Defects in software design can have major impacts on product
quality, project duration and budget. Analytical quality assurance
tasks, like software inspection and testing, help detect deviations.
Recently, Pair Programming has been introduced as constructive
approach for agile code construction that includes implicit quality
assurance approaches, e.g., continuous defect detection, but
without active guidance. Several empirical studies recommend
active guidance for more efficient and effective defect detection.
In this paper we propose an extension of pair programming that
integrates best-practice inspection and test case generation
approaches in order to improve defect detection in software
products. We discuss the concept of a controlled experiment to
empirically evaluate the proposed pair programming approach.