abstract: One of the most common errors developers make is to provide incorrect string
identifiers across the HTML5-JavaScript-CSS3 stack. The existing literature shows that a
significant percentage of defects observed in real-world codebases belong to this
category. Existing work focuses on semantic static analysis, while this thesis attempts to
tackle the challenges that can be solved using syntactic static analysis. This thesis
proposes a tool for quickly identifying defects at the time of injection due to
dependencies between HTML5, JavaScript, and CSS3, specifically in syntactic errors in
string identifiers. The proposed solution reduces the delta (time) between defect injection
and defect discovery with the use of a dedicated just-in-time syntactic string identifier
resolution tool. The solution focuses on modeling the nature of syntactic dependencies
across the stack, and providing a tool that helps developers discover such dependencies.
This thesis reports on an empirical study of the tool usage by developers in a realistic
scenario, with the focus on defect injection and defect discovery times of defects of this
nature (syntactic errors in string identifiers) with and without the use of the proposed
tool. Further, the tool was validated against a set of real-world codebases to analyze the
significance of these defects. / Dissertation/Thesis / Masters Thesis Computer Science 2016
| Identifer | oai:union.ndltd.org:asu.edu/item:39436 |
| Date | January 2016 |
| Contributors | Kalsi, Manit Singh (Author), Gary, Kevin A (Advisor), Lindquist, Timothy E (Committee member), Doupé, Adam (Committee member), Arizona State University (Publisher) |
| Source Sets | Arizona State University |
| Language | English |
| Detected Language | English |
| Type | Masters Thesis |
| Format | 106 pages |
| Rights | http://rightsstatements.org/vocab/InC/1.0/, All Rights Reserved |
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