ASE 2022 (series) / [Workshop] AeSIR '22 / Rank Learning-Based Code Readability Assessment with Siamese Neural Networks
Rank Learning-Based Code Readability Assessment with Siamese Neural NetworksVirtual
Mon 10 Oct 2022 11:20 - 11:30 at Online Workshop 3 - Paper Presentation Session 2: Readability Assessment Chair(s): Fernanda Madeiral
Automatically assessing code readability is a relatively new challenge that has attracted growing attention from the software engineering community. In this paper, we outline the idea to regard code readability assessment as a learning-to-rank task. Specifically, we design a pairwise ranking model with siamese neural networks, which takes as input a code pair and outputs their readability ranking order. We have evaluated our approach on three publicly available datasets. The result is promising, with an accuracy of 83.5%, a precision of 86.1%, a recall of 81.6%, an F-measure of 83.6% and an AUC of 83.4%.
Mon 10 OctDisplayed time zone: Eastern Time (US & Canada)
Mon 10 Oct
Displayed time zone: Eastern Time (US & Canada)
11:10 - 11:45 | Paper Presentation Session 2: Readability Assessment[Workshop] AeSIR '22 at Online Workshop 3 Chair(s): Fernanda Madeiral Vrije Universiteit Amsterdam | ||
11:10 10mPaper | How Readable is Model Generated Code? Examining Readability and Visual Inspection of GitHub CopilotVirtual [Workshop] AeSIR '22 Naser Al Madi Colby College | ||
11:20 10mPaper | Rank Learning-Based Code Readability Assessment with Siamese Neural NetworksVirtual [Workshop] AeSIR '22 | ||
11:30 15mLive Q&A | Q&A and Open Discussion on Readability AssessmentVirtual [Workshop] AeSIR '22 | ||
