Leadership: 1The analysis data consist of 360 Decision Episodes … · 2010-11-06 · We analyzed...
Transcript of Leadership: 1The analysis data consist of 360 Decision Episodes … · 2010-11-06 · We analyzed...
Investigating the Dynamics ofFLOSS Development Teams Investigating the Dynamics ofFLOSS Development Teams
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Andrea
Wiggins
Keisuke Inoue
Sarah Harwell
Steven Rowe
Nancy
McCracken
What are the dynamics through which self-organizing, distributed teams develop and work?Research partially funded by NSF grant 05–27457, with prior support from 03–41475 & 04–14468
Na LiQing Li
Kangning Wei
Robert Heckman
U. Yeliz Eseryel
Elizabeth Liddy
James Howison
Kevin Crowston
Eileen Allen
Michael Scialdone
Key
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To D
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Key
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To D
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Cita
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Cita
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Part
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Part
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• Barbara Scozzi, Politecnico di Bari, Italy• Megan Conklin, Elon University, North Carolina
Scozzi, B., Crowston, K., Eseryel, U. Y., & Li, Q. (Accepted). Shared mental models among open source software developers. Hawai'i International Conference on System Science, Big Island, Hawai'i, Jan 2008.
Crowston, K., Wei, K., Li, Q., Eseryel, U. Y., & Howison, J. (2007) Self-organization of teams in free/libre open source software development. Information and Software Technology Journal, Special issue on "Understanding the Social Side of Software Engineering, Qualitative Software Engineering Research", vol. 49, p. 564. Published.
Heckman, R., Crowston, K., Eseryel, Y., Allen, E., & Li, Q. (2007) Emergent Decision-making Practices in Free/Libre Open Source Software (FLOSS) Development Teams. Third International Conference on Open Source Systems, IFIP 2.13 Working Conference, Limerick, Ireland. Published.
Heckman, R., Crowston, K., Misiolek, N. & Eseryel, Y. (2007) Emergent leadership in self-organizing virtual teams. Proceedings of the International Conference on Information Systems (ICIS 2007), Montreal, Quebec, Canada, Dec 2007. Accepted with revisions.
Crowston, K., Conklin, M. & Howison, J. (2007) A Proposed Data and Analysis Archive for Research on Free and Open Source Software and Its Development. Third International Conference on e-Social Science. Accepted as poster.
Crowston, K. (2007) The bug fixing process in proprietary and free/libre open source software: A coordination theory analysis, bibl. M. E. Sharpe, Inc, Armonk, NY. Book Published of Collection: Grover, V. and Markus, M. L., Business Process Transformation.
Plus 6 publications from 2006
Plan
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• Shared Mental Models: Transcripts of 27 interviews with members of the open-source community are being analyzed through cognitive mapping, and the integration of Natural Language Processing is being considered. Results to date indicate a degree of sharing of mental models, and we are looking for casual links within the community.
• Leadership: A detailed coding scheme has been developed that considers the concepts of first and second order leadership, including respective indicators. This code book is currently in the process of validation and the subsequent content analysis is planned for inclusion in the doctoral dissertation of one of our graduate assistants.
• Group Maintenance: A detailed coding scheme drawing on politeness theory, organizational citizenship behavior, and social presence theory literature has been developed. The code book is being validated and refined through a pilot analysis on episodic data from two open-source teams. Once finalized, our content analysis will continue on additional episodic data.
• We have developed National Language Processing (NLP) text extraction rules to reliably identify 63-72% of decision triggers, and 71-85% of decision announcements.
• There is a positive relationship between the level of participation and group effectiveness, with effective projects exhibiting high involvement from peripheral members.
• Some open-source projects that appear decentralized are actually centralized, but with individuals at the center changing their roles over time.
• In studying shared-mental models, norms and rules are highly shared within groups. However, it seems that tenure in projects can cause those to change within individuals, indicating dynamic processes over time.
• Second-level leadership in open-source teams is enabled by first-level leadership. First-level includes task coordination and contribution, group maintenance, and boundary spanning; while second-level is behavior that influences changes in structure that guides group action.
Multiple incompatibleoverlapping repositories
Projectselection
Datacollection
Datacleaning Data storage
Analysis
FLOSSMole
Publication
Prod
ucts
Prod
ucts
• floss.syr.edu website with copies of papers and analyses• FLOSSmole, a collaborative project to gather, share and store comparable
data and analyses of free and open source software development for academic research.
2Natural language processing for content analysis
After preprocessing, manual processes were automated by using manual coding as the Gold Standard• IM projects data were analyzed for decision announcements and triggers with the sentence as a unit of analysis • Manual coding was validated by 2 or 3 coders, and used as training data for rule-writing and evaluation of results• Rules utilize NLP features such as morphology, word form, syntax, semantics, discourse, and pragmatics
Automating manual coding processes
Automatic Coding - Decison Episodes
Fire
aMSN : doc E01.NT5126frametype = entity trigger = Today I received aproposal for a new logo for the website.
aMSN
GAIM: docNT217frametype = entityDecision-Announcement = I disagree ( which is why Icommitted the change after KingAnt suggested it ) .
Decision Triggers
DecisionAnnouncements
1-19 14:51:41"
o-Realname="Steven Garrity"
Tue, 2004-08-17 at 17:15, Steven Garrity wrote:">
f Retail on Ink & Toner - Free Shipping and Free Gift.
--
Sectionsidentified
Paragraphsseparated
Metadataidentified
<?xml version="1.0"?><DOC><TEXT><SECTION type="email-message" List-Id="24" Msg-Id="9259245" Post-Id="3744"
Thread-Id="1285" Child-Of="3741" Depth="3" Post-Date="2004-08-18 08:30:00" Posters-Realname="Matthew Keller" Date-Collected="2005-1 Datasource-Id="26" Replying-T Message-Subject="Re: Gaim Sounds - First Draft"> <SECTION type="from">Matthew Keller</SECTION> <SECTION type="replying-to">Steven Garrity</SECTION> <SECTION type="subject">Re: Gaim Sounds - First Draft</SECTION> <SECTION type="date">2004-08-18 08:30:00</SECTION>
I think it goes without saying that your sounds are better than the defaults. I doubt anyone who's checked them out would disagree.
Then again, I think that llama's bleating would be better on the ears than the default AOLish sounds, but that's not to diminish the sounds you and Brad have produced.
<SECTION type="quote" level="1" attribution="On <SECTION type="quote" level="2" attribution="Tyler Lane wrote:"> I totally love the sounds. Great work. However, after a couple days of using them, I find that it is occasionally hard to distinguish the sounds with music playing in the background. Perhaps something with a higher pitch would make it easier to hear the sounds with music playing. </SECTION>
Glad to hear you like them Tyler. They are someone low in volume. We could probably boost the levels for final versions.
Other opinions? I though we'd been swamped! :-)
Steven
<SECTION type="sourceforge-signature"> -------------------------------------------------------
SF.Net email is sponsored by Shop4tech.com-Lowest price on Blank Media 100pk Sonic DVD-R 4x for only $29 -100pk Sonic DVD+R for only $33 Save 50% of http://www.shop4tech.com/z/Inkjet_Cartridges/9_108_r285 ----------------------------------------------- Gaim-devel mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/gaim-devel </SECTION> </SECTION> <SECTION type="tagline">
Matthew Keller signat-url: http://mattwork.potsdam.edu/signat-url/ "No one ever says, "I can't read that ASCII E-mail you sent me."" </SECTION></SECTION></TEXT></DOC>
Preprocessed message in xml format
• Identification ofmajor sections ofan email message,eg header,signature, tagline
• removal of “>”symbols thatinterfere withsentence detection
• identification ofquote levelsembedded inmessages andauthor of thequoted snippets.
All - analysis by each marked sentenceGroup - analysis by each decision group of sentencesSM - software modification decision episodesSt - strategic decision episodesDA - Decision Announcements
Key Metrics
Precision - % marked that agree with Gold StandardRecall - % of Gold Standard that are markedUtility - % marked that assist researcher in understanding Decision Episodes
Results on IM Projects
All
Gro
ups
SM St
0%20%40%60%
80%100%
Precision - DA
All
Gro
ups
SM S t
0%20%40%60%80%
100%
Precision - Triggers
All
Gro
ups
SM St
0%20%40%60%80%
100%
Recall - DA
All
Gro
ups
SM S t
0%20%40%60%80%
100%
Recall - Triggers
GaimaMSNFire
All
Gro
ups
SM St
0%20%40%60%
80%100%
Utility - DA
All
Gro
ups
SM S t
0%20%40%60%80%
100%
Utility - Triggers
Findings: The more successfulprojects exhibited higherperipheral involvement in
their decision making processesthan the less successful projects.
Decision making processes in FLOSS teamsWe analyzed the email listservs and fora for 6 FLOSS project teams using Decision Episodes as the unit of analysis.The analysis data consist of 360 Decision Episodes from the beginning, middle, and end periods of email interactions.1We analyz
analys
Linear
Loop-back2.3%
NormativeNormative
28.7%
22.5%
30 %
25 %
20 %
15 %
10 %
5 %
0 %
No decision
Short-cut
No development
No selection
All phases
webERPOFbizCompiereIndividualEnterprise Resource PlanningSystem (ERP)
FireaMSNGaimCompanyInstant Messaging Client (IM)
More Successful--->Less Successful
Team SuccessIntended UsersProduct ComplexityCase Selection
Coding Scheme IDecision Episode
TT DD DD DD DADA
Descriptive StatisticsDescriptive Statistics•Length of Episode (N of messages)• Duration of Episodes (N of days)•N of Participants (Admin, Developer, User)
DecisionEpisode
•Trigger Type•(Bug, Feature, Problem…)•Triggering Person•(Admin, Developer, User)
•Decision Announcement Type•(Code change needed, Code change committed)•Decision Announcer•(Core [Admin, Developer], Periphery [User])
•Decision Episode Type•(Software-modification*;Strategic )
I-IdentificationI-Identification II-DevelopmentII-Development III-SelectionIII-Selection IV-Announcement IV-Announcement
1a:decisionrecognition1b:diagonosis
2a:solution analysis2b:solution search2c:solution design
3a-1: solution evaluation-opinion 3a-2:solution evaluation-action3b: solution confirmation
4:decisionannouncement
Unit of Coding:Functional Move
No decision 9.3%
Short-cut 28.3%
No Development 0.8%
No Selection 30.6%
All phases 31%
Identification Development Selection Announcement
Identification Development Selection AnnouncementLinear (41.9%)
Loop-back (59.1%) Identification Development Selection Announcement
Decision Styles
Coding Scheme II
Normative
Decision Making
Process
0
1020
30
4050
60
Autocratic/Autonomous
Independent/Autonomous
Deliberate/Autonomous
Democratic/Autonomous
TrulyCollaborative/Consensus
Gaim
aMSN
Fire
010
203040
5060
Autocratic/Autonomous
Independent/Autonomous
Deliberate/Autonomous
Democratic/Autonomous
TrulyCollaborative/Consensus
Compiere
OFbiz
WebERP
Level ofsuccess
IM
ERP
Level ofsuccess
Findings: Generally, the decision making processes
in the open source projects are not normative.
We are reviewing the research on FLOSS development and use in an effort to assess the state of the literature. We have reviewed 586 papers in the first round, which were collected from Web of Science, ABI/Inform, journal special issues, AOM and AIS conferences, IntOSS (IFIP) conferences, ICSE workshops and opensource.mit.edu.
We are currently organizing the review around an input-mediator-output-input (IMOI) model. The 295 papers that were found both empirical and relevant are being categorized into issues pertaining to
- inputs (member characteristics, technology use and project characteristics)- processes (social processes, software development processes and IT-related processes)- emergent states (social states, task related states and IT-related states)- output (team performance and FLOSS implementation)1reviewing
ewes, AO
ntly und bmemes (sont sta
IMOI model of FLOSS literature review
Socialization: What processes to members go through in becoming a part of an open-source team, and how are different levels of membership defined?
Decision Making: How are decisions made in matrix environment such as open-source teams where leadership is not always clearly defined?
Leadership Building: How is leadership defined in open-source teams, and how do members rise into such positions?
Coordination/Collaboration: What are the dynamics of interaction within open-source teams where roles are not always clearly defined?
Team Maintenance: How do open-source teams form, and what keeps these teams together?Knowledge Management: Where do open-source teams store their group knowledge, and how is it
accessed by members?Trust: How is trust formed within open-source teams?Conflict: What types of conflicts arise within open-source teams, and how are such conflicts resolved?Level of Commitment: Considering the often voluntary nature of open-source teams, what amounts of
commitment do members invest?
Process
OutputTeam PerformanceMeasure
Softwareimplementation
Input
Member characteristics
Demographics,company, discontinuities,motivation, skills
Technology use
Types of technology used, technology features
Project characteristics
Software type, license types
Software development process
Planning, requirements, coding, release, maintenance, project management
IT-related process
Technology collaboration
Emergent States
Social statesTrust, cohesion, conflict,commitment level, interaction structure
IT-related states
Shared norms of IT use
Task-related states
Member roles, individual contributions, development status, shared understanding, evolution of the software
Social processesSocialization, decision making, leadership building, coordination/collaboration, team maintenance, knowledge management
Engagement with FLOSS community advisory boardRese
arch
Pla
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sear
ch P
lan
2006 2007 2008
Manual examination of transcripts to locate
evidence of concepts
Refining applicationof NLP techniques
Utilizing NLP , SNAand Code metrics on large sample
Specialization of NLPtechniques for novel text
types (e.g., chat logs)
Exploration of dynamic Social Network Analysis
techniques
Manual refiningof identified
features according to conceptual framework
Extraction of code and SNA metrics from
growing sample
Clustering of projects through optimal pattern
matching of timelines
Comparison of dynamics across
projects to provide
generalizableknowledge
1
2
Demographicdata
Source Code
Interactionlogs
Plans and procedures
Manual and NLP-based
contentanalysis
SNA
Code metrics
Cognitivemaps
Roles
Norms and rules
Contribution and coordination
Processmaps
Event and developerdynamics
Raw data
Stage 1
analysis
Stage 2
analysis
Stage 3
analysis
Teamoutcomes
Ana
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s Pl
anA
naly
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Plan
Data IntegrationData Integration
Raw DataRaw Data
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