Abstract
A considerable part of the source code is identifier names-- unique lexical tokens that provide information about entities, and entity interactions, within the code. Identifier names provide human-readable descriptions of classes, functions, variables, etc. Poor or ambiguous identifier names (i.e., names that do not correctly describe the code behavior they are associated with) will lead developers to spend more time working towards understanding the code's behavior. Bad naming can also have detrimental effects on tools that rely on natural language clues; degrading the quality of their output and making them unreliable. Additionally, misinterpretations of the code, caused by poor names, can result in the injection of quality issues into the system under maintenance. Thus, improved identifier naming increases developer effectiveness, higher-quality software, and higher-quality software analysis tools. In this dissertation, I establish several novel concepts that help measure and improve the quality of identifiers. The output of this dissertation work is a set of identifier name appraisal and quality tools that integrate into the developer workflow. Through a sequence of empirical studies, I have formulated a series of heuristics and linguistic patterns to evaluate the quality of identifier names in the code and provide naming structure recommendations. I envision and working towards supporting developers in integrating my contributions, discussed in this dissertation, into their development workflow to significantly improve the process of crafting and maintaining high-quality identifier names in the source code.
Library of Congress Subject Headings
Software maintenance--Quality control; Readability (Literary style); File organization (Computer science)--Automation
Publication Date
6-2022
Document Type
Dissertation
Student Type
Graduate
Degree Name
Computing and Information Sciences (Ph.D.)
Department, Program, or Center
Computer Science (GCCIS)
Advisor
Christian D. Newman
Advisor/Committee Member
Mohamed Wiem Mkaouer
Advisor/Committee Member
Marcos Zampieri
Recommended Citation
Peruma, Anthony S., "Supporting the Maintenance of Identifier Names: A Holistic Approach to High-Quality Automated Identifier Naming" (2022). Thesis. Rochester Institute of Technology. Accessed from
https://repository.rit.edu/theses/11219
Campus
RIT – Main Campus
Plan Codes
COMPIS-PHD