TY - GEN
T1 - Patterns of syntax theme customization for code editors
AU - Matthew Sterling, Mark
AU - Suleimenov, Aidarbek
PY - 2019/2/19
Y1 - 2019/2/19
N2 - Modern software development tools typically provide a syntax highlighting feature to enhance the readability of source code. Syntax highlighting means that different kinds of terms in the text of source code are rendered in visually distinct ways. A syntax theme is a collection of definitions that determine the look of a workspace. Editors and IDEs often let the user customize the syntax theme to their preference and can also provide services for users to share themes within the community. This paper presents a data mining study of a large collection of publicly available syntax themes (approximately 330) associated with a popular open-source text editor. For each theme we collected certain metadata as well as a cascading stylesheet definition. The metadata includes information such as the title of theme, a plain text description, and specific programming languages supported by the theme. For each syntax theme, a preprocessor script creates a feature vector that aggregates data from the theme definition and metadata. Themes are analyzed with both RGB and HSV color models. Analysis shows a variety of significant correlations in the dataset as well general patterns of syntax theme usage. We also discuss how our dataset bears on previously established models of code comprehension.
AB - Modern software development tools typically provide a syntax highlighting feature to enhance the readability of source code. Syntax highlighting means that different kinds of terms in the text of source code are rendered in visually distinct ways. A syntax theme is a collection of definitions that determine the look of a workspace. Editors and IDEs often let the user customize the syntax theme to their preference and can also provide services for users to share themes within the community. This paper presents a data mining study of a large collection of publicly available syntax themes (approximately 330) associated with a popular open-source text editor. For each theme we collected certain metadata as well as a cascading stylesheet definition. The metadata includes information such as the title of theme, a plain text description, and specific programming languages supported by the theme. For each syntax theme, a preprocessor script creates a feature vector that aggregates data from the theme definition and metadata. Themes are analyzed with both RGB and HSV color models. Analysis shows a variety of significant correlations in the dataset as well general patterns of syntax theme usage. We also discuss how our dataset bears on previously established models of code comprehension.
KW - Data mining
KW - Syntax highlighting
KW - Text editors
UR - http://www.scopus.com/inward/record.url?scp=85063166065&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85063166065&partnerID=8YFLogxK
U2 - 10.1109/ICOMIS.2018.8644882
DO - 10.1109/ICOMIS.2018.8644882
M3 - Conference contribution
AN - SCOPUS:85063166065
T3 - 2018 IEEE 3rd International Conference on Communication and Information Systems, ICCIS 2018
SP - 173
EP - 176
BT - 2018 IEEE 3rd International Conference on Communication and Information Systems, ICCIS 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd IEEE International Conference on Communication and Information Systems, ICCIS 2018
Y2 - 28 December 2018 through 30 December 2018
ER -