DAY 1, 21 MAY
14:00 - 14:45

Technical A

Mesut Durukal
Test Automation Lead
For All


Mesut Durukal is QA & Test Automation Manager at Siemens.
He has a BSc & MSc degree from Boğaziçi University Electrical & Electronic Engineering. He has a 7 years’ experience in Defense Industry, working in Multilocation projects serving as the Manager of Verification & Validation activities. He has then been working in Agile Software Testing projects for 3 years. He is acting as a Product Owner & E2E Test Automation Leader for the QA team.
His expertise includes:
- Project Management
- Agile Methodologies: Scrum Framework
- Software Testing: Test automation in Java & SW testing frameworks
- Cloud Testing (SAP, AWS)
- API testing frameworks: SOAP & Restful Web Services Testing

Talk: Practical Applications of Artificial Intelligence in Software Testing.

Today, every possible application, which can help to overcome increasing QA and Testing challenges, is tried to be adapted to software testing. Probably, one of the most exciting candidates in this point is the emerging introduction of machine-based intelligence into testing. From contribution against challenges point of view, AI practices promise for save on time and additional coverage.
The presentation introduces the practical applications of artificial intelligence (AI) based software testing. Specifically, it follows the traditional software testing process to review AI applications in each period. Firstly, this talk gives a quick view of the machine learning types. Then, the AI applications are listed from these perspectives: test definition, implementation, execution, maintenance and grouping, and bug handling. What’s more, not only existing AI applications are presented but also insights about what can be done in the future are made. Finally, the talk summarizes the application areas with algorithms and discusses the advantages and the potential risks of AI applications in software testing.
In this presentation, several AI applications which are examined on automated testing framework are investigated. Requirements in each case, details of the algorithms and results will be shared. Statistical data which is an indicator for the advantages of the applications will be provided as well. A few sample applications are:
- Detection of changes on design and relevant reactions
- Bug tracking
- Clustering of defects and relevant reactions:
o Generating test cases
o Generating test suites
o Prioritization
- Automatic Code generation
This talk targets at an important problem, AI-based applications of software testing. As more and more researchers try to use AI techniques to solve the traditional software problems, what and how we can use it is a crucial issue. Some guides are needed for both AI and software engineering researchers, so as this talk does. AI is one of the hottest topics in software world nowadays. Especially mining valuable information from bugs can be made use of by managers to guide feature priorities.
It is well organized and easy-to-follow. It introduces the applications in different stages of testing, that makes audience easy to find what they want.
Proposed approaches can be applied by any organization by adapting according to the related work to achieve time and cost reduction. In this way, key learnings will be covered such as:
• How to strengthen test coverage.
• How to utilize test suites.
• Maintenance effort reduction.
• Automation in all stages: Implementation, Executions, Reporting.
• How to learn from bugs.
• How to detect bugs in early stages.