Charting the optimal path for your team's software testing strategy can be confusing when navigating the many types of software tests.
Static software tests check for defects, verifying without executing the code while dynamic software tests validate software with code execution.
Functional software tests establish if the features of an app or program works as they are supposed to, per the software requirements. Functional tests include unit, integration, system testing, and acceptance testing.
Non-functional software tests assess the specifications that may not be crucial to an app’s functionality but contribute greatly to the end-user experience.
Software testing aims to eliminate bugs and advance your overall product with user experience, performance, and security. Quality testing strategies lead to better user experience AND developer experience.
Delivering error-free software requires a killer testing strategy. But how do you know what types of software tests to include to make a top-tier strategy? Understanding the ins and outs of software test types is the primer to building the testing strategy for your team.
We’ve mapped out a complete blueprint for the many types of software tests and broken out common test categories to explore each key element.
Charting the optimal path for your team's software testing strategy can be confusing when navigating the many types of software tests. Understanding test categories and the types of software tests that fall into each category can help you build and execute the best software testing life cycle for your specific organization’s needs.
Within the overall hierarchy of software testing, there are some key categories to understand. At a high level are static and dynamic tests and functional and non-functional tests. Within these categories are types of software tests that help verify and validate based on where in the software testing life cycle they are.
To verify or to validate? That is the question. When understanding the differences between static and dynamic software tests, we can differentiate them based on code execution.
Static software tests check for defects, verifying without executing the code. Static testing helps to identify errors or flaws during the earlier stages of development so problems are resolved quickly. Static testing is also helpful in uncovering issues not found during dynamic software testing. Typical static tests include Informal reviews, technical reviews, walkthroughs and inspections. Static tests come in both manual and automated variations.
Dynamic software tests validate software with code execution. In dynamic testing, you test and analyze the physical response from the system to fluctuating variables. It helps to highlight weak areas in a program or software’s environment. Performed at all levels of testing, dynamic tests confirm your product functions in alignment with business requirements.
Dynamic software tests include both functional and non-functional software tests. Functional software testing seeks to establish if the features of an app or program works as they are supposed to, per the software requirements. These requirements are specifically those that an end user would demand when using an app or a program. Functionalities are a form of input given to the system (i.e. the grocery store need-to-buys), the operation performed, and then the expected output.
Functional software tests include unit testing, integration testing, system testing, and acceptance testing.
A unit test is a single unit of code isolated from the system. Unit tests can be a function, subroutine, property, or method and are typically performed quickly, as they require minimal setup. Due to the close relationship between unit tests and the software they test, the tooling you use to build your software, like Maven or Gradle, is also used to run your unit tests. Unit tests are easy to write and run by their nature.
Unit tests fall into the category of white-box testing, a type of software testing that
tests the internal structures of an app, like the code, integrations, and design. White-box testing verifies the flow of inputs and outputs within a product and boosts user-friendliness, design, and security.
Integration testing evaluates the compliance of a system, feature, or component with specified functional requirements. Integration tests aim to make sure all key components work together, and are performed when single modules are combined and group-tested.
Integration testing is a form of gray-box testing, which tests both the internal architecture and functionality of an app. Its purpose is to hunt down the bugs, errors, and defects caused by a problematic structure or incorrect usage of applications. Gray-box testing is a combo of white-box testing and black-box testing, or testing a system with no previous knowledge of the internal functioning.
The third category of functional software testing is system testing. System testing is performed on a complete integrated system and evaluates the overall compliance of the system with different requirements. In system testing, integration testing passed components are used as inputs. There are three types of system testing:
↔️ End-to-end tests (E2E tests) verify that the components of a system perform at peak levels in real world scenarios. End-to-end testing requires testing an app from start to finish, to see if it responds and performs as promised.
🗳️ Black-box tests, or closed-box tests, examine the functionality of an application without exploring any inner framework. Black-box testing is used throughout the software testing pyramid.
😊 Happy path tests are tightly scripted and use known inputs to produce an expected output. Happy path testing verifies only that the required functionality performs correctly. Also known as the most likely and positive alternative, provided there are no errors.
Finally, one more kind of functional testing is acceptance testing. Acceptance testing can also be thought of as an example scenario for how a product functions. Frequently, the goal of acceptance testing is to automate the tests, through a great tool. Acceptance tests are typically one of two options: pass or fail.
💨 Smoke tests are a subset of acceptance tests that reveal any failures that could ultimately derail a release. Smoke tests are all about testing if the essential functions of an app are in order and performed as needed. A software build must undergo smoke testing before automated test cases can be executed. Those organizations with continuous testing built in can perform smoke testing and confirm the build's successful installation to conduct the first test case. Automated smoke tests will help you run tests faster and get feedback quickly so you can fix them immediately if you haven't already.
Non-functional software testing assesses the specifications that may not be crucial to an app’s functionality but contribute greatly to the end-user experience.
Another way to think about non-functional software testing is it’s all about testing the way a system operates and what makes or breaks a user experience. There are four common kinds of non-functional software tests - performance, security, usability, and compatibility.
Performance testing is designed to show how a software program or app will perform under different workloads. Performance tests are designed to assess speed, scalability, and stability. There are three common performance tests, including load testing, stress testing, and stability testing.
🪨 Load tests determine a system’s behavior under normal and peak load conditions. During load testing, the load is constantly and steadily increasing upon the system, until the system reaches its maximum or threshold limit.
💦 Stress tests assess the stability and reliability of software applications by testing the program under extremely heavy load conditions. The ultimate goal of stress testing? Ensure the software doesn’t crash.
⌛ Stability tests measure the efficiency of a software application to continuously function over a long period of time. Stability testing checks if a software application will crash or fail during normal usage.
Security testing uncovers the vulnerabilities of a system and determines if an app will be protected from potential threats and probable risks. Security tests can include static code analysis, compliance assessments, and penetration testing to assess vulnerabilities and stanch weaknesses before release.
Focused on measuring an app's functionality, usability tests include the assessment from real users engaging and using a program. In a similar vein, cross-browser testing checks if an app works as it’s supposed to for users, across different devices and browsers.
Compatibility testing determines if a system functions properly on different hardware, systems, environments, apps, and mobile devices. There are two kinds of compatibility testing, backwards compatibility testing and forward compatibility testing.
⬅️ Backward Compatibility Testing assesses the behavior and compatibility of developed hardware and software against the older versions.
➡️ Forward Compatibility Testing assesses the behavior and compatibility of developed hardware or software against the newer versions of that same hardware or software.
In a perfect world, code releases would never have issues, but releasing code changes can cause unexpected problems to existing functionality. Regression tests round out the testing blueprint as it evaluates code changes after release.
Testing strategies are incomplete without regression tests. Functional tests verify whether new features work as intended, but they test these inside a vacuum. By simulating how a component functions in real software in the real world, regression tests solve the problem of compatibility between changes and new features. Customer satisfaction relies on regressions tests that release features without breaking the old ones.
🔎 Sanity tests are regression tests used in quality assurance to check that bugs are fixed after the build. Sanity tests save organizations time and money; the software product is rejected if they fail. Sanity tests run after smoke tests have passed, and the QA team has approved further testing.
Software testing is critical to developing and releasing an amazing, high-performing product that’s useful and enjoyable for users. Unfortunately, software testing is all too often the biggest bottleneck to the STLC and releasing a project.
To speed up test cycle times, developers need to make their tests data-driven - allowing them to choose the right tests to run based on code changes and slash overall test suite run times and useless tests.
Launchable is helping developers and quality assurance teams automate their tests selection and monitoring with Predictive Test Selection. Using your test suite data Predictive Test Selection identifies and runs tests with the highest probability of failing, based on code and test metadata. Developers can run fewer tests and rest assured errors will always be found. With each change, Launchable ranks tests by importance, so developers can create a unique subset, based on the importance of code ranking.
Launchable also knows that test suite entropy is a bottleneck that backs up testing velocity and risks quality. Get insights into your test trends and enjoy reliable tests. Flag the top flaky tests in your suite so you have confidence in your test cases with Flaky Tests Insights. Track any increase in test session duration to identify if developer cycle time is trending upward. Flag which tests are being run less frequently and have visibility on the tests that are failing to fix issues within your testing pipeline before they cause problems.
Language agnostic, Launchable is a good fit for all types of software tests:
✔️ Shorten test feedback delay during pull requests by running tests that are likely to fail, first.
✔️ Subset long-running integration tests and UI suite and shift left to earlier in your development cycle.
✔️ Using canary deployment? Shift tests that are unlikely to fail post-deploy.
From unit tests to integration tests and all the way to regression tests, Launchable cuts test times, boosts release times, and sparks joy and productivity during developer work days.
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