Understanding software testing methodologies, test types, and tooling options can help developers speed up testing cycles without sacrificing quality.
Practical software testing tools help developers automate repetitive tasks, streamline their workflow, and speed up release times.
Developing complex products demands vetted methods and processes to evaluate and verify if an app does what it should. Software testing acts as quality control and ensures customers and end users receive the best possible version of a product. Organizations rely on software testing to meet business objectives and deliver superior user experiences.
But for developers, software testing can be a prolonged process and frustrating bottleneck that drags down release time. Understanding software testing methodologies, test types, and tooling options can help developers speed up testing cycles without sacrificing quality.
Software testing is the organizational process within the software development life cycle where teams verify software for quality and performance. Software testing evaluates and confirms that a product or application performs as desired.
There are two main software test categories: manual and automated. Manual tests are when a human manually tests a software application to identify bugs or uncover underlying issues. Manual tests can deliver invaluable insight into a product but are also susceptible to human error, time-consuming, expensive, and typically cannot be reused.
Automated tests use outside software programs or apps to automatically control text execution and assess actual and predicted outcomes without human intervention. Today, most agile and DevOps teams use automated testing in the SDLC because automated testing is faster, more likely to be accurate, and more efficient than human-led testing.
Both manual and automated software testing aim to ensure a product or app delivers accuracy, quality, and stability.
Software testing helps to prevent bugs, keeps development costs down, and improves the final product or application performance. Customers and organizations benefit immensely from software testing in four crucial areas:
Customer satisfaction and confidence through reliable experiences nurture long-term customer relationships.
Enhanced security builds trust and reduces the risk of critical failures.
Cost savings by finding issues before they are released, avoiding unexpected hotfixes and customer service nightmares.
A streamlined development pipeline for consistent feature releases and positive developer experience.
Software testing is the key to releasing high-quality, high-performing products and apps people are delighted to use.
Development teams employ various software testing methodologies to ensure that an application behaves and looks as expected. Based on the tester's knowledge of the source code and backend of the application, software testing is grouped into three boxes: black, gray, and white. The color of the boxes indicates the level of transparency the tester has with the application.
Black box testing, or closed box testing, tests the functionality of an application without the tester knowing the inner architecture. Black box testing happens at every level of the software testing pyramid, from unit tests to acceptance tests. Black box testing is sometimes called specification-based or closed box testing and is performed by end-users and testers.
As the opposite of black box testing, white box testing, or open box testing, the testers have complete knowledge of the application's internal workings. Performed by developers and testers, this testing investigates the internal structure and logic of the code. Because of this, white box testing is the most time-consuming. This testing methodology verifies the flow of inputs and outputs within a product and can help to improve an app’s usability, design, and security. White box testing is also referred to as code-based testing, glass box testing, or structural testing.
When you mix these two software testing methodologies, you get the third variation called gray box testing. A combination of white box testing and black box testing, gray box testing includes testers with limited knowledge of the application's internal workings. Typically a gray box tester has access to the design documents and the database, unlike a black box tester who tests only the application's user interface. Gray box testing uncovers bugs, errors, and defects caused by an incorrect structure or incorrect usage of applications.
All three software testing methods examine and verify an app's or software's inner workings and functionality in varying depths.
Software testing types range in complexity based on their goal and metrics. But, when viewed as a whole, all software tests are designed to test the quality and performance of an application or product, uncover issues, and ultimately improve the final user experience.
Unit tests sit at the bottom of the software testing pyramid because they are closest to the code. A unit test examines a single unit of code or the smallest piece of code isolated within a system. Unit tests can be a function, subroutine, property, or method. Due to their simplicity and limited variables, unit tests are fast with minimal setup. For applications with hundreds and thousands of unit tests, unit test inefficiencies can bottleneck testing cycle times.
Integration testing is intended to ensure integrated modules work as expected and evaluates the compliance of the integration based on specified functional requirements. Integration tests help ensure all critical components work together. Integration tests, by nature, take longer due to the increased variables and can drain developer resources due to their complexity.
With the focus on testing the readiness of a system, performance tests are considered non-functional testing that shows how the software performs under different workloads. Load testing measures the system performance as workload increases, whereas stress testing measures performance outside typical working conditions. These tests assess the scalability and flag inefficient resources or configuration issues.
While the previous test types focus on a portion of the software, end-to-end testing verifies every component of the system runs as intended in real-world scenarios. As the name implies. End-to-end testing means testing the entire app from start to finish, including all of the dependencies. E2E tests are critical but also the most resource-intensive and time-consuming.
Also known as application tests or end-user tests, user acceptance tests (UAT) are the last phase in the software testing process where the actual software users test to confirm the product meets specifications. Different types of UATs include alpha testing, beta testing, operational acceptance testing, prototype testing, contract, and regulation acceptance testing, and factory acceptance testing. User acceptance testing ensures business requirements are met and the software behaves precisely as anticipated.
Smoke tests reveal simple failures that could sabotage a release through minimal tests. Smoke tests focus on an app's main functionality and determine if the software's most essential functions work correctly. Sometimes called confidence or build verification tests, these tests rapidly confirm whether the software is ready for testing, so teams don’t waste resources and time testing a flawed build.
Despite testing at every phase of the SDLC, regression tests are necessary to ensure new features and code changes do not harm existing functionality. Regression tests re-run cleared test cases against the latest version to verify the app's functionality works as intended. To stay competitive, organizations release new features, but the more you release new features, the more often the testing has to be re-evaluated. Teams often choose which regression tests are critical to run case-by-case, increasing the risk to releases to save time and expense.
All software testing types intend to support higher quality products, but some cause more of a bottleneck than others. Developers and quality assurance engineers rely on tools to ensure testing is reliable and repeatable and are implementing more intelligent testing practices to reduce software testing bottlenecks for faster, more dependable releases.
Testing is a significant part of developer experience. Releasing bug-free well-performing products means developers don’t have to deal with hot fixes or customer service crises. Unfortunately, testing is one of the biggest problems developers face, whether it’s not having enough tests or having too many tests.
That’s where software testing tools come into play. Practical software testing tools help developers automate repetitive tasks, streamline their workflow, and speed up release times. The top software testing tools available today include:
Selenium - A free, open-source set of tools and libraries that support browser automation. This automated testing framework validates web applications across multiple browsers and platforms.
Launchable - Our Predictive Test Selection harnesses an ML model to identify the most critical tests to run to seriously reduce testing cycle times. Launchable slashes test suite size by streamlining the number of tests you run on applications during development and speeds up your entire CI/CD pipeline.
Katalon - A test automation solution that generates, executes, and orchestrates web, API, mobile, and desktop application test automation.
TestComplete - An easy-to-use functional automated testing platform that handles all test automation needs in various languages.
Unified Functional Tester - Software that provides functional and regression test automation for software applications and environments. UFT supports keyword and scripting interfaces and features a graphical user interface.
Additional Resources: Continuous Delivery Tools for Rapid Software Development Cycles
Software testing is critical, but slow testing cycles are the biggest (and most annoying!) bottleneck in the software development life cycle. Slow test cycles halt workflows and drag down developer happiness and productivity. Smarter testing is the only way teams can genuinely speed up bloated test suites.
As the first dev intelligence platform, Launchable helps teams improve testing and push more commits with a truly data-driven pipeline. Launchable’s Predictive Test Selection identifies and runs tests with the highest probability of failing, based on your code and test metadata, with the goal of a faster dev feedback loop.
Launchable predicts the likelihood of failure for each test based on past runs and the source code changes being tested. This allows developers to run a dynamically selected subset of tests that are likely to fail, reducing a long-running test suite to mere minutes.
Beyond slashing test cycle times, Predictive Test Selection works with existing test selection strategies, including cloud-native, embedded, mobile, and traditional applications. It’s also language agnostic and compliant, which means Launchable works with all programming languages and frameworks and does not require any storing of code. Predictive Test Selection can be deployed across different parts of the software testing pyramid to speed up the entire testing cycle from soup to nuts.
Launchable also helps teams measure and track the health of their tests with Test Suite Insights. Understanding the pain points caused by testing bottlenecks and measuring the health of your test suite over time nurtures positive developer experience.
Developers can measure test suite entropy by speeding up test times through Launchable’s Test Suite Insights. Connect the dots between your failed tests and how they’re affecting your velocity with the following insights:
Flaky test insights - find the top flaky tests in a test suite, so developers can prioritize fixing the right tests first.
Test session duration insights - highlight increases in test session time to display upward trending developer cycle times.
Test session frequency insights - uncover which tests run less often, have increased cycle times, or reduced quality.
Test session failure ratio insights - identify the tests failing more often to see if a release is becoming unstable.
Nurture better developer experience with data and make your testing process faster through smart testing automation. Help your engineers experience quicker testing cycles without sacrificing quality.
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