Let us examine some of the factors that drive the cost of quality assurance activity thus bloating the IT budgets. Taking pre-emptive measures can salvage the situation before it is too late.
Flaws in test automation
Test automation has proved beneficial for software testing, however, with increasing demand and the need for speed with superior quality has exposed certain chinks in the armor.
False failures are the bane of test automation since they lead to slowing down the whole testing process.
Test suite maintenance increasingly becomes a major headache with every test cycle. Updating test cases based on previous test results, or changes in specifications is a challenging and error-prone activity.
Test data maintenance isnโt easy either. Any change in specifications may lead to modification in test inputs. Keeping pace with rapid changes and testing multiple test conditions with multiple data combinations is an enormous task.
All these issues add to the overall project cost since the efforts involved are high and there might be delays due to tracking correcting false failures and maintenance activity.
Discovering bugs late in the testing cycle
Sometimes, the bug is discovered very late in the test cycle. Reasons could be any- outdated or limited test data, or unexpected errors due to an untested path because of limited test cases. Discovering bugs late in the testing cycle has a cascading effect on the project quality and schedule, which puts the whole estimated QA cost in peril.
Shift-left testing coupled with the power of AI addresses this issue to a major extent.
Inadequate test planning
Impeccable planning is the key to the success of any project. However, the lack of collaboration and communication between business and technical teams may riddle the project with delays. And the cost goes high since time is money.
How AI-based test automation helps in managing QA costs
Efficient test execution and management
AI-based testing helps in creating test cases covering all possible scenarios leading to better test coverage. Test cases are updated as a result of continuous feedback generated after every test.
The testing process is improvised since AI is capable of generating a large volume of varied test data for multiple test conditions. As a consequence, the time and effort involved in generating and maintaining test cases and test data are saved, resulting in saving overall cost.
Webomates can help you with working test automation in 4 weeks, with AiHealing by fixing the automation for every build in less than 24 hours, at half the cost.
The Webomates triad of AI Modeler engine, AI Test Strategy creator, and AI Test Package Analyzer is a boon for businesses struggling with rising QA costs.
AI Modeler engine can help you in generating and automating the right test cases.
AI Test Strategy and creator can help in devising a well-rounded test strategy for your software.
AI Test Package Analyzer keeps the test suite updated by providing a continuous feedback loop of defects to user stories/epics/requirements. All this is packaged together in a single testing service at a very nominal cost.
Self-Healing Test Automation
AI-infused testing services can effortlessly identify, understand and analyze frequent changes done to the software and aid in self-healing.
Webomatesโ AiHealing process leverages the power of AI/ML to achieve self-healing and scalability in testing, making regression testing much more efficient.
Now, we all know that executing the whole test suite for every change is not feasible. We make it simpler by giving an option of executing mini test suites, instead of the whole test suite, saving substantial man-hours, which further makes a significant difference in QA cost. Read More About: Optimize QA costs
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https://www.webomates.com/blog..../using-ai-based-test
White box testing ?
https://www.webomates.com/blog..../software-testing/yi
White box testing is used to test the structure and business logic of a program being developed. It requires the tester to know all the functional and design details of the module/code that is being tested. The tester needs to have in-depth knowledge of the requirements, design, code as well as the expected outcome. White-box testing can be applied at the Unit, Integration and System levels of the software testing process.
White Box Testing is known by several other names, such as Glass box testing, Clear Box testing, Open Box testing, Structural testing, Path Driven Testing or Logic driven testing.
Types of White Box Testing
Unit Testing: Performed on each unit or block of code as it is developed to identify a majority of bugs, early in the software development lifecycle.
Testing for Memory Leaks: Essential in cases where you have a slow running software application due to memory leaks.
What is black box testing?
Black Box Testing, also known as functional testing or behavioural testing, essentially requires the testers to evaluate the functionality and usability of the software without looking at the details of the code. It not only verifies and validates the functionality of the software but also checks for any interface issues.
In this article, we will explore the differences between these two types of testing and analyse how they can be best used for comprehensive testing.
Types of Black Box Testing
There are many types of Black Box Testing but the following are the prominent ones โ
Functional testing โ Related to the functional requirements of a system.
Non-functional testing โ Related to non-functional requirements such as performance, scalability, usability.
Regression testing โ Regression Testing is done after code fixes, upgrades or any other system maintenance to check the new code has not affected the existing code.
White box testing ensures traceability of test cases right to the source, thus ensuring adaptability of testing in case there is any change in the code.If you are interested in learning more about Webomatesโ CQ service please click here and schedule a demo or reach out to us at infoWebomates Inc.com
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