A comprehensive model for code readability. Issue 6 (8th June 2018)

• Record Type: Journal Article
• Authors: Scalabrino, Simone; Linares‐Vásquez, Mario; Oliveto, Rocco; Poshyvanyk, Denys
• Other Names: Bavota Gabriele guestEditor.; Maletic Jonathan I. guestEditor.; Collard Michael L. guestEditor.
• Is Part Of: Journal of software. Volume 30:Issue 6(2018)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-06-08
• Subjects: code readability -- quality warning prediction -- textual analysis; Software engineering -- Periodicals; Computer software -- Development -- Periodicals; Software maintenance -- Periodicals; 005.1
• DOI: 10.1002/smr.1958
• Languages: English
• ISSNs: 2047-7473

Abstract

Abstract: Unreadable code could compromise program comprehension, and it could cause the introduction of bugs. Code consists of mostly natural language text, both in identifiers and comments, and it is a particular form of text. Nevertheless, the models proposed to estimate code readability take into account only structural aspects and visual nuances of source code, such as line length and alignment of characters. In this paper, we extend our previous work in which we use textual features to improve code readability models. We introduce 2 new textual features, and we reassess the readability prediction power of readability models on more than 600 code snippets manually evaluated, in terms of readability, by 5K+ people. We also replicate a study by Buse and Weimer on the correlation between readability and FindBugs warnings, evaluating different models on 20 software systems, for a total of 3M lines of code. The results demonstrate that (1) textual features complement other features and (2) a model containing all the features achieves a significantly higher accuracy as compared with all the other state‐of‐the‐art models. Also, readability estimation resulting from a more accurate model, ie, the combined model, is able to predict more accurately FindBugs warnings.