Readability models and tools have been proposed to measure the effort to read code. However, these models are not completely able to capture the quality improvements in code as perceived by developers. To investigate possible features for new readability models and production-ready tools, we aim to better understand the types of readability improvements performed by developers when actually improving code readability, and identify discrepancies between suggestions of automatic static tools and the actual improvements performed by developers. We collected 370 code readability improvements from 284 Merged Pull Requests (PRs) under 109 GitHub repositories and produce a catalog with 26 different types of code readability improvements, where in most of the scenarios, the developers improved the code readability to be more intuitive, modular, and less verbose. Surprisingly, SonarQube only detected 26 out of the 370 code readability improvements. This suggests that some of the catalog produced has not yet been addressed by SonarQube rules, highlighting the potential for improvement in Automatic static analysis tools (ASAT) code readability rules as they are perceived by developers.

Abstract Official documentation of software development technologies, for example, APIs, may not be sufficient for all developer needs, so searching on the Internet is a usual practice. Nonetheless, finding useful information may be challenging because the best solutions are not always among the first ranked pages. Developers need to read and discard irrelevant pages, that is, those without code examples or those that have content with little focus on the desired solution. This work aims at proposing an approach to mine relevant solutions for programming tasks from search engine results by removing irrelevant pages. The authors evaluated the top‐20 pages returned by the Google search engine, for 10 different queries, and observed that only 31% of the evaluated pages are relevant to developers. Then, the authors proposed and evaluated three different approaches to mine the relevant pages returned by the search engine. Google's search engine has been used as a baseline, and authors’ results have shown that it returns a reasonable number of irrelevant pages for developers, and the authors could establish an effective approach to remove irrelevant pages, suggesting that developers could benefit from a customised web search filter for development content.