AI to the Rescue: AI Tests Software

In a previous blog post, I discussed the evolution of testing your software through different schools. One of the most recent schools is the Context-Driven School. The Context-Driven school, as defined by Pettichord, has these characteristics:

• People create software
• Testing finds bugs. A bug is anything that could bug a stakeholder
• Testing provides information to the project
• Testing is a skilled, mental activity
• Testing is multidisciplinary
• Key question: What tests would be most valuable right now?
• Contribution example: Exploratory testing

People and AI create software

While thinking about the impact AI can have on software development, I realized that the first bullet point in this list is a very human-centric perspective. Of course, Pettichord wrote this statement decades ago. While people still create software, AI is pushing the boundaries of what that means. AI tools significantly enhance what a software engineer can do. Tools like GitHub co-pilot can now start software projects. And while a bit of a publicity stunt, Cognition AI’s Devin (the so-called first AI software engineer) can handle many complicated software development tasks.

Are we at the threshold of a new era where people and AI collaborate in software creation? It's not just a possibility but a highly likely scenario. We may still be in the early stages of the AI revolution, but the signs are promising. AI is already a valuable assistant in various industries, including software development. We're entering an era where heuristic work is automated, a clear testament to the collaborative potential of people and AI. We've made significant strides in automating algorithmic work over the past few decades. The future looks even brighter as we take the next step: automating heuristic work in partnership with AI solutions.

AI tests software

At Testaify, we agree with bullets two and three: Testing finds bugs and provides information to the project. Finding bugs and providing information is precisely Testaify’s purpose. Testaify conducts testing to find bugs and reports its findings back to the project's responsible party.

What about “Testing is a skilled, mental activity”? Yes, it is. Can AI perform the mental activity? The answer is yes. An essential part of the work for testing is to perform a set of discovery steps that will allow you to design the appropriate test cases. That information drives testing. Testaify’s AI Discovery Engine, a unique feature of our platform, can discover a web application in minutes. It builds a model that enables our AI Oracle Engine to design test cases. Testaify designs test cases and generates the test data for each test case. Then, Testaify’s AI Execution Engine executes all those test cases. That is how Testaify generates findings. Those findings are essential information about the status of the project.

At Testaify, we are committed to continuous improvement. We rebuild our model as the project evolves during every test session to identify the new context. Our AI Oracle Engine learns from the project stakeholders and their judgment regarding every finding reported by Testaify. In essence, Testaify is not just a static tool but a dynamic solution that improves with every test session. This commitment to continuous improvement sets us apart and ensures we are always at the forefront of testing software.

Testaify’s vision is to become multidisciplinary. As stated in one of our first blog posts, our vision is to get to CCT (Continuous Comprehensive Testing). When fully realized, Testaify will enable you to evaluate the following aspects of your software:

• Functional
• Usability
• Performance
• Accessibility
• Security

While we cannot offer all these perspectives with the first release, we want you to know where we want to go as we reach for the CCT star. Testaify will be a multidisciplinary solution to your testing problems.

AI can test more

According to Pettichord, the essential question for context-driven schools is: What tests would be most valuable right now? Testaify diverges from this school because our answer is, ”As much as we can execute!” 

One of the unique opportunities provided by AI/ML is to do more than what we can do today. By default, Testaify uses ten AI worker bees to work behind the scenes. When it comes to test execution, ten different tests execute concurrently. Testaify’s AI Execution Engine, a key component of our platform, can run as often as needed at any time of the day. Imagine executing thousands of test cases in an hour. When I joined e-Builder, the QA team told me they would need four to five weeks to execute the regression suite manually. That regression suite had a little bit less than a thousand tests.

AI will significantly impact how we test software. The future of testing is here! Join our waitlist to be one of the first to try Testaify.