box Testing](https://res.cloudinary.com/practicaldev/image/fetch/s--shG8HMmV--/c_limit%2Cf_auto%2Cfl_progressive%2Cq_66%2Cw_880/https://dev-to-uploads.s3.amazonaws.com/uploads/articles/f639sq6krordxspv1wxi.gif) -## What Challenges are in Whitebox Testing? +## Overcoming Challenges in White Box Testing ### 1. Expertise Required: -White box testing demands a deep understanding of the programming languages, algorithms, and data structures used in the application. Testers need to possess strong technical skills, making it challenging to find qualified professionals. +White box testing requires in-depth knowledge of programming languages, algorithms, and data structures, making it a task for skilled professionals. ### 2. Comprehensive Coverage: -Achieving comprehensive test coverage can be challenging, especially in large and complex software systems. Ensuring that all code paths are tested requires meticulous planning and execution. +Ensuring every code path is tested, especially in large systems, demands meticulous planning. ### 3. Maintenance Overhead: -As the codebase evolves, white box test cases may need frequent updates to align with the changes. This maintenance overhead can be time-consuming and requires synchronization with the development team's activities. +As code evolves, test cases must be updated, requiring ongoing coordination with development teams. -## Best Practices in White Box Testing: +## Best Practices for Effective White Box Testing 1. **Collaboration with Developers**: White box testing is most effective when testers collaborate closely with developers. This ensures a shared understanding of the codebase, facilitates knowledge transfer, and streamlines the identification and resolution of issues. @@ -86,21 +89,18 @@ As the codebase evolves, white box test cases may need frequent updates to align 3. **Test-Driven Development (TDD)**: Test-Driven Development encourages writing test cases before implementing the actual code. This approach ensures that the code meets the specified requirements and promotes a culture of continuous testing throughout the development process. -## Comparison of Black-Box Testing and WhiteBox Testing +### White Box Testing vs. Black Box Testing -| Black-box testing | Whitebox testing | -| ----------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------- | -| Does not require knowledge of the internal structure or implementation details of the software being tested | Requires knowledge of the internal structure or implementation details of the software being tested | -| Focuses on the software's external behavior and how it interacts with users | Focuses on the software's internal logic and how it works | -| Can be performed by testers with a variety of skill levels | Requires testers with specialized knowledge and skills | -| Can find a wide range of defects | Can find defects that are related to the software's internal logic | -| Can be used to verify the software's functionality, usability, and performance | Can be used to optimize performance, identify vulnerabilities, and ensure robust applications | - -Both whitebox and black-box testing are valuable software testing techniques, each with its own strengths and weaknesses. +| **Aspect** | **White Box Testing** | **Black Box Testing** | +| ---------------------- | ----------------------------------------------- | ----------------------------------------------------- | +| Knowledge Required | Internal structure and implementation details | No knowledge of internal structure | +| Focus | Internal logic and code behavior | External behavior and functionality | +| Skill Level | Requires specialized technical skills | Can be performed by testers with various skill levels | +| Types of Defects Found | Internal logic errors, security vulnerabilities | Functional, usability, and performance issues | -## **Whitebox testing with Keploy** +## How to perform Whitebox testing with Keploy ? -Install [Keploy](https://keploy.io/) and integrate it with your development setup. Keploy supports various platforms and CI tools like [GitHub CI](http://localhost:3000/docs/ci-cd/github/), [GitLab Runners](http://localhost:3000/docs/ci-cd/gitlab/), and [Jenkins Pipeline](http://localhost:3000/docs/ci-cd/jenkins/), making integration straightforward : - +Firstly, install [Keploy](https://keploy.io/), a testing tool that helps you automate the testing process. Here’s how you can perform white box testing with Keploy: - **Instrument Your Code:** Use Keploy’s instrumentation to capture interactions and internal processes. Keploy works at a kernel and network level, capturing data flows, API calls, and other internal interactions without modifying your application code. @@ -116,95 +116,73 @@ Install [Keploy](https://keploy.io/) and integrate it with your development setu ## Conclusion -The key differences between these approaches lie in the tester's knowledge, perspective, and focus. _Blackbox testing_ emphasizes external behavior and is suitable when internal code knowledge is not essential. _Whitebox testing_, on the other hand, dives into internal logic, making it indispensable for code optimization, security assessment, and uncovering potential vulnerabilities. Depending on project goals, a combination of both methodologies may be employed to ensure comprehensive and effective software testing throughout the development lifecycle. - -In general, whitebox testing is more effective at finding bugs, but it can be more time-consuming and expensive to implement. Black-box testing is less effective at finding bugs, but it can be faster and less expensive to implement. +White box testing is invaluable for uncovering hidden errors and optimizing performance. While it requires technical expertise, its thorough approach ensures robust, secure, and high-performing software. Combining white box testing with black box testing offers comprehensive coverage, enhancing the overall quality of your applications. ## FAQs ### What is white box testing? -White box testing is a software testing technique that examines the internal structures or workings of an application. The tester uses knowledge of the code and logic to design and execute tests. +White box testing examines the internal structures of an application, ensuring that the code behaves as expected and meets requirements. ### What are the primary goals of white box testing? -The primary goals are to: - -- Verify the correctness of the code. -- Ensure all code paths are executed. -- Check the accuracy of calculations and data manipulations. -- Assess the quality of code structure and organization. - -### What techniques are used in white box testing? - -Common techniques include: - -- **Statement coverage** -- **Branch coverage** -- **Path coverage** -- **Condition coverage** -- **Data flow coverage** -- **Loop testing** -- **Code reviews** +- Verify code correctness. +- Ensure all paths are executed. +- Check calculations and data manipulations. +- Assess code quality. ### What tools are commonly used in white box testing? -Common tools include: - -- **Code coverage tools** -- **Debuggers** -- **Static code analysis tools** -- **Profiling tools** -- **Unit testing frameworks** +- Code Coverage Tools +- Debuggers +- Static Code Analysis Tools +- Profiling Tools +- Unit Testing Frameworks ### What are the main challenges of white box testing? -The main challenges are: - -- Requires deep technical knowledge and expertise. -- Achieving comprehensive coverage is difficult. -- Maintenance overhead due to frequent updates needed as the code evolves. +- Requires technical expertise. +- Comprehensive coverage is difficult. +- High maintenance overhead. ### How does white box testing differ from black box testing? -| **Aspect** | **White Box Testing** | **Black Box Testing** | -| ---------------------- | ----------------------------------------------- | ----------------------------------------------------- | -| Knowledge Required | Internal structure and implementation details | No knowledge of internal structure | -| Focus | Internal logic and code behavior | External behavior and functionality | -| Skill Level | Requires specialized technical skills | Can be performed by testers with various skill levels | -| Types of Defects Found | Internal logic errors, security vulnerabilities | Functional, usability, and performance issues | +| **Aspect** | **White Box Testing** | **Black Box Testing** | +| -------------------------- | ----------------------------------------------- | ----------------------------------------------------- | +| **Knowledge Required** | Internal structure and implementation details | No knowledge of internal structure | +| **Focus** | Internal logic and code behavior | External behavior and functionality | +| **Skill Level** | Requires specialized technical skills | Can be performed by testers with various skill levels | +| **Types of Defects Found** | Internal logic errors, security vulnerabilities | Functional, usability, and performance issues | ### What are the benefits of white box testing? -- Provides thorough testing of code logic and pathways. -- Helps in identifying security vulnerabilities. -- Assists in optimizing performance and resource usage. -- Ensures all parts of the code are executed and tested. +- Thorough testing of logic and pathways. +- Identifies security vulnerabilities. +- Optimizes performance and resource usage. +- Ensures all code parts are tested. ### What are the limitations of white box testing? -- Can be time-consuming and expensive. -- Requires highly skilled testers. -- May not find issues related to the software's external behavior or usability. +- Time-consuming and expensive. +- Requires skilled testers. +- May not address external behavior or usability. ### When should white box testing be used? -White box testing should be used when: - -- Detailed knowledge of the internal workings of the software is available. -- There is a need to test the software's logic, security, and performance. -- Early detection of bugs during the development phase is crucial. +- When detailed internal knowledge is available. +- To test logic, security, and performance. +- For early bug detection during development. ### How can white box testing be made more effective? -- Collaborate closely with developers to understand the codebase. -- Use automated testing tools to increase efficiency and coverage. -- Implement Test-Driven Development (TDD) to write tests before coding. +- Collaborate with developers. +- Use automated tools. +- Implement Test-Driven Development (TDD). ### Can white box testing and black box testing be used together? -Yes, using both methods together provides comprehensive testing coverage. White box testing ensures the internal logic is correct, while black box testing verifies the software's functionality, usability, and performance from an end-user perspective. +Yes, combining both methods ensures comprehensive coverage, validating internal logic and external behavior. ### What is Test-Driven Development (TDD) and how does it relate to white box testing? -TDD is a development approach where test cases are written before the actual code. This ensures the code meets the specified requirements and promotes continuous testing. TDD aligns well with white box testing by emphasizing the importance of understanding the code's internal logic during test case creation. +TDD involves writing tests before code, ensuring requirements are met. It aligns with white box testing by emphasizing internal logic during test creation. diff --git a/versioned_docs/version-2.0.0/quickstart/python-flask-mongo-local.md b/versioned_docs/version-2.0.0/quickstart/python-flask-mongo-local.md deleted file mode 100644 index 399a9e253..000000000 --- a/versioned_docs/version-2.0.0/quickstart/python-flask-mongo-local.md +++ /dev/null @@ -1,171 +0,0 @@ ---- -id: samples-flask-local -title: Sample Student Data CRUD App (Flask) -sidebar_label: Flask + Mongo (Local) -description: The following sample app showcases how to use the Flask framework and the Keploy Platform. -tags: - - python - - quickstart - - samples - - examples - - tutorial - - python-framework - - mongodb - - flask-framework -keyword: - - Flask Framework - - MongoDB - - NoSQL - - Python - - API Test generator - - Auto case generation ---- - -# Introduction - -🪄 Dive into the world of Student CRUD Apps and see how seamlessly Keploy integrated with [Flask](https://flask.palletsprojects.com/en/3.0.x/) and [MongoDB](https://www.mongodb.com/). Buckle up, it's gonna be a fun ride! 🎢 - -import InstallationGuide from '../concepts/installation.md' - - - -## Get Started! 🎬 - -## Clone the sample flask-mongo application - -```bash -git clone https://github.com/keploy/samples-python.git && cd samples-python/flask-mongo-local -``` - -## Install all dependencies - -```bash -pip install -r requirements.txt -``` - -## Start the MongoDB server - -```bash -sudo service mongod start -``` - -## Setup Keploy - -Let's get started by setting up the Keploy alias with this command: - -```bash -curl --silent -O -L https://keploy.io/install.sh && source install.sh -``` - -You should see something like this: - -```bash - ▓██▓▄ - ▓▓▓▓██▓█▓▄ - ████████▓▒ - ▀▓▓███▄ ▄▄ ▄ ▌ - ▄▌▌▓▓████▄ ██ ▓█▀ ▄▌▀▄ ▓▓▌▄ ▓█ ▄▌▓▓▌▄ ▌▌ ▓ - ▓█████████▌▓▓ ██▓█▄ ▓█▄▓▓ ▐█▌ ██ ▓█ █▌ ██ █▌ █▓ - ▓▓▓▓▀▀▀▀▓▓▓▓▓▓▌ ██ █▓ ▓▌▄▄ ▐█▓▄▓█▀ █▓█ ▀█▄▄█▀ █▓█ - ▓▌ ▐█▌ █▌ - ▓ - -Keploy CLI - -Available Commands: - example Example to record and test via keploy - generate-config generate the keploy configuration file - record record the keploy testcases from the API calls - test run the recorded testcases and execute assertions - update Update Keploy - -Flags: - --debug Run in debug mode - -h, --help help for keploy - -v, --version version for keploy - -Use "keploy [command] --help" for more information about a command. -``` - -## Lights, Camera, Record! 🎥 - -To initiate the recording of API calls, execute this command in your terminal: - -```bash -keploy record -c "python3 app.py" -``` - -Now, your app will start running, and you have to make some API calls to generate the test cases!! - -1. **Make a POST request:** - -```bash -curl -X POST -H "Content-Type: application/json" -d '{"title":"Task 1","description":"Important task"}' http://localhost:5000/api/tasks -``` - -2. **Make a GET request:** - -```bash -curl http://localhost:5000/api/tasks -``` - -3. **Make a PUT request:** - -```bash -curl -X PUT -H "Content-Type: application/json" -d '{"title":"Task 1","description":"Random task"}' http://localhost:5000/api/tasks/12345 -``` - -4. **Make a DELETE request:** - -```bash -curl -X DELETE http://localhost:5000/api/tasks/12345 -``` - -And once you are done, you can stop the recording and give yourself a pat on the back! With that simple spell, you've conjured up a test case with a mock! Explore the **keploy** directory and you'll discover your handiwork in `tests` directory and `mocks.yml`. - -## Run the tests - -Now, it's time to put things to the test 🧪 - -```bash -keploy test -c "python3 app.py" --delay 10 -``` - -Now, you can also try different API calls, tweak the DB response in the mocks.yml, or fiddle with the request or response in test-x.yml. Run the tests again and see the magic unfold! - -## Check Test Coverage - -We have a `test-app.py` where all the unit test cases has been written. Now using Keploy, we can check it's code coverage!! -Now to run your unit tests with Keploy, you can run the command given below: - -```bash -python3 -m coverage run -p --data-file=.coverage.unit -m pytest -s test_keploy.py test_app.py -``` - -To combine the coverage from the unit tests, and Keploy's API tests we can use the command below: - -```bash -python3 -m coverage combine -``` - -Finally, to generate the coverage report for the test run, you can run: - -```bash -python3 -m coverage report -``` - -and if you want the coverage in an html file, you can run: - -```bash -python3 -m coverage html -``` - -## Wrapping it up 🎉 - -Congrats on the journey so far! You've seen Keploy's power, flexed your coding muscles, and had a bit of fun too! Now, go out there and keep exploring, innovating, and creating! Remember, with the right tools and a sprinkle of fun, anything's possible.😊🚀 - -Hope this helps you out, if you still have any questions, reach out to us . - -import GetSupport from '../concepts/support.md' - -