18th IEEE International Workshop on Software Test Automation (STA 2026)

Goal of the workshop

Test automation aims to reduce the cost and improve the effectiveness of software testing by using various techniques and methods. Other benefits are consistency and accuracy, reduction of overall test cycle time, risk mitigation of manual testing, and increase in overall product quality. Recording test activities as test scripts and playing the test scripts or record and playback was the traditional method. Software test automation has produced noteworthy research in the last decades. The search for solutions to automatically test any concept of software is critical, and it encompasses several areas: from the generation of the test cases, test oracles, test stubs/mocks; through the definition of selection and prioritization criteria; up to the engineering of infrastructures governing the execution of testing sessions locally or remotely in the cloud. Use of AI for test automation is particularly exciting and the future.

Workshop theme

Software engineering continues to prove essential to our daily lives ranging from financial services, health care, remote learning platforms, social networks to the era of connected and autonomous vehicles, and artificial intelligence control. As computer researchers, we see challenges as opportunities to fill gaps in how all dimensions of computing are developed, utilized, and supported. How to improve the resiliency of these components across a wide range of use domains is a significant challenge we suddenly find ourselves facing. How do we design systems that are able to withstand the stress of global-scale use, and still provide robust and secure services to end-users? 

The theme for COMPSAC 2026 is Agentic AI: Innovative Software, Computing Paradigms, and Applications for Migrating from Reactive Models to Proactive Systems. This highlights a crucial shift in artificial intelligence. Traditional AI has focused on generating information or responding to queries, but the next wave of AI development centers on proactive AI agents—systems that plan multi-step processes, make autonomous decisions, and learn from their interactions.

STA 2026 will be 18th edition of the workshop organized and run successfully every year since 2008. The workshop promotes high-quality research contributions on methods for software test automation, and original case studies reporting practices in this field. We invite contributions that focus on: (a) lessons learned about experiments of automatic testing in practice; (b) experiences of the adoption of testing tools, methods and techniques; (c) best practices to follow in testing and their measurable consequences; and (d) theoretical approaches that are applicable to the industry.

Aligned with the conference theme, STA theme for this year is “Adapting test automation to the AI era” emphasizing test automation for AI, test automation using AI, and AI testing education and training. We encourage submission in broad areas of software automation including AI in testing as well as applications and case studies in these areas will highly be appreciated.

Scope of the workshop

Topics of interest include, but are not limited to, the following:

• AI for Software Testing Automation
• Automated Testing of AI-based systems
• Education to software testing with the advent of AI-based technology
• Test case generation based on formal, semi-formal and AI models
• Test automation for large, complex systems
• Automated software testing for sustainability, resource efficiency, energy consumption
• Codeless and low code test automation
• Test Automation in Software Process and Evolution, DevOps, Agile, CI/CD flows
• Test-driven development and behavior driven testing
• Early defect detection, exploratory testing, reducing development timeline
• Formal methods, model checking and theories for testing and test automation
• Theoretical foundations and methods for test automation
• Functional, interoperability, and conformance testing. 
• Non-functional Security, performance, and robustness testing. Usability and user experience testing.
• Testing of embedded, reactive and object-oriented systems
• Testing cloud and web systems and services
• Product line testing
• Testing anomaly detectors
• Metrics for testing – test effectiveness, efficiency, test coverage
• Test tools
• Test modeling and test methodologies. Model Based Testing, Keyword Based Testing, Combinatorial testing, Test input generation
• Application in different domains – digital world, cloud computing, HPC, healthcare
• Experiments, empirical studies, experience reports, and case studies.
• Design of high-quality, reusable tests, test reuse, libraries, Product Line Testing
• Support for testing methods, test framework, test infrastructure.
• Management of distributed test assets and test environments
• Development, operation, integration, and standardization of test tools
• Test metrics to measure test efficiency and test coverage optimization. Quantitative studies.