Code smells in cascading style sheets : an empirical study and a predictive model
department or school: Applied Science, Faculty of
department or school: Electrical and Computer Engineering, Department of
data provider: DSpace
degree campus: UBCV
creator: Gharachorlu, Golnaz
issued: 2014-12-05T17:07:09Z
issued: 2014
related degree: Master of Applied Science - MASc
degree grantor: University of British Columbia
description: Cascading Style Sheets (CSS) is widely used in today's web applications to separate presentation semantics from HTML content. Despite the simple syntax of CSS, the language has some characteristics, such as inheritance, cascading and specificity, which make authoring and maintaining CSS a challenging task. In this thesis, we describe a set of 26 CSS smells and errors, collected from various development resources and propose an automated technique to detect them. Additionally, we conduct a large empirical study on 500 websites, 5060 CSS files in total which consist of more than 10 million lines of CSS code, to investigate which smells and errors are more prevalent and to what extent they occur in CSS code of today's web applications. Finally, we propose a model based on the findings of our empirical study that is capable of predicting the total number of CSS code smells in any given website which can be used by developers as a CSS code quality guidance. A study of unused CSS code on 187 websites and its results are also described in this thesis.
aggregated CHO: https://circle.library.ubc.ca/rest/handle/2429/51364
note: Code Smells in Cascading StyleSheets: An Empirical Study and aPredictive ModelbyGolnaz GharachorluB.Sc., The University of Tehran, 2008A THESIS SUBMITTED IN PARTIAL FULFILLMENT OFTHE REQUIREMENTS FOR THE DEGREE OFMASTER OF APPLIED SCIENCEinThe Faculty of Graduate and Postdoctoral Studies(Electrical and Computer Engineering)THE UNIVERSITY OF BRITISH COLUMBIA(Vancouver)December 2014c© Golnaz Gharachorlu 2014AbstractCascading Style Sheets (CSS) is widely used in today’s web applications toseparate presentation semantics from HTML content. Despite the simplesyntax of CSS, the language has some characteristics, such as inheritance,cascading and specificity, which make authoring and maintaining CSS achallenging task. In this thesis, we describe a set of 26 CSS smells and errors,collected from various development resources and propose an automatedtechnique to detect them. Additionally, we conduct a large empirical studyon 500 websites, 5060 CSS files in total which consist of more than 10 millionlines of CSS code, to investigate which smells and errors are more prevalentand to what extent they occur in CSS code of today’s web applications.Finally, we propose a model based on the findings of our empirical studythat is capable of predicting the total number of CSS code smells in any givenwebsite which can be used by developers as a CSS code quality guidance. Astudy of unused CSS code on 187 websites and its results are also describedin this thesis.iiPrefaceThis thesis presents a large empirical study of code smells in CascadingStyle Sheets (CSS) conducted by the author under the supervision of Dr.Ali Mesbah. I was responsible for designing the smell detection algorithms,implementation and evaluation of the tool CSSNose that is an extendedversion of an open source tool called Cilla [1], collecting data, analyzingresults and proposing the predictive model.The results of this work is under review as a submission to a softwareengineering journal.iiiTable of ContentsAbstract . . …
has type: Thesis/Dissertation
date issued: 2015-02
is shown at: 10.14288/1.0167067
language: eng
degree discipline: Electrical and Computer Engineering
provider: Vancouver : University of British Columbia Library
publisher: University of British Columbia
rights: Attribution-NonCommercial-NoDerivs 2.5 Canada
rights URI: http://creativecommons.org/licenses/by-nc-nd/2.5/ca/
scholar level: Graduate
type: Text
identifier URI: http://hdl.handle.net/2429/51364