In theory, (good) documentation is an invaluable asset to any software project, as it helps stakeholders to use, understand, maintain, and evolve a system. In practice, however, documentation is generally affected by numerous shortcomings and issues, such as insufficient and inadequate content and obsolete, ambiguous information. To counter this, researchers are investigating the development of advanced recommender systems that automatically suggest high-quality documentation, useful for a given task. A crucial first step is to understand what quality means for practitioners and what information is actually needed for specific tasks.

We present two surveys performed with 146 practitioners to investigate (i) the documentation issues they perceive as more relevant together with solutions they apply when these issues arise; and (ii) the types of documentation considered as important given specific tasks. Our findings can help researchers in designing the next generation of documentation recommender systems.