AI-Driven Testing

Chapter 5. Future Directions

Now that you’ve taken the tour of AI-driven test automation, let me take you on a journey into the future of this emerging technology. In this chapter, I share my thoughts on how AI-driven test automation tools will evolve over the next decade. In my opinion, the AI for automation evolution and/or revolution, if you watch enough Hollywood movies, involves three steps. Within the context of software testing, these including using AI for the following:

1. Enhancing existing tools and frameworks at each testing level and dimension

2. Full stack replacement of entire test automation tool sets

3. Adaptive ML systems designed with self-testing capabilities

Although I have zero faith in my ability to predict the future, I do think it’s important to spend some time discussing and theorizing about the future directions, paths, and intersections of AI and testing, prior to wrapping up this report.

Enhancing Existing Tools

Considering the current state of the art, I believe the immediate future of AI-driven test automation is on track with continued integration of AI into existing tools that target different testing levels, quality attributes, and application domains. As shown in Figure 5-1, the trend is likely to be one where researchers and practitioners continue to tackle each concern somewhat in isolation, until individual areas become stable and reliable.

Figure 5-1. In the near term, AI enhances existing tools that tackle individual testing concerns ...