Further information

Background

Traditional approaches to software quality management are based on the assumption that developers can understand, take responsibility for and improve the code they write. AI-supported development paradigms such as vibe coding are increasingly calling this basic assumption into question: code is generated, adopted and deployed without a complete understanding on the part of the developer. This has far-reaching implications for established SQM processes such as code inspections, reviews, metrics or documentation standards, which are implicitly based on this very understanding.

Task definition

The target of the work is to systematically investigate which classic SQM processes and concepts are impaired in their effectiveness by AI-supported development and how they need to be adapted. Possible focal points include:

• Systematic review of classic SQM processes and their implicit assumptions about developer understanding and responsibility
• Analyzing the impact of vibe coding and AI-generated code on these processes
• Identification of processes that are obsolete, have limited effectiveness or need to be fundamentally adapted
• Derivation of recommendations for action for an adapted SQM in AI-supported development environments

Own ideas and focal points can be introduced in consultation.