SEOct 14, 2021

Readability and Understandability of Snippets Recommended by General-purpose Web Search Engines: a Comparative Study

arXiv:2110.07087v1
Originality Synthesis-oriented
AI Analysis

This addresses code quality issues for developers relying on web searches, but it is incremental as it compares existing engines without proposing new methods.

The study analyzed the readability and understandability of code snippets recommended by general-purpose web search engines like Google, Yahoo!, and Bing for 9,480 queries, finding that better-ranked snippets are not always more readable or understandable, and Google outperformed others in readability scores.

Developers often search for reusable code snippets on general-purpose web search engines like Google, Yahoo! or Microsoft Bing. But some of these code snippets may have poor quality in terms of readability or understandability. In this paper, we propose an empirical analysis to analyze the readability and understandability score from snippets extracted from the web using three independent variables: ranking, general-purpose web search engine, and recommended site. We collected the top-5 recommended sites and their respective code snippet recommendations using Google, Yahoo!, and Bing for 9,480 queries, and evaluate their readability and understandability scores. We found that some recommended sites have significantly better readability and understandability scores than others. The better-ranked code snippet is not necessarily more readable or understandable than a lower-ranked code snippet for all general-purpose web search engines. Moreover, considering the readability score, Google has better-ranked code snippets compared to Yahoo! or Microsoft Bing

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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