research-article

Codebook: discovering and exploiting relationships in software repositories

Authors:

Yit Phang Khoo,

Thomas ZimmermannAuthors Info & Claims

ICSE '10: Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 1

Pages 125 - 134

https://doi.org/10.1145/1806799.1806821

Published: 01 May 2010 Publication History

Abstract

Large-scale software engineering requires communication and collaboration to successfully build and ship products. We conducted a survey with Microsoft engineers on inter-team coordination and found that the most impactful problems concerned finding and keeping track of other engineers. Since engineers are connected by their shared work, a tool that discovers connections in their work-related repositories can help.

Here we describe the Codebook framework for mining software repositories. It is flexible enough to address all of the problems identified by our survey with a single data structure (graph of people and artifacts) and a single algorithm (regular language reachability). Codebook handles a larger variety of problems than prior work, analyzes more kinds of work artifacts, and can be customized by and for end-users. To evaluate our framework's flexibility, we built two applications, Hoozizat and Deep Intellisense. We evaluated these applications with engineers to show effectiveness in addressing multiple inter-team coordination problems.

References

[1]

F. Alkhateeb. Querying RDF(S) with Regular Expressions. PhD thesis, Joseph Fourier University of Grenoble, June 2008.

[2]

M. C. Andrew Cencini. Sql server 2005 full-text search: Internals and enhancements. http://msdn.microsoft.com/en-us/library/ms345119(SQL.90).aspx.

[3]

J. Anvik, L. Hiew, and G. C. Murphy. Who should fix this bug? In Proceedings of ICSE, pages 361--370, 2006.

Digital Library

[4]

J. Aranda and G. Venolia. The secret life of bugs: Going past the errors and omissions in software repositories. In Proceedings of ICSE, pages 298--308, 2009.

Digital Library

[5]

B. Ashok, J. Joy, H. Liang, S. Rajamani, G. Srinivasa, and V. Vangala. Debugadvisor: A recommender system for debugging. In Proceedings of ESEC/FSE '09, August 2009.

Digital Library

[6]

A. Begel and R. DeLine. Codebook: Social networking over code. In Proceedings of ICSE, NIER Track, 2009.

[7]

A. Begel, N. Nagappan, C. Poile, and L. Layman. Coordination in large-scale software teams. In Proceedings of CHASE, pages 1--7, 2009.

Digital Library

[8]

M. Cataldo, D. Damian, P. Devanbu, S. Easterbrook, J. Herbsleb, and A. Mockus. 2nd international workshop on socio-technical congruence, May 2009.

[9]

M. Cataldo, J. D. Herbsleb, and K. M. Carley. Socio-technical congruence: a framework for assessing the impact of technical and work dependencies on software development productivity. In Proceedings of ESEM, pages 2--11, 2008.

Digital Library

[10]

M. Cataldo, P. A. Wagstrom, J. D. Herbsleb, and K. M. Carley. Identification of coordination requirements: implications for the design of collaboration and awareness tools. In Proceedings of CSCW, pages 353--362, 2006.

Digital Library

[11]

D. Cubranic, J. Singer, and K. S. Booth. Hipikat: A project memory for software development. IEEE TSE, 31(6):446--465, 2005. Member-Gail C. Murphy.

Digital Library

[12]

C. de Souza, J. Froehlich, and P. Dourish. Seeking the source: software source code as a social and technical artifact. In Proceedings of GROUP, pages 197--206, 2005.

Digital Library

[13]

C. R. B. de Souza and D. F. Redmiles. An empirical study of software developers' management of dependencies and changes. In Proceedings of ICSE, pages 241--250, New York, NY, USA, 2008. ACM.

Digital Library

[14]

A. E. Hassan. The road ahead for mining software repositories. In Proceedings ICSM, FoSM track, pages 48--57, 2008.

[15]

P. Hinds and C. McGrath. Structures that work: social structure, work structure and coordination ease in geographically distributed teams. In Proceedings of CSCW, pages 343--352, 2006.

Digital Library

[16]

R. Holmes and A. Begel. Deep intellisense: a tool for rehydrating evaporated information. In Proceedings of MSR, pages 23--26, 2008.

Digital Library

[17]

R. C. Holt. Grokking software architecture. In Proceedings of WCRE, pages 5--14, 2008.

Digital Library

[18]

D. Hyland-Wood, D. Carrington, and S. Kaplan. Toward a software maintenance methodology using semantic web techniques. In Proceedings of SOFTWARE-EVOLVABILITY, pages 23--30, 2006.

Digital Library

[19]

H. H. Kagdi, M. L. Collard, and J. I. Maletic. A survey and taxonomy of approaches for mining software repositories in the context of software evolution. Journal of Software Maintenance, 19(2):77--131, 2007.

Digital Library

[20]

C. Kiefer, A. Bernstein, and J. Tappolet. Mining software repositories with iSPARQL and a software evolution ontology. In Proceedings of MSR, page 10, 2007.

Digital Library

[21]

A. J. Ko, R. DeLine, and G. Venolia. Information needs in collocated software development teams. In Proceedings of ICSE, pages 344--353, 2007.

Digital Library

[22]

K. Kochut and M. Janik. Sparqler: Extended sparql for semantic association discovery. In Proceedings of ESWC, pages 145--159, 2007.

Digital Library

[23]

T. D. LaToza, G. Venolia, and R. DeLine. Maintaining mental models: a study of developer work habits. In Proceedings of ICSE, pages 492--501, 2006.

Digital Library

[24]

F. Manola and E. Miller. RDS primer. http://www.w3.org/TR/REC-rdf-syntax/, February 2004.

[25]

A. Mockus and J. D. Herbsleb. Expertise browser: a quantitative approach to identifying expertise. In Proceedings of ICSE, pages 503--512, 2002.

Digital Library

[26]

E. Prud'hommeaux and A. Seaborne. SPARQL query language for RDF. http://www.w3.org/TR/rdf-sparql-query/, January 2008.

[27]

P. Runeson, M. Alexandersson, and O. Nyholm. Detection of duplicate defect reports using natural language processing. In Proceedings of ICSE, pages 499--510, 2007.

Digital Library

[28]

Z. M. Saul, V. Filkov, P. Devanbu, and C. Bird. Recommending random walks. In Proceedings of ESEC-FSE, pages 15--24, 2007.

Digital Library

[29]

A. Tarvo. Mining software history to improve software maintenance quality: A case study. IEEE Software, 26(1):34--40, 2009.

Digital Library

[30]

E. Trainer, S. Quirk, C. de Souza, and D. Redmiles. Bridging the gap between technical and social dependencies with ariadne. In Proceedings of eTX at OOPSLA, pages 26--30, 2005.

Digital Library

[31]

G. Venolia. Textual alusions to artifacts in software-related repositories. In Proceedings of MSR, pages 151--154, 2006.

Digital Library

[32]

T. Zimmermann, P. Weißgerber, S. Diehl, and A. Zeller. Mining version histories to guide software changes. IEEE TSE, 31(6):429--445, 2005.

Digital Library

Cited By

Horvath AMacvean AMyers B(2024)Meta-Manager: A Tool for Collecting and Exploring Meta Information about CodeProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642676(1-17)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642676
Rocha LCanedo EPereira CBezerra CMendes F(2024)How does parenthood affect an ICT practitioner’s work? A survey study with fathersEmpirical Software Engineering10.1007/s10664-024-10534-929:6Online publication date: 19-Aug-2024
https://dl.acm.org/doi/10.1007/s10664-024-10534-9
Wang GZhou MWei XYang G(2023)Vehicular Abandoned Object Detection Based on VANET and Edge AI in Road ScenesIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2023.329650824:12(14254-14266)Online publication date: Dec-2023
https://doi.org/10.1109/TITS.2023.3296508
Show More Cited By

Recommendations

Supporting Qualitative Analysis with Large Language Models: Combining Codebook with GPT-3 for Deductive Coding
IUI '23 Companion: Companion Proceedings of the 28th International Conference on Intelligent User Interfaces

Qualitative analysis of textual contents unpacks rich and valuable information by assigning labels to the data. However, this process is often labor-intensive, particularly when working with large datasets. While recent AI-based tools demonstrate ...
Grounded Copilot: How Programmers Interact with Code-Generating Models

Powered by recent advances in code-generating models, AI assistants like Github Copilot promise to change the face of programming forever. But what is this new face of programming? We present the first grounded theory analysis of how programmers interact ...
Analyze this! 145 questions for data scientists in software engineering
ICSE 2014: Proceedings of the 36th International Conference on Software Engineering

In this paper, we present the results from two surveys related to data science applied to software engineering. The first survey solicited questions that software engineers would like data scientists to investigate about software, about software ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

ICSE '10: Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 1

May 2010

627 pages

ISBN:9781605587196

DOI:10.1145/1806799

General Chairs:
Jeff Kramer
Imperial College, London, UK
,
Judith Bishop
Microsoft Research, Redmond
,
Program Chairs:
Prem Devanbu
University of California at Davis
,
Sebastian Uchitel
University of Buenos Aires, Argentina and Imperial College London, UK

Copyright © 2010 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 May 2010

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

ICSE '10

Sponsor:

SIGSOFT

ICSE '10: 32nd International Conference on Software Engineering

May 1 - 8, 2010

Cape Town, South Africa

Acceptance Rates

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

Upcoming Conference

ICSE 2025

2025 IEEE/ACM 46th International Conference on Software Engineering

April 26 - May 3, 2025

Ottawa , ON , Canada

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

155
Total Citations
View Citations
1,152
Total Downloads

Downloads (Last 12 months)46
Downloads (Last 6 weeks)6

Reflects downloads up to 05 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

Horvath AMacvean AMyers B(2024)Meta-Manager: A Tool for Collecting and Exploring Meta Information about CodeProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642676(1-17)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642676
Rocha LCanedo EPereira CBezerra CMendes F(2024)How does parenthood affect an ICT practitioner’s work? A survey study with fathersEmpirical Software Engineering10.1007/s10664-024-10534-929:6Online publication date: 19-Aug-2024
https://dl.acm.org/doi/10.1007/s10664-024-10534-9
Wang GZhou MWei XYang G(2023)Vehicular Abandoned Object Detection Based on VANET and Edge AI in Road ScenesIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2023.329650824:12(14254-14266)Online publication date: Dec-2023
https://doi.org/10.1109/TITS.2023.3296508
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
da Silva Junior JCampagna DClua ESarma AMurta L(2022)Dominoes: An Interactive Exploratory Data Analysis Tool for Software RelationshipsIEEE Transactions on Software Engineering10.1109/TSE.2020.298824148:2(377-396)Online publication date: 1-Feb-2022
https://doi.org/10.1109/TSE.2020.2988241
Bradley NFritz THolmes R(2022)Sources of software development task frictionEmpirical Software Engineering10.1007/s10664-022-10187-627:7Online publication date: 1-Dec-2022
https://dl.acm.org/doi/10.1007/s10664-022-10187-6
Zhang JWang LZheng ZTao X(2022)Social Community Evolution Analysis and Visualization in Open Source Software ProjectsWeb Information Systems Engineering – WISE 202210.1007/978-3-031-20891-1_4(38-45)Online publication date: 7-Nov-2022
https://doi.org/10.1007/978-3-031-20891-1_4
Almarimi NOuni AChouchen MMkaouer M(2022)Improving the detection of community smells through socio‐technical and sentiment analysisJournal of Software: Evolution and Process10.1002/smr.250535:6Online publication date: 2-Sep-2022
https://dl.acm.org/doi/10.1002/smr.2505
Wang YRedmiles D(2021)IIAG: a data-driven and theory-inspired approach for advising how to interact with new remote collaborators in OSS teamsAutomated Software Engineering10.1007/s10515-021-00283-028:2Online publication date: 24-May-2021
https://dl.acm.org/doi/10.1007/s10515-021-00283-0
Pashchenko IVu DMassacci FLigatti JOu XKatz JVigna G(2020)A Qualitative Study of Dependency Management and Its Security ImplicationsProceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security10.1145/3372297.3417232(1513-1531)Online publication date: 30-Oct-2020
https://dl.acm.org/doi/10.1145/3372297.3417232
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Table of Conten