Assessing the alignment between the information needs of developers and the documentation of programming languages: A case study on Rust
Filipe R. Cogo, Xin Xia, Ahmed E. Hassan

TL;DR
This paper introduces an automated semi-supervised topic modeling approach to evaluate how well programming language documentation aligns with developers' actual information needs, demonstrated through a case study on Rust.
Contribution
It presents a novel method for assessing topical alignment between documentation and developer queries, aiding documentation improvement and prioritization.
Findings
High overall topical alignment in Rust documentation
Scarcity of specific niche topics in documentation and Q&A
Certain language feature topics are only present in Q&A, not in official docs
Abstract
Programming language documentation refers to the set of technical documents that provide application developers with a description of the high-level concepts of a language. Such documentation is essential to support application developers in the effective use of a programming language. One of the challenges faced by documenters (i.e., personnel that produce documentation) is to ensure that documentation has relevant information that aligns with the concrete needs of developers. In this paper, we present an automated approach to support documenters in evaluating the differences and similarities between the concrete information need of developers and the current state of documentation (a problem that we refer to as the topical alignment of a programming language documentation). Our approach leverages semi-supervised topic modelling to assess the similarities and differences between the…
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Taxonomy
TopicsPower Systems and Technologies
