A Talk given at the IEEE Mining Software Repositories conference collocated with ICSE'09 You can find more details on the paper

1. From Work to Word:
How Do So/ware
Developers Describe
Their Work?
Walid Maalej, Technische Universität München
Hans‐Jörg Happel, FZI Research Center Karlsruhe

2. Outline
1 MoMvaMon
2 Research SeKng
3 Research Results
4 Conclusion and Next Steps
© W. Maalej, Mai 09 From Work To Word 2

3. WHY Do Developers Describe Their Work?
RaMonale Capture 1 ReflecMon & Experience Capture
• Remember status when conGnuing postponed work
• Log decisions and why
they have been taken • Capture experiences on problems and their soluGons
in this parGcular way
• Reason about previous 2
decisions by reading Purposes of Work Status Awareness
the work descripGons
DescripMon • Help collaborators in
4 distributed projects to
know about the status
of work
Controlling
• Provide a short, human
• Report work done in a period of Gme
readable summary of
• Control effort and cost (e.g. for adding one feature) 3 changes
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4. WHERE Do Developers Describe Their Work?
Personal note
Commit message ArMfacts
Issue report comments
including
work
descripMons
Social media Time sheet
But: How do developers describe work?
This is the goal of our exploraMve study
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5. Outline
1 MoMvaMon
2 Research SeKng
3 Research Results
4 Conclusion and Next Steps
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6. Our Research QuesMons On Work DescripMon
Content Analysis Time Metadata
 Vocabulary usage,  Session duraMon and
similariGes and terms descripGon frequency
frequency
 Logging day Mme and
 Work categories and relaGon to descripGon
proporGon of acGviGes quality
 DescripGon pa_erns and  Pseudo descripGons,
common templates only Gme metadata
 Referenced arGfacts  Required effort
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7. Data Sets Collected in Different Contexts
Data set Summary Number of Number of Represented
developers descripMons period
Developers’ Gme
8 years
MyComp cards in a German 25 38,045
(2001 – 2009)
soWware company
Commit messages of 15 years
Apache 1,949 747,403
all Apache projects (1994 – 2009)
Subjects‘ personal
notes in a field study 10 days
Eureka 21 115
with 5 European (2008)
companies
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8. Outline
1 MoMvaMon
2
3 Research Results
4 Conclusion and Next Steps
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9. Vocabulary Usage and Term Frequency
Rank
Mycomp German Apache Eureka English
Term
Not 2 17 4 1 29
For/ Since 7 184 23 212 906
Change 3 911 26 214 333
Review 1 >10,000 13 - 2,275
Problem 24 461 10 9 239
Now 12 576 14 58 808
Done 17 4,454 300 59 606
Work descripMons extensively include:
• NegaMve formulaMons
• JusMficaMons and argumentaMons
• Problems that caused the work
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10. Described Categories of Work
• Not only acMviMes “with work products” are described
• Granularity is more “ediMng‐” rather than acMvity‐oriented
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11. Work DescripMon Pa_erns
1. ArgumentaMon Pa_erns
Pa#ern ::= <Ac-on> 'concerning' | 'performed on' <Ar-fact>
'for'|'since'|'because' <Cause descrip-on>|<Reference to cause>
2. Status Pa_erns
Pa#ern ::= <Ar-fact> 'works now'
Pa#ern ::= 'Problem'|'Bug' <Reference to issue>|<Problem descrip-on>
'fixed'|'solved' <Solu-on> ['reviewed with' <Colleague>]
3. Experience Sharing Pa_erns
Pa#ern ::= 'If' <Context> 'then' <Experience>
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12. CreaMon Time and Session DuraMon
• Delayed descripMons are shorter than immediate ones
• The mean of session duraMons is between 30 and 90 min.
• Developers entered between 8 and 12 descripMons per work day
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13. Work DescripMon Quality and Effort
10% of pseudo descripMons
• Developers don’t have Mme or moMvaMon to describe 10% of the sessions
• 3 – 6% of developer Mme is spent for describing work (30 min. / day )
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14. Outline
1 MoMvaMon
2 Research SeKng
3 Research Results
4 Conclusion and Next Steps
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15. Summary of the Talk
1
We conducted an exploratory study on how developers describe
their work using real world data
2
A considerable amount of effort is spent to describe work, with
oWen empty or pseudo‐descripGons: automaGon would pay off
3
We found similariGes in descripGon contents: part of the
descripGon can be automated by observing interacMons
4
We found similariGes in the Mme metadata: the work day can be
sessionized automaGcally
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16. Open Source Plaqorm: TeamWeaver
www.teamweaver.org
© W. Maalej, Mai 09 PotenMals and Challenges of RS in SD 16

17. © W. Maalej, Mai 09 From Work To Word 17

18. You are welcome to join!
Contact:
Walid Maalej Hans‐Jörg Happel
TUM FZI
maalejw@cs.tum.edu happel@fzi.de
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