  Previous studies have shown that high-quality code comments assist developers
in program comprehension and maintenance tasks. However, the semi-structured
nature of comments, unclear conventions for writing good comments, and the lack
of quality assessment tools for all aspects of comments make their evaluation
and maintenance a non-trivial problem. To achieve high-quality comments, we
need a deeper understanding of code comment characteristics and the practices
developers follow. In this thesis, we approach the problem of assessing comment
quality from three different perspectives: what developers ask about commenting
practices, what they write in comments, and how researchers support them in
assessing comment quality.
  Our preliminary findings show that developers embed various kinds of
information in class comments across programming languages. Still, they face
problems in locating relevant guidelines to write consistent and informative
comments, verifying the adherence of their comments to the guidelines, and
evaluating the overall state of comment quality. To help developers and
researchers in building comment quality assessment tools, we provide: (i) an
empirically validated taxonomy of comment convention-related questions from
various community forums, (ii) an empirically validated taxonomy of comment
information types from various programming languages, (iii) a
language-independent approach to automatically identify the information types,
and (iv) a comment quality taxonomy prepared from a systematic literature
review.
