Article

Supporting reuse by delivering task-relevant and personalized information

Authors:

Gerhard FischerAuthors Info & Claims

ICSE '02: Proceedings of the 24th International Conference on Software Engineering

Pages 513 - 523

https://doi.org/10.1145/581339.581402

Published: 19 May 2002 Publication History

Abstract

Technical, cognitive, and social factors inhibit the widespread success of systematic software reuse. Our research is primarily concerned with the cognitive and social challenges faced by software developers: how to motivate them to reuse and how to reduce the difficulty of locating components from a large reuse repository. Our research has explored a new interaction style between software developers and reuse repository systems enabled by information delivery mechanisms. Instead of passively waiting for software developers to explore the reuse repository with explicit queries, information delivery autonomously locates and presents components by using the developers' partially written programs as implicit queries.We have designed, implemented, and evaluated a system called CodeBroker, which illustrates different techniques to address the essential challenges in information delivery: to make the delivered information relevant to the task-at-hand and personalized to the background knowledge of an individual developer. Empirical evaluations of CodeBroker show that information delivery is effective in promoting reuse.

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Index Terms

Supporting reuse by delivering task-relevant and personalized information
1. Software and its engineering
  1. Software creation and management
  2. Software notations and tools
    1. Software libraries and repositories

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Published In

cover image ACM Conferences

ICSE '02: Proceedings of the 24th International Conference on Software Engineering

May 2002

797 pages

ISBN:158113472X

DOI:10.1145/581339

General Chair:
Will Tracz
Lockheed Martin Federal Systems
,
Program Chairs:
Jeff Magee
Imperial College
,
Michal Young
University of Oregon

Copyright © 2002 ACM.

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Published: 19 May 2002

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ICSE02: International Conference on Software Engineering

May 19 - 25, 2002

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ICSE '02 Paper Acceptance Rate 45 of 303 submissions, 15%;

Overall Acceptance Rate 276 of 1,856 submissions, 15%

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Cited By

Wu DAhmad WZhang DRamanathan MMa XSalakhutdinov RKolter ZHeller KWeller AOliver NScarlett JBerkenkamp F(2024)REPOFORMERProceedings of the 41st International Conference on Machine Learning10.5555/3692070.3694253(53270-53290)Online publication date: 21-Jul-2024
https://dl.acm.org/doi/10.5555/3692070.3694253
Maddila CShanbhogue SAgrawal AZimmermann TBansal CForsgren NAgrawal DHerzig Kvan Deursen ARoychoudhury ACadar CKim M(2022)Nalanda: a socio-technical graph platform for building software analytics tools at enterprise scaleProceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3540250.3558949(1246-1256)Online publication date: 7-Nov-2022
https://dl.acm.org/doi/10.1145/3540250.3558949
Abid SAbdul Basit HShamail SRoychoudhury ACadar CKim M(2022)Context-aware code recommendation in Intellij IDEAProceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3540250.3558937(1647-1651)Online publication date: 7-Nov-2022
https://dl.acm.org/doi/10.1145/3540250.3558937
Yu HLou YSun KRan DXie THao DLi YLi GWang QDwyer MDamian DZeller A(2022)Automated assertion generation via information retrieval and its integration with deep learningProceedings of the 44th International Conference on Software Engineering10.1145/3510003.3510149(163-174)Online publication date: 21-May-2022
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Mukherjee RChaudhuri SJermaine C(2021)Searching a database of source codes using contextualized code searchProceedings of the VLDB Endowment10.14778/3401960.340197213:10(1765-1778)Online publication date: 10-Mar-2021
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Kuttal SKim SMartos CBejarano A(2021)How end-user programmers forage in online repositories? An information foraging perspectiveJournal of Computer Languages10.1016/j.cola.2020.10101062(101010)Online publication date: Feb-2021
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Abid SShamail SBasit HNadi S(2021)FACER: An API usage-based code-example recommender for opportunistic reuseEmpirical Software Engineering10.1007/s10664-021-10000-w26:6Online publication date: 18-Aug-2021
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