Test Design Techniques
The benefits of following the best practices in software quality assurance are clear. Every team strives to build a smooth and efficient process, and such practices are meant to enhance customer experience and add value to the brand’s reputation. With numerous international compliance rules and ever-growing user expectations, tech leaders have to understand the paces their product will be put through thoroughly.
As agile methodologies take over the testing domain, the role of testing is now almost organization-centric. So everyone in the tech team should perform their work with quality in mind. However, the QA leader still has the responsibility of designing effective tests.
The “shift left” approach emphasizes the need for the team to concentrate on quality from the earliest development stages. This trend in software testing means that a test leader needs to understand and build rapport with developers and include their feedback and abilities into the test design workflow and strategies.
A test leader’s challenges start at the very beginning of the product cycle. A SAAS platform today is ever-evolving, the features it had a year back are perhaps redundant, and product managers are thinking of ways to implement new features every sprint. In such a scenario, test design cannot remain a static phenomenon.
Just like with software development, the testing strategy should take into account how the system will work under real-world conditions. The number of methods to test a system is infinite, but testing resources are limited. A testing effort is shown in a test design to offer project and test workers a conceptual framework on the boundaries and extent of the test effort.
There is a lot of thought put into handling frequent deployments in today’s software development world. Testing is the most time-consuming phase of software development. Continuous delivery and software quality necessitates the use of numerous automated and manual tests.
Test design is the process of creating and writing a collection of test cases, also referred to as a test suite, to test a piece of software. Specification-based (also known as black-box) techniques, structure-based (also known as white-box) techniques, and experience-based techniques are the three primary types of test design techniques. These are classified as static or dynamic.
Continuous delivery practices have brought new challenges to QA leadership. Here are some of the common challenges faced.
Challenges of Continuous Testing
Things get complicated when your team drafts requirements during the test design phase. It’s common to have the process of defining requirements to be somewhat loose and imprecise. To make matters worse, requirements can shift during a sprint. Due to this, test coverage is frequently incomplete or even redundant. Organizations often end up having to allocate resources for additional testing. How do we solve this challenge? Let’s break down the answer into multiple pieces.
The Importance of Having Maximum Test Coverage
The ultimate goal of the software testers is to ensure that the developed application meets user requirements as well as the industry standards. In other words, it should be a bug-free application, which must meet or exceed the user’s expectations. Maximum test coverage is the key to achieving this goal. The QAs must have an excellent technical domain of the application along with in-depth knowledge of the user requirements during test design. Test coverage varies, and it depends on the particular stage of SDLC at which the test cases are executed. It also depends heavily on the type and platform of an application under test. For example, if you have a web application, you must know that the test coverage would differ between desktop and mobile browsers for the same application.
If you are developing test cases based on the features then the test coverage demands to cover all possible scenarios, while mimicking user behavior. This kind of approach would ensure that bugs are timely found and fixed. Any bug released into production otherwise would not only be a testing failure, but could also be expensive to mend.
The decision tree is another thing that could be maximized in test design. It is a flowchart type of structure where each node depicts a ‘test’ on an attribute. Every branch of the tree represents the output of the test, and every leaf node is a class label. That label is the decision taken after computing or checking all the attributes. This practice is found to be very effective, and it comprehensively enhances test coverage.
The other key benefit of maximum test coverage is that its output would reflect on that particular part of the codebase, which is still not covered in your testing. In the same way, it also points out the area that is useless for the project’s current scope. Therefore, you could easily eliminate those cases to make your test suite lighter and more effective. Eventually, all the practices related to test coverage mentioned here would prevent defect leakage to the higher or production environment.
It’s a win-win situation when you automate your tests. Regression testing ensures that the application continues to function after a change has been implemented. When testing after a bug fix, QA testers need to retest the entire product. On average, there are 3 new bugs introduced per 10 bugs fixed. This means a bug fix may bring in a new bug in another part of the product. Since the same tests must be run repeatedly after each fix and deployment, scripts or automated testing tools are recommended. Utilizing automation for the right types of testing activities saves vast amounts of time, catches issues early, and makes the whole process much more efficient. testRigor offers tremendous help here, enabling everyone on the QA team to create automated tests in plain English, no coding skills needed.
Getting Better Test Data
Locating appropriate test data is yet another challenge in the continuous delivery testing process. Data management takes up a significant amount of time. As a result, proper test data management (TDM) can help your team achieve better efficiency.
Automation of test data generation and the use of trustworthy test data management (TDM) tools are required. Synthetic data creation may also be an option for complying with the new regulations on data privacy.
Managing Test Environments
As part of continuous delivery, tests are run continuously during both the development and integration phases. As a result, your team will require a variety of environments for various purposes. Building, maintaining, and managing test environments is expensive and time-consuming, so if your team has multiple environments, it may be difficult to coordinate them all.
The challenges facing tech leaders nowadays are manifold. Business owners often deploy inadequate resources for testing, and the expectations from QA teams are ever-increasing. In this environment, QA leaders need a strategic approach to test design. There is a need for QA leaders to think of new metrics for test effectiveness and communicate successfully with stakeholders.