Despite GenAI is taking place replacing programmers work, the software engineering activities are not limited to programming only. Within the life-cycle of software development, multiple steps could benefit from proper AI utilization. Previously the analysis of requirements, code, system performance and documentation were highly managed by person. With the rise of GenAI and ML models popularity, the possibilities to automate the most of the software development life cycle could be considered. This challenge invites to propose solutions, oriented on system quality estimation in different stages of the software development life cycle.
The direction for the challenge ideas, which could be converted into multiple final thesis or individual project topics is the following:
- Research of code-mining methods for programmign code quality assurance
- Detection of code quality vulnerabilities through deep learning models
- Automation of acceptance test generation, based on the requirements specificaion
- Model for quality evaluation of the requirement specification.
Regarding more details on the challenge and topics contact Asta Slotkienė, VILNIUS TECH.