Testing approaches refer to the strategies and methodologies adopted to conduct software testing activities
Smoke Testing: It is a type of testing performed to quickly assess whether the basic functionalities of an application are working as expected after a build or deployment. It is often performed before conducting more detailed testing. Smoke testing is part of the functional testing category.
Sanity Testing: It is a type of testing performed to determine whether the system is stable enough for further testing. Sanity testing focuses on a subset of functionalities or areas that are most likely to be affected by recent changes. It is part of the functional testing category.
Monkey Testing: It is a type of testing where the application or system is tested randomly, using inputs that are not necessarily based on any specific test cases. The purpose of monkey testing is to explore how the application behaves under unpredictable or random user actions. Monkey testing is part of the exploratory testing category.
Gorilla Testing: It is a type of testing that focuses on thoroughly testing specific functionalities or modules of an application, often with heavy data or load. Gorilla testing is performed to ensure that critical or high-risk components of the system are working as expected. It is part of the functional testing category.
Opaque Testing: Opaque testing is not a commonly used term in the testing domain. It may refer to a specific approach or technique that is not widely recognized. Without more context, it is difficult to associate it with a specific type of testing.
Ad hoc Testing: It is a type of testing performed without any specific test plans or predefined test cases. It involves exploring the application or system in an unplanned and spontaneous manner to find defects or issues. Ad hoc testing is part of the exploratory testing category.
Exploratory Testing: It is a testing approach where testers explore and investigate the application or system while simultaneously designing and executing test cases. Exploratory testing focuses on learning, understanding, and uncovering issues in an iterative and flexible manner. It is part of the testing approach rather than a distinct category.
Alpha Testing and Beta Testing: Alpha testing is performed by the internal development team to identify defects and issues before releasing the software to a limited group of external users for beta testing. Beta testing helps gather user feedback and real-world usage data.
Model-Based Testing: This approach utilizes models, such as flowcharts or state diagrams, to derive test cases systematically. It helps ensure comprehensive test coverage based on the application’s behavior specifications.
Compatibility Testing: This approach verifies the application’s compatibility across different devices, browsers, operating systems, and network environments. It ensures that the application works as expected on various platforms.
Backward Compatibility Testing: Backward compatibility testing validates that a new version of the software remains compatible with older versions, data formats, and interfaces. It ensures that existing functionality continues to work correctly after software updates or migrations.
A/B Testing: A/B testing, also known as split testing, involves comparing two or more versions of an application or webpage to determine which version performs better in terms of user engagement, conversion rates, or other metrics. It helps make data-driven decisions and optimize the user experience.
Compliance Testing: Compliance testing ensures that the application adheres to specific standards, regulations, or legal requirements relevant to the industry or domain. It verifies that the software meets the necessary compliance criteria.
Interoperability Testing: Interoperability testing verifies the application’s ability to interact and function correctly with other systems, interfaces, or third-party components. It ensures that the application can communicate, exchange data, and operate seamlessly in a heterogeneous environment.
Globalization Testing: Globalization testing validates the application’s ability to adapt to different cultures, languages, and regional settings. It ensures that the application can handle internationalization features, such as date formats, character encodings, and language translations.
Localization Testing: Localization testing checks whether the application is culturally and linguistically appropriate for the target audience in different regions or countries. It ensures that the application is adapted to specific locales, languages, and cultural preferences.
Accessibility Testing: Accessibility testing assesses whether the application is accessible to users with disabilities. It ensures compliance with accessibility standards and regulations to make the application inclusive to all users.
Installation Testing: This approach validates the installation and uninstallation processes of the application, ensuring that they are smooth and do not cause conflicts with the system or other applications.
Risk-Based Testing: Risk-based testing focuses on prioritizing tests based on the identified risks and their potential impact on the system. It involves analyzing the project’s risks and allocating testing efforts to areas that pose higher risks.
Model-Based Testing: Model-based testing utilizes models or diagrams to derive test cases systematically. The models, such as state transition diagrams or decision tables, are used to generate test inputs and expected outputs, improving test coverage and efficiency.
Usability Testing: Usability testing evaluates the application’s user-friendliness, intuitiveness, and overall user experience. It involves observing users performing tasks and collecting feedback to identify usability issues and areas for improvement.
Mutation Testing: Mutation testing involves introducing intentional defects, known as mutants, into the application’s source code. It assesses the effectiveness of the test suite by checking if the mutants are detected and killed, indicating the quality and thoroughness of the tests.
Recovery Testing: Recovery testing is performed to assess how well the application recovers from failures or disruptions, such as system crashes, network outages, or power failures. It tests the application’s resilience and its ability to restore data and functionality after such events.
Performance Testing: This approach is used to evaluate the system’s performance under different conditions, such as load, stress, and scalability. Performance testing ensures that the application can handle the expected user load without performance degradation.
Stress Testing: Stress testing evaluates the application’s performance and stability under extreme or peak load conditions. It checks how the system handles high volumes of concurrent users, data, or transactions.
Concurrency Testing: Concurrency testing verifies the application’s behavior and performance when multiple users or processes access and manipulate shared resources simultaneously. It helps identify any issues related to concurrency control and data consistency.
Scalability Testing: Scalability testing assesses the application’s ability to handle increased workload and user demand as the system’s size or complexity grows. It ensures that the application can scale effectively without significant performance degradation.
Volume Testing: Volume testing focuses on testing the application’s performance and behavior when dealing with a large volume of data. It verifies that the application can handle a significant amount of data without performance degradation or data corruption.
Endurance Testing: Endurance testing, also known as longevity testing, checks the application’s performance and stability over an extended period. It evaluates how the system behaves under sustained load or continuous operation to identify any performance degradation or resource leaks.
Each testing approach serves a specific purpose and complements other testing methods in a comprehensive software testing strategy. Depending on the project’s needs and objectives, multiple testing approaches can be combined to achieve higher test coverage and deliver a high-quality product.