STLC stands for Software Testing Life Cycle. STLC is a testing strategy performed by the testing team ensuring software quality standards are met. STLC is not to be confused with (SDLC) Software Development Life Cycle. SDLC embodies all software development phases while the software testing life cycle only focuses on the test phases.
Ivan Gekht, CEO of Gehsoft concurs by stating, “STLC is a step-by-step approach to testing, where QA, throughout a sequence of predefined steps, ensures the quality of the product.” Casey Jordan CTO and Co-Founder of easyDITA explains, “The best organizations integrate testing with development in ways that reduce time to market, improve quality, and ensure features meet customer needs.”
This guide will explore the definition of software testing life cycle (STLC,) the differences between STLC & SDLC, hear from expert practitioners in the industry, and learn of automated software testing tools that foster productivity.
There are differences between STLC and SDLC. The main difference is, Software Testing Life Cycle is a subset of the Software Development Life Cycle. Whereas, SDLC embodies the entire software creation process- from concept to completion. Testing software is a vital part of software creation. Therefore, STLC is a set of processes in the testable portions of creating software. “STLC is most concerned with how a feature works and less about how a feature is built,” adds Casey Jordan of easyDITA.
Andrei Mikhailau, Software Testing Director at ScienceSoft elaborates, “As STLC is an inseparable part of SDLC aimed at software quality, each STLC stage should result in deliverables valuable for the SDLC process. STLC is aimed at ensuring the quality of developed software and its full compliance with the requirements specification. STLC comprises QA and testing practices (test planning, functional, integration, compatibility, performance, security, usability, regression test cases development & execution, and performing exploratory testing.)”
There are six major phases in the software testing life cycle (STLC model.)
Naomi Bishop, CEO of Surfky/Bidwise, defines the requirements analysis phase as, “Analyze and research the criteria during this phase of the STLC. Participate in brainstorming sessions with other departments to determine if the criteria are testable. This stage aids in determining the extent of the research. If a function cannot be checked, let the team know during this process so that a mitigation plan can be formulated.” The QA team’s interaction with various key stakeholders is crucial at this stage.
Responsible QA team members collaborate with stakeholders. Any unclear aspects can be remedied here. We recommend the potential to automate testing capabilities. Automation testing tools such as Autify can be introduced. For example, we use our own test automation software to automatically test our product at this phase.
After the quality assurance team completes the requirements analysis stage they can move to the test planning phase. In this stage, a test plan document is created which acts as a strategic blueprint for testing. It details time and cost estimations, resources required, responsibilities delegation, and determining testing environments.
Naomi Bishop explains, “Test preparation is the first phase of the research process in most cases. We define the tasks and services that will aid in meeting the research goals during this process. We also aim to define the measures, as well as the way of collecting and monitoring those metrics, throughout the planning process.”
Test cases are created during this phase. These tests check that every portion of the software works as intended for the end-user.
A test case includes test steps, testing data (such as login details,) an expected result upon successful execution, as well as unexpected results if there are failures. QA teams should strive for test case efficiencies as well. Traditionally, it has been known for QA teams to document test cases in spreadsheets, but this can be rather cumbersome especially at scale.
To reach 100% coverage, test scripts should be a mixture of manual and automated scenarios. The latter should dominate where possible. QA teams with the majority of manual testing experience bottlenecks, inefficient costs due to more time spent manually testing, and the potential for more bugs slipping into production due to the human error element.
Traditionally, test scripts are written in programming languages by skilled developers. This raises the barrier for entry, meaning, not everyone on the QA team can execute the tasks. Our software, Autify, makes testing easy for anyone on the team using our GUI rather than coding. Instead of writing test scripts in a programming language, our codeless platform writes the coded steps for users. Therefore, a tester would only need to focus on interaction with the browser. Engineers can focus on coding new features. Autify’s machine learning algorithms also handle maintenance too.
Test environments are set up and deployed at this phase. This includes determining test data, hardware, and software implementation. Testing tools such as Autify, Selenium, or other top software testing tools are used to aid in automation testing. It is vital that the testing environment closely emulates the software after deployment. For example, if a membership web application runs on the client’s server, then the testing environment should closely match. It’s common to perform smoke testing at this phase.
In the test execution phase, testers carry out the strategy outlined in the test plan, by executing test cases. The expected results are compared to actual results and reported back to the development team. Implementing sufficient bug tracking, defect reports, and test execution reports are key. When using an automation testing tool such as Autify, the AI automatically gathers reporting showing passed and failed test scenarios. It can also save mountains of time (which are cost savings in software development) by detecting changes that may occur in the user interface.
The test cycle closure phase should conclude test execution. In essence, it’s a collection of test reporting results that should be presented, discussed, and analyzed among team members.
Naomi Bishop shares test cycle closure experiences from her team, ”[First,] verify that the evaluation has been done. If all test cases are executed or purposely mitigated. Verify that no defects of severity 1 have been opened.” She continues, ”[Second,] conduct a lesson-learned conference and prepare a lesson-learned study. (Include what went well, where changes should be made, and what should be improved.)”
In brief, testing early and often can save money in software development. This methodology is known as Shift Left. Meaning, testing shifts earlier in the software development life cycle rather than towards the end.
The Ponemon Institute crunched the numbers and estimated the cost of catching bugs in the development lifecycle. They found that catching bugs in the coding stage can cost an average of only $80 to fix. The cost rises to an average of $240 per defect to fix during the build stage. If software companies wait until the QA and security stages (which is common with waterfall testing methodologies) defects can cost $960 on average to fix. If a bug makes it through production, it can get costly at $7,600 per defect to repair.
Shift Left is great in theory, however, in practice can be difficult to implement. Most traditional practitioners would agree. One of the best ways to transition to Shift Left is with automation testing. Uniting testing at the coding stage, running automated test scenarios during the build and QA stages, with the goal of little testing at the security phase, and ultimately no bugs will slip through production.
It is important to implement STLC principles as early as possible. This avoids software delays, higher development costs, or bottlenecks as experienced in the past with waterfall development cycles.
Ivan Gekht of Gehsoft shares experiences from his company’s transition from waterfall methodologies and how it vastly helped improve the time to market. He explains, “the STLC/SDLC approach facilitates silos. In each phase, while working together, each part of the team is only responsible for their area. When the quality of the product is the QA team’s responsibility, it is incredibly hard to facilitate the developer’s accountability for the code’s quality.” Gekht describes how inefficiencies can derive from this method saying, “While STLC is an attempt to answer Agile challenges within waterfall methodologies, it still maintains the facilitation of some of the waterfall’s downfalls.”
STLC principles are designed to improve software quality and rid delays. Creating silos and countermanding accountability does not aid productivity. Ivan Gekht explains why, “In Agile, when you go with TDD (test-driven development) principles, unit tests are the developer’s responsibility. You write tests first and the code second. You are thinking about quality from the beginning instead of working on the code while your QA tries to come up with the unit test.”
For development shops to truly evolve with Shift Left practices, they must adopt testing in earlier phases of SDLC. We have clients who use our test automation tool to automatically test features early on in their development of new features. This acts as a synthetic model for Shift Left testing.
Superior, bug-free high-quality software is the focus of any software maker. If you are seeking superior software testing tools, give Autify a try today.