Towards Automated Context-aware Software Quality Management

To consistently improve software quality management, greater automation and tighter integration of quality tools and measurements in the software engineering environment is essential. However, automation of software quality management faces numerous challenges such as project uniqueness, project dynamics, efficiency, and limited time and quality expenditures. In this paper, an approach is proposed that extends the Goal-Question-Metric technique and automates the monitoring of quality goals via a multi-agent system by using competitive bidding agent behavior for proactive vs. cooperative voting for reactive measures. The preliminary results show promise for systematically harmonizing (conflicting) quality attributes, goals, metrics, and countermeasures and for automating aspects of software quality management

Towards Configurable Data Collection for Sustainable Supply Chain Communication

These days, companies in the automotive and electronics sector are forced by legal regulations and customer needs to collect a myriad of different indicators regarding sustainability of their products. However, in today's supply chains, these products are often the result of the collaboration of a large number of companies. Thus, these companies have to apply complex, cross-organizational, and potentially long-running data collection processes to gather their sustainability data. Comprising a great number of manual and automated tasks for different partners, these processes imply great variability. To support such complex data collection, we have designed a lightweight, automated approach for contextual process configuration