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dc.contributor.authorCito, Jürgen
dc.contributor.authorShen, Jiasi
dc.contributor.authorRinard, Martin
dc.date.accessioned2021-11-05T19:16:01Z
dc.date.available2021-11-05T19:16:01Z
dc.date.issued2020-06
dc.identifier.urihttps://hdl.handle.net/1721.1/137591
dc.description.abstract© 2020 ACM. Background: Application frameworks, such as Ruby on Rails, introduce abstractions with the goal of simplifying development for particular application domains, such as web development. While experts enjoy increased productivity due to these abstractions, the flow of the programs is often hard to understand for non-experts and newcomers due to implicit flow and concealed lower level action that seems like "magic". Objective: We conjecture that converting these implicit flows into an explicit and unified form can help non-experts comprehend the programs using these frameworks. We call the process of unifying distributed, implicit flows into a single routine deimplicitization. Method: We want to conduct an experiment that studies the impact of deimplicitization on program comprehension. Particularly, we want to study how software developers with different expertise (novices/students, framework experts/professional developers) can answer comprehension questions differently with respect to time and correctness, under the treatments of either a deimplicitized version of the program in Python or the original version of the program in Ruby on Rails.en_US
dc.language.isoen
dc.publisherACMen_US
dc.relation.isversionof10.1145/3379597.3387507en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceMIT web domainen_US
dc.titleAn Empirical Study on the Impact of Deimplicitization on Comprehension in Programs Using Application Frameworksen_US
dc.typeArticleen_US
dc.identifier.citationCito, Jürgen, Shen, Jiasi and Rinard, Martin. 2020. "An Empirical Study on the Impact of Deimplicitization on Comprehension in Programs Using Application Frameworks." Proceedings - 2020 IEEE/ACM 17th International Conference on Mining Software Repositories, MSR 2020.
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.relation.journalProceedings - 2020 IEEE/ACM 17th International Conference on Mining Software Repositories, MSR 2020en_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2021-03-10T14:38:49Z
dspace.orderedauthorsCito, J; Shen, J; Rinard, Men_US
dspace.date.submission2021-03-10T14:38:51Z
mit.licenseOPEN_ACCESS_POLICY
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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