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Learning API mappings for programming platforms
Descriptive
TitleInfo
Title
Learning API mappings for programming platforms
Name
(type = personal)
NamePart
(type = family)
Padmanaban
NamePart
(type = given)
Yogesh
NamePart
(type = date)
1986-
DisplayForm
Yogesh Padmanaban
Role
RoleTerm
(authority = RULIB)
author
Name
(type = personal)
NamePart
(type = family)
Ganapathy
NamePart
(type = given)
Vinod
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Vinod Ganapathy
Affiliation
Advisory Committee
Role
RoleTerm
(authority = RULIB)
chair
Name
(type = personal)
NamePart
(type = family)
Nath
NamePart
(type = given)
Badri
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Badri Nath
Affiliation
Advisory Committee
Role
RoleTerm
(authority = RULIB)
internal member
Name
(type = personal)
NamePart
(type = family)
Borgida
NamePart
(type = given)
Alex
DisplayForm
Alex Borgida
Affiliation
Advisory Committee
Role
RoleTerm
(authority = RULIB)
internal member
Name
(type = corporate)
NamePart
Rutgers University
Role
RoleTerm
(authority = RULIB)
degree grantor
Name
(type = corporate)
NamePart
Graduate School - New Brunswick
Role
RoleTerm
(authority = RULIB)
school
TypeOfResource
Text
Genre
(authority = marcgt)
theses
OriginInfo
DateCreated
(qualifier = exact)
2013
DateOther
(qualifier = exact);
(type = degree)
2013-01
Place
PlaceTerm
(type = code)
xx
Language
LanguageTerm
(authority = ISO639-2b);
(type = code)
eng
Abstract
(type = abstract)
Software developers often need to port applications written for a source platform to a target platform. One of the key tasks here is to find matching API calls in the target platform for the given API calls in the source platform. This task involves exhaustive reading in target platform API (Application Programming Interface) documentation to identify API methods corresponding to the given API methods of the source platform. We introduce an approach to the problem of inferring mapping between the APIs of a source and target platforms. It is constructed based on independently developed applications on source and target platforms performing similar functionality. We observe that in building these applications, developers exercised knowledge of the corresponding APIs. We develop two dynamic analysis techniques to systematically harvest this knowledge and infer likely mappings between the Graphical APIs of JavaME and Android Graphical platform. Rosetta Mapper: A tool which provides a ranked list of target API methods or method sequences that likely map to each source API method or method sequences. Rosetta Classifier: A supervised learning tool which classifies whether the given mapping between source API and target API is true or false using support vector machines.
Subject
(authority = RUETD)
Topic
Computer Science
RelatedItem
(type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier
(type = RULIB)
ETD
Identifier
ETD_4489
PhysicalDescription
Form
(authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
ix, 101 p. : ill.
Note
(type = degree)
M.S.
Note
(type = bibliography)
Includes bibliographical references
Note
(type = statement of responsibility)
by Yogesh Padmanaban
Subject
(authority = ETD-LCSH)
Topic
Application software--Development
Subject
(authority = ETD-LCSH)
Topic
Programming software
Identifier
(type = hdl)
http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000067816
RelatedItem
(type = host)
TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier
(type = local)
rucore19991600001
Location
PhysicalLocation
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(displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier
(type = doi)
doi:10.7282/T3GX498K
Genre
(authority = ExL-Esploro)
ETD graduate
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Rights
RightsDeclaration
(ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder
(type = personal)
Name
FamilyName
Padmanaban
GivenName
Yogesh
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime
(encoding = w3cdtf);
(qualifier = exact);
(point = start)
2013-01-07 03:28:36
AssociatedEntity
Name
Yogesh Padmanaban
Role
Copyright holder
Affiliation
Rutgers University. Graduate School - New Brunswick
AssociatedObject
Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical
RULTechMD
(ID = TECHNICAL1)
ContentModel
ETD
OperatingSystem
(VERSION = 5.1)
windows xp
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