UA cloudflare authentication

 

Combining information retrieval modules and structural information for source code bug localization and feature location

Simple item page
dc.contributorAtkison, Travis Levestis
dc.contributorCarver, Jeffrey C.
dc.contributorParrish, Allen Scott
dc.contributor.advisorSmith, Randy K.
dc.contributor.advisorKraft, Nicholas A.
dc.contributor.authorShao, Peng
dc.contributor.otherUniversity of Alabama Tuscaloosa
dc.date.accessioned2017-03-01T14:48:42Z
dc.date.available2017-03-01T14:48:42Z
dc.date.issued2011
dc.descriptionElectronic Thesis or Dissertationen_US
dc.description.abstractBug localization and feature location in source code are software evolution tasks in which developers use information about a bug or feature present in a software system to locate the source code elements, such as classes or methods. These classes or methods must be modified either to correct the bug or implement a feature. Automating bug localization and feature location are necessary due to the size and complexity of modern software systems. Recently, researchers have developed static bug localization and feature location techniques using information retrieval techniques, such as latent semantic indexing (LSI), to model lexical information, such as identifiers and comments, from source code. This research presents a new technique, LSICG, which combines LSI modeling lexical information and call graphs to modeling structural information. The output is a list of methods ranked in descending order by likelihood of requiring modification to correct the bug or implement the feature under consideration. Three case studies including comparison of LSI and LSICG at method level and class level of granularity on 25 features in JavaHMO, 35 bugs in Rhino, 3 features and 6 bugs in jEdit demonstrate that The LSICG technique provides improved performance compared to LSI alone.en_US
dc.format.extent163 p.
dc.format.mediumelectronic
dc.format.mimetypeapplication/pdf
dc.identifier.otheru0015_0000001_0000733
dc.identifier.otherShao_alatus_0004D_10742
dc.identifier.urihttps://ir.ua.edu/handle/123456789/1238
dc.languageEnglish
dc.language.isoen_US
dc.publisherUniversity of Alabama Libraries
dc.relation.hasversionborn digital
dc.relation.ispartofThe University of Alabama Electronic Theses and Dissertations
dc.relation.ispartofThe University of Alabama Libraries Digital Collections
dc.rightsAll rights reserved by the author unless otherwise indicated.en_US
dc.subjectComputer science
dc.titleCombining information retrieval modules and structural information for source code bug localization and feature locationen_US
dc.typethesis
dc.typetext
etdms.degree.departmentUniversity of Alabama. Department of Computer Science
etdms.degree.disciplineComputer Science
etdms.degree.grantorThe University of Alabama
etdms.degree.leveldoctoral
etdms.degree.namePh.D.

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
file_1.pdf
Size:
646.75 KB
Format:
Adobe Portable Document Format
Download

Collections

Theses and Dissertations
Theses and Dissertations - Department of Computer Science