Everything You Need to Know about the Software Testing Life Cycle
Speed up your software testing lifecycle by addressing bloated test suites and long test run times.
Key Takeaways
The software testing life cycle is a proven testing strategy DevOps teams use to test software and achieve quality goals and standards.
Teams often find bloated test suites and long testing cycles to be common themes hampering their software testing velocity.
DevOps teams are maturing their software testing life cycles with machine learning models for smarter testing.
Software development consists of multiple phases, with testing being one of the most essential and biggest bottlenecks. What is the point of releasing software if it doesn’t function as designed or has a broken user experience? There's more to software testing than ensuring an application works and looks slick. Before software launches, Quality Assurance rules out issues. This workflow is known as the software testing life cycle.
The software testing life cycle (STLC) is a proven testing strategy DevOps teams use to test software and achieve quality goals and standards.
The software testing life cycle was designed to standardize and speed up the testing process and helps teams uncover and fix flaws, errors, or failures before release. Organizations use this process to craft practical testing plans that make tracking project progress easier and knock product and business goals out of the park.
STLC vs. SDLC: What’s the difference?
The software development life cycle (SDLC) helps teams to create and develop new software and apps efficiently. The SDLC incorporates planning, building, testing, and eventually deploying an app. The SDLC is responsible for procuring requirements and developing features.
On the other hand, the software testing life cycle (STLC) helps teams test the software, find flaws, and meet quality standards. The STLC includes strategizing, planning, executing, and completing all required software tests throughout a project’s development. Responsible for creating tests adapted to the collected requirements, the STLC verifies features meet those requirements.
Both processes are critical to developing high-quality, error-free software that delivers on claims for users and achieves performance goals.
The Six Software Testing Life Cycle (STLC) Phases
The software testing life cycle gives teams a systematic approach to testing. There are six phases in the software testing life cycle, and each step has defined entry and exit criteria. Deliverables and activities for each phase set expectations for actions and results. While some of these phases can run simultaneously, others must be completed before proceeding to the next stage.
The six STLC phases allow testers to discover requirements and prep test scenarios that will enable them to shift left and speed up their testing velocity.
Requirement Analysis
During this initial stage of the software testing life cSTycle, developers study the requirements of the test and determine the Entry Criteria (also known as the Entry Requirements), which are the items they must complete before testing begins. Requirement analysis entry criteria include three key components:
Requirements document for both functional and non-functional elements
Acceptance criteria
Application architecture document
Meanwhile, the QA team communicates with stakeholders to understand functional or non-functional requirements in detail. In this early stage, teams will identify the types of tests to perform, procure details about testing priorities, create the Requirement Traceability Matrix (RTM), and identify critical test environment details needed for tests to function currently. Automation feasibility analysis can also happen during Requirement Analysis.
Test planning
The second stage of the software testing life cycle focuses on strategizing and planning tests. Test team roles, tools, environment, limitations, requirements, and the testing schedule go into a test plan, along with projected labor, time, and costs. A test plan document is finalized and approved. This test plan serves as the blueprint throughout the project.
Test case development
In order to test software accurately, teams need to create test cases which include documentation on specific inputs, pre-conditions, test execution steps, and the expected test result. A manual test is one that is performed by individuals without the help of tools or scripts. Test automation, on the other hand, involves using software, scripts, and tools to execute test cases. Development teams will generate the needed test cases and automation scripts, review and reconfigure them as needed, and then create the test data in the test case development phase.
Test environment setup
The test environment setup stage is critical to the success of the software testing life cycle. During this phase, teams define the product testing software and hardware conditions. Developers must also prepare a hardware and software requirement list for the test environment, set up the test environment and data, and perform a smoke test on the build.
Test execution
In the second to STLC last phase, it’s time to execute the planned tests and document the test results, including defects, errors, and failed cases. With flaws uncovered, teams must map the defects in the Requirement Traceability Matrix (RTM), retest to fix defects, and ultimately solve any underlying issues.
Test cycle closure
We’ve reached the end of the software testing life cycle. In the final stage, testing teams draft and sign off on a test closure report. Team members assess the performance, metrics, and results of tests. They also analyze testing artifacts and discuss options to create a faster, more streamlined, and more efficient testing process in the future. Exit criteria are met, all planned tests are executed, and all defects are logged and handled.
Finding solutions to testing bottlenecks is the crux of the test cycle closure stage. Assessing how well they executed testing, teams often find bloated test suites and long testing cycles to be common themes hampering their software testing velocity.
What are the benefits and limitations of the software testing life cycle?
The software testing life cycle helps to define the goals and expectations of a project. By pre-defining plans for a new feature, developers can more easily track their progress on a project and uncover any slow, troublesome points in the workflow. Creating clear goals for the final testing outcomes with the STLC helps keep DevOps teams on track and delivering on time.
Through the STLC requirement analysis, development teams can identify testable requirements. Developers create an architecture for testing and supporting key stakeholders (i.e., QA) to understand the functional and non-functional requirements. The software testing life cycle also confirms features pass requirements before moving on to the next test. It gives guidelines and establishes a process to ensure all specified requirements of a release are achieved during the development process and discover (and then fix) errors.
DevOps teams are able to define their processes and introduce consistency into a workflow, allowing them to create higher quality products free from errors that deliver great experiences to clients and users alike.
The software testing life cycle puts guardrails in place for a project with deadlines. It helps create practical time constraints on projects by planning and sticking to the desired testing schedule. In a perfect world, the software testing life cycle runs as expected without any delays – but unfortunately that is not often the case. DevOps teams big and small face the common friction points within their STLC - bloated test suites that cause longer test runs and lengthen the testing cycle time substantially.
Although the software testing life cycle gives structure and process, allowing for predictable, faster releases, it cannot solve all the testing bottleneck burdens teams face.
Faster Software Testing Life Cycles with Predictive Test Selection
Developers understand that software testing is critical to the success of any project or app. But testing is also the most significant bottleneck that delays release times.
Running tests for every change stacks up the hours spent running an entire test suite. Testing for every change also delays the feedback developers need to move forward. How are teams speeding up their software testing life cycle?
DevOps teams are maturing their software testing life cycles with machine learning models for smarter testing.
Launchable’s Predictive Test Selection was made by developers, for developers because we hate getting bogged down in slow testing cycles too. Predictive Test Selection uses machine learning to choose the highest value tests to run for a specific change. By automating which tests to run for a given code change based on their expected value, you cut test suite size and time without sacrificing quality.
Using your own testing data, you can identify and run tests with the highest probability of failing, based on code and test metadata, to speed up the dev feedback loop. On each change, Launchable ranks tests by importance to code changes and allows devs to create a unique subset, based on this ranking, in real-time. That means only a fraction of a test suite needs to be run - but ensures failures or errors will also always be found by devs.
