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High-quality code comments support developers in software maintenance and program comprehension tasks. However, the semi-structured nature of comments, several conventions to write comments, and the lack of quality assessment tools for all aspects of comments make comment evaluation and maintenance a non-trivial problem. To understand the specification of high-quality comments to build effective assessment tools, we emphasize on acquiring a multi-perspective view of the comments, which can be approached by analyzing (1) the academic support for comment quality assessment, (2) developer commenting practices across languages, and (3) developer concerns about comments. To help researchers and developers in building comment quality assessment tools, we contribute: (i) a systematic literature review (SLR) of ten years (2010-2020) of research on assessing comment quality, (ii) a taxonomy of comment quality attributes, (iii) an empirically validated taxonomy of class comment information types (CITs) from three programming languages, (iv) a multi-programming-language approach to automatically identify the CITs, and (v) an empirically validated taxonomy of comment convention-related questions and recommendation from various Q&A forums. Our contributions provide various kinds of empirical evidence of the developer's interest in reducing efforts in the software documentation process, of the limited support developers get in automatically assessing comment quality, and of the challenges they face in writing high-quality comments.
