SlideShare ist ein Scribd-Unternehmen logo
1 von 15
Downloaden Sie, um offline zu lesen
N/A
Katja Kevic, Sebastian C. Müller, Thomas Fritz, and Harald C. Gall
Collaborative Bug Triaging
CHASE „13, San Francisco – May 25, 2013
Motivation
How to support developers for collaborative bug triaging?
2
bug
bug
bug
bug bug
bug
Related Work
• Source code analysis [e.g. MCDonald 2000]
• «One out of four bug reports required
dicussion and negotiation..» [Carstensen,
1995]
3J. Anvik, L. Hiew, and G. C. Murphy, “Who should fix this bug?,” in Proceedings of the 28th International Conference on Software Engineering, ICSE ‟06.
D. W. McDonald and M. S. Ackerman, “Expertise recommender: a flexible recommendation system and architecture,” in Proceedings of the 2000 ACM Conference on Computer Supported Cooperative Work, CSCW ‟00,
Carstensen, P. H., Sorensen, C. and Tuikka, T., Let's talk about bugs! Scandanavian Journal of Information Systems, 1995. 7,1 33-54.
• Information Retrieval or Machine Learning
[e.g. Anvik 2006]
Related Work
• Source code analysis [e.g. MCDonald 2000]
• «One out of four bug reports required
dicussion and negotiation..» [Carstensen,
1995]
4J. Anvik, L. Hiew, and G. C. Murphy, “Who should fix this bug?,” in Proceedings of the 28th International Conference on Software Engineering, ICSE ‟06.
D. W. McDonald and M. S. Ackerman, “Expertise recommender: a flexible recommendation system and architecture,” in Proceedings of the 2000 ACM Conference on Computer Supported Cooperative Work, CSCW ‟00,
Carstensen, P. H., Sorensen, C. and Tuikka, T., Let's talk about bugs! Scandanavian Journal of Information Systems, 1995. 7,1 33-54.
• Information Retrieval or Machine Learning
[e.g. Anvik 2006]
Collaborative Bug
Triaging
Collaboration
IR + change set analysis
Allow change set investigation
5
Information Retrieval –
Finding similar Bugs
0.78
0.72
0.71
cosine similarity
threshold
> 0.7
6
Information Retrieval –
Finding similar Bugs
0.78
cosine similarity
threshold
7
> 0.75
Information Retrieval –
Finding similar Bugs
0.78
0.72
0.71
cosine similarity
threshold
8
> 0.6
Change Set Analysis –
Finding Potential Experts
0.71
0.78
0.72
5.46
1.44
4.28
9
Developer 1
Developer 2
Developer 3
7
Change set 1
2
Change set 2
2
Change set 3
4
Change set 4
Similar bug 1
Similar bug 2
Similar bug 3
Prototype: Analysis
10
Prototype: Context
11
Collaboration
12
Evaluation
• Applied in our own software projects
• Future work: user studies
13
Summary
14
Collaboration
IR + change set analysis
Allow change set investigation
For more details visit:
http://www.ifi.uzh.ch/seal/people/kevic/researchprojects/CollabBugTriaging.html
References
15
J. Anvik, L. Hiew, and G. C. Murphy, “Who should fix this bug?,” in
Proceedings of the 28th International Conference on Software Engineering,
ICSE ‟06, (New York, NY, USA), pp. 361–370, ACM, 2006.
D. W. McDonald and M. S. Ackerman, “Expertise recommender: a
flexible recommendation system and architecture,” in Proceedings of
the 2000 ACM Conference on Computer Supported Cooperative Work,
CSCW ‟00, (New York, NY, USA), pp. 231–240, ACM, 2000.
Carstensen, P. H., Sorensen, C. and Tuikka, T., Let's talk about
bugs! Scandanavian Journal of Information Systems, 1995. 7,1 33-54.

Weitere ähnliche Inhalte

Ähnlich wie Collaborative Bug Triaging

Analyzing Big Data's Weakest Link (hint: it might be you)
Analyzing Big Data's Weakest Link  (hint: it might be you)Analyzing Big Data's Weakest Link  (hint: it might be you)
Analyzing Big Data's Weakest Link (hint: it might be you)HPCC Systems
 
Big Data: the weakest link
Big Data: the weakest linkBig Data: the weakest link
Big Data: the weakest linkCS, NcState
 
Getting (and giving) credit for all that we do
Getting (and giving) credit for all that we doGetting (and giving) credit for all that we do
Getting (and giving) credit for all that we domhaendel
 
The Art and Science of Analyzing Software Data
The Art and Science of Analyzing Software DataThe Art and Science of Analyzing Software Data
The Art and Science of Analyzing Software DataCS, NcState
 
Designing at the Intersection of HCI & AI: Misinformation & Crowdsourced Anno...
Designing at the Intersection of HCI & AI: Misinformation & Crowdsourced Anno...Designing at the Intersection of HCI & AI: Misinformation & Crowdsourced Anno...
Designing at the Intersection of HCI & AI: Misinformation & Crowdsourced Anno...Matthew Lease
 
Lies, Damned Lies and Software Analytics: Why Big Data Needs Rich Data
Lies, Damned Lies and Software Analytics:  Why Big Data Needs Rich DataLies, Damned Lies and Software Analytics:  Why Big Data Needs Rich Data
Lies, Damned Lies and Software Analytics: Why Big Data Needs Rich DataMargaret-Anne Storey
 
Architectural Design of a Clinical Decision Support System for Clinical Triag...
Architectural Design of a Clinical Decision Support System for Clinical Triag...Architectural Design of a Clinical Decision Support System for Clinical Triag...
Architectural Design of a Clinical Decision Support System for Clinical Triag...Luis Felipe Tabares Pérez
 
Improving Software Maintenance using Unsupervised Machine Learning techniques
Improving Software Maintenance using Unsupervised Machine Learning techniquesImproving Software Maintenance using Unsupervised Machine Learning techniques
Improving Software Maintenance using Unsupervised Machine Learning techniquesValerio Maggio
 
A Systems Approach To Qualitative Data Management And Analysis
A Systems Approach To Qualitative Data Management And AnalysisA Systems Approach To Qualitative Data Management And Analysis
A Systems Approach To Qualitative Data Management And AnalysisMichele Thomas
 
Synergy of Human and Artificial Intelligence in Software Engineering
Synergy of Human and Artificial Intelligence in Software EngineeringSynergy of Human and Artificial Intelligence in Software Engineering
Synergy of Human and Artificial Intelligence in Software EngineeringTao Xie
 
Advancing Foundation and Practice of Software Analytics
Advancing Foundation and Practice of Software AnalyticsAdvancing Foundation and Practice of Software Analytics
Advancing Foundation and Practice of Software AnalyticsTao Xie
 
Dagstuhl14 intro-v1
Dagstuhl14 intro-v1Dagstuhl14 intro-v1
Dagstuhl14 intro-v1CS, NcState
 
Leveraging HPC Resources to Improve the Experimental Design of Software Analy...
Leveraging HPC Resources to Improve the Experimental Design of Software Analy...Leveraging HPC Resources to Improve the Experimental Design of Software Analy...
Leveraging HPC Resources to Improve the Experimental Design of Software Analy...Chakkrit (Kla) Tantithamthavorn
 
The Science of Data Science
The Science of Data Science The Science of Data Science
The Science of Data Science James Hendler
 
system analysis and design chapter 1 Kendall & Kendall
system analysis and design chapter 1 Kendall & Kendallsystem analysis and design chapter 1 Kendall & Kendall
system analysis and design chapter 1 Kendall & KendallDana dia
 
Computational Thinking in the Workforce and Next Generation Science Standards...
Computational Thinking in the Workforce and Next Generation Science Standards...Computational Thinking in the Workforce and Next Generation Science Standards...
Computational Thinking in the Workforce and Next Generation Science Standards...Josh Sheldon
 
Introduction to Data and Computation: Essential capabilities for everyone in ...
Introduction to Data and Computation: Essential capabilities for everyone in ...Introduction to Data and Computation: Essential capabilities for everyone in ...
Introduction to Data and Computation: Essential capabilities for everyone in ...Kim Flintoff
 
Machine Learning Pitfalls
Machine Learning Pitfalls Machine Learning Pitfalls
Machine Learning Pitfalls Dan Elton
 

Ähnlich wie Collaborative Bug Triaging (20)

Analyzing Big Data's Weakest Link (hint: it might be you)
Analyzing Big Data's Weakest Link  (hint: it might be you)Analyzing Big Data's Weakest Link  (hint: it might be you)
Analyzing Big Data's Weakest Link (hint: it might be you)
 
Big Data: the weakest link
Big Data: the weakest linkBig Data: the weakest link
Big Data: the weakest link
 
Getting (and giving) credit for all that we do
Getting (and giving) credit for all that we doGetting (and giving) credit for all that we do
Getting (and giving) credit for all that we do
 
The Art and Science of Analyzing Software Data
The Art and Science of Analyzing Software DataThe Art and Science of Analyzing Software Data
The Art and Science of Analyzing Software Data
 
Designing at the Intersection of HCI & AI: Misinformation & Crowdsourced Anno...
Designing at the Intersection of HCI & AI: Misinformation & Crowdsourced Anno...Designing at the Intersection of HCI & AI: Misinformation & Crowdsourced Anno...
Designing at the Intersection of HCI & AI: Misinformation & Crowdsourced Anno...
 
Lies, Damned Lies and Software Analytics: Why Big Data Needs Rich Data
Lies, Damned Lies and Software Analytics:  Why Big Data Needs Rich DataLies, Damned Lies and Software Analytics:  Why Big Data Needs Rich Data
Lies, Damned Lies and Software Analytics: Why Big Data Needs Rich Data
 
Lopez
LopezLopez
Lopez
 
Architectural Design of a Clinical Decision Support System for Clinical Triag...
Architectural Design of a Clinical Decision Support System for Clinical Triag...Architectural Design of a Clinical Decision Support System for Clinical Triag...
Architectural Design of a Clinical Decision Support System for Clinical Triag...
 
Improving Software Maintenance using Unsupervised Machine Learning techniques
Improving Software Maintenance using Unsupervised Machine Learning techniquesImproving Software Maintenance using Unsupervised Machine Learning techniques
Improving Software Maintenance using Unsupervised Machine Learning techniques
 
A Systems Approach To Qualitative Data Management And Analysis
A Systems Approach To Qualitative Data Management And AnalysisA Systems Approach To Qualitative Data Management And Analysis
A Systems Approach To Qualitative Data Management And Analysis
 
Synergy of Human and Artificial Intelligence in Software Engineering
Synergy of Human and Artificial Intelligence in Software EngineeringSynergy of Human and Artificial Intelligence in Software Engineering
Synergy of Human and Artificial Intelligence in Software Engineering
 
Advancing Foundation and Practice of Software Analytics
Advancing Foundation and Practice of Software AnalyticsAdvancing Foundation and Practice of Software Analytics
Advancing Foundation and Practice of Software Analytics
 
Dagstuhl14 intro-v1
Dagstuhl14 intro-v1Dagstuhl14 intro-v1
Dagstuhl14 intro-v1
 
Contextual Analysis
Contextual AnalysisContextual Analysis
Contextual Analysis
 
Leveraging HPC Resources to Improve the Experimental Design of Software Analy...
Leveraging HPC Resources to Improve the Experimental Design of Software Analy...Leveraging HPC Resources to Improve the Experimental Design of Software Analy...
Leveraging HPC Resources to Improve the Experimental Design of Software Analy...
 
The Science of Data Science
The Science of Data Science The Science of Data Science
The Science of Data Science
 
system analysis and design chapter 1 Kendall & Kendall
system analysis and design chapter 1 Kendall & Kendallsystem analysis and design chapter 1 Kendall & Kendall
system analysis and design chapter 1 Kendall & Kendall
 
Computational Thinking in the Workforce and Next Generation Science Standards...
Computational Thinking in the Workforce and Next Generation Science Standards...Computational Thinking in the Workforce and Next Generation Science Standards...
Computational Thinking in the Workforce and Next Generation Science Standards...
 
Introduction to Data and Computation: Essential capabilities for everyone in ...
Introduction to Data and Computation: Essential capabilities for everyone in ...Introduction to Data and Computation: Essential capabilities for everyone in ...
Introduction to Data and Computation: Essential capabilities for everyone in ...
 
Machine Learning Pitfalls
Machine Learning Pitfalls Machine Learning Pitfalls
Machine Learning Pitfalls
 

Kürzlich hochgeladen

Objectives n learning outcoms - MD 20240404.pptx
Objectives n learning outcoms - MD 20240404.pptxObjectives n learning outcoms - MD 20240404.pptx
Objectives n learning outcoms - MD 20240404.pptxMadhavi Dharankar
 
Executive Directors Chat Initiating Equity for Impact.pdf
Executive Directors Chat  Initiating Equity for Impact.pdfExecutive Directors Chat  Initiating Equity for Impact.pdf
Executive Directors Chat Initiating Equity for Impact.pdfTechSoup
 
DBMSArchitecture_QueryProcessingandOptimization.pdf
DBMSArchitecture_QueryProcessingandOptimization.pdfDBMSArchitecture_QueryProcessingandOptimization.pdf
DBMSArchitecture_QueryProcessingandOptimization.pdfChristalin Nelson
 
HackerOne X IoT Lab Bug Bounty 101 with Encryptsaan & IoT Lab at KIIT Univers...
HackerOne X IoT Lab Bug Bounty 101 with Encryptsaan & IoT Lab at KIIT Univers...HackerOne X IoT Lab Bug Bounty 101 with Encryptsaan & IoT Lab at KIIT Univers...
HackerOne X IoT Lab Bug Bounty 101 with Encryptsaan & IoT Lab at KIIT Univers...kumarpriyanshu81
 
Jordan Chrietzberg In Media Res Media Component
Jordan Chrietzberg In Media Res Media ComponentJordan Chrietzberg In Media Res Media Component
Jordan Chrietzberg In Media Res Media ComponentInMediaRes1
 
LEVERAGING SYNERGISM INDUSTRY-ACADEMIA PARTNERSHIP FOR IMPLEMENTATION OF NAT...
LEVERAGING SYNERGISM INDUSTRY-ACADEMIA PARTNERSHIP FOR IMPLEMENTATION OF  NAT...LEVERAGING SYNERGISM INDUSTRY-ACADEMIA PARTNERSHIP FOR IMPLEMENTATION OF  NAT...
LEVERAGING SYNERGISM INDUSTRY-ACADEMIA PARTNERSHIP FOR IMPLEMENTATION OF NAT...pragatimahajan3
 
18. Training and prunning of horicultural crops.pptx
18. Training and prunning of horicultural crops.pptx18. Training and prunning of horicultural crops.pptx
18. Training and prunning of horicultural crops.pptxUmeshTimilsina1
 
Jason Potel In Media Res Media Component
Jason Potel In Media Res Media ComponentJason Potel In Media Res Media Component
Jason Potel In Media Res Media ComponentInMediaRes1
 
Basic cosmetics prepared by my student Mr. Balamurugan, II Maths, 2023-2024
Basic cosmetics prepared by my student Mr. Balamurugan, II Maths, 2023-2024Basic cosmetics prepared by my student Mr. Balamurugan, II Maths, 2023-2024
Basic cosmetics prepared by my student Mr. Balamurugan, II Maths, 2023-2024St.John's College
 
BÀI TẬP BỔ TRỢ 4 KĨ NĂNG TIẾNG ANH LỚP 8 - CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC ...
BÀI TẬP BỔ TRỢ 4 KĨ NĂNG TIẾNG ANH LỚP 8 - CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC ...BÀI TẬP BỔ TRỢ 4 KĨ NĂNG TIẾNG ANH LỚP 8 - CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC ...
BÀI TẬP BỔ TRỢ 4 KĨ NĂNG TIẾNG ANH LỚP 8 - CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC ...Nguyen Thanh Tu Collection
 
Paul Dobryden In Media Res Media Component
Paul Dobryden In Media Res Media ComponentPaul Dobryden In Media Res Media Component
Paul Dobryden In Media Res Media ComponentInMediaRes1
 
CHUYÊN ĐỀ ÔN THEO CÂU CHO HỌC SINH LỚP 12 ĐỂ ĐẠT ĐIỂM 5+ THI TỐT NGHIỆP THPT ...
CHUYÊN ĐỀ ÔN THEO CÂU CHO HỌC SINH LỚP 12 ĐỂ ĐẠT ĐIỂM 5+ THI TỐT NGHIỆP THPT ...CHUYÊN ĐỀ ÔN THEO CÂU CHO HỌC SINH LỚP 12 ĐỂ ĐẠT ĐIỂM 5+ THI TỐT NGHIỆP THPT ...
CHUYÊN ĐỀ ÔN THEO CÂU CHO HỌC SINH LỚP 12 ĐỂ ĐẠT ĐIỂM 5+ THI TỐT NGHIỆP THPT ...Nguyen Thanh Tu Collection
 
(Part 2) CHILDREN'S DISABILITIES AND EXCEPTIONALITIES.pdf
(Part 2) CHILDREN'S DISABILITIES AND EXCEPTIONALITIES.pdf(Part 2) CHILDREN'S DISABILITIES AND EXCEPTIONALITIES.pdf
(Part 2) CHILDREN'S DISABILITIES AND EXCEPTIONALITIES.pdfMJDuyan
 
Healthy Minds, Flourishing Lives: A Philosophical Approach to Mental Health a...
Healthy Minds, Flourishing Lives: A Philosophical Approach to Mental Health a...Healthy Minds, Flourishing Lives: A Philosophical Approach to Mental Health a...
Healthy Minds, Flourishing Lives: A Philosophical Approach to Mental Health a...Osopher
 
Transdisciplinary Pathways for Urban Resilience [Work in Progress].pptx
Transdisciplinary Pathways for Urban Resilience [Work in Progress].pptxTransdisciplinary Pathways for Urban Resilience [Work in Progress].pptx
Transdisciplinary Pathways for Urban Resilience [Work in Progress].pptxinfo924062
 
The Emergence of Legislative Behavior in the Colombian Congress
The Emergence of Legislative Behavior in the Colombian CongressThe Emergence of Legislative Behavior in the Colombian Congress
The Emergence of Legislative Behavior in the Colombian CongressMaria Paula Aroca
 
PART 1 - CHAPTER 1 - CELL THE FUNDAMENTAL UNIT OF LIFE
PART 1 - CHAPTER 1 - CELL THE FUNDAMENTAL UNIT OF LIFEPART 1 - CHAPTER 1 - CELL THE FUNDAMENTAL UNIT OF LIFE
PART 1 - CHAPTER 1 - CELL THE FUNDAMENTAL UNIT OF LIFEMISSRITIMABIOLOGYEXP
 
4.9.24 Social Capital and Social Exclusion.pptx
4.9.24 Social Capital and Social Exclusion.pptx4.9.24 Social Capital and Social Exclusion.pptx
4.9.24 Social Capital and Social Exclusion.pptxmary850239
 
16. Discovery, function and commercial uses of different PGRS.pptx
16. Discovery, function and commercial uses of different PGRS.pptx16. Discovery, function and commercial uses of different PGRS.pptx
16. Discovery, function and commercial uses of different PGRS.pptxUmeshTimilsina1
 

Kürzlich hochgeladen (20)

Objectives n learning outcoms - MD 20240404.pptx
Objectives n learning outcoms - MD 20240404.pptxObjectives n learning outcoms - MD 20240404.pptx
Objectives n learning outcoms - MD 20240404.pptx
 
Executive Directors Chat Initiating Equity for Impact.pdf
Executive Directors Chat  Initiating Equity for Impact.pdfExecutive Directors Chat  Initiating Equity for Impact.pdf
Executive Directors Chat Initiating Equity for Impact.pdf
 
DBMSArchitecture_QueryProcessingandOptimization.pdf
DBMSArchitecture_QueryProcessingandOptimization.pdfDBMSArchitecture_QueryProcessingandOptimization.pdf
DBMSArchitecture_QueryProcessingandOptimization.pdf
 
HackerOne X IoT Lab Bug Bounty 101 with Encryptsaan & IoT Lab at KIIT Univers...
HackerOne X IoT Lab Bug Bounty 101 with Encryptsaan & IoT Lab at KIIT Univers...HackerOne X IoT Lab Bug Bounty 101 with Encryptsaan & IoT Lab at KIIT Univers...
HackerOne X IoT Lab Bug Bounty 101 with Encryptsaan & IoT Lab at KIIT Univers...
 
Jordan Chrietzberg In Media Res Media Component
Jordan Chrietzberg In Media Res Media ComponentJordan Chrietzberg In Media Res Media Component
Jordan Chrietzberg In Media Res Media Component
 
LEVERAGING SYNERGISM INDUSTRY-ACADEMIA PARTNERSHIP FOR IMPLEMENTATION OF NAT...
LEVERAGING SYNERGISM INDUSTRY-ACADEMIA PARTNERSHIP FOR IMPLEMENTATION OF  NAT...LEVERAGING SYNERGISM INDUSTRY-ACADEMIA PARTNERSHIP FOR IMPLEMENTATION OF  NAT...
LEVERAGING SYNERGISM INDUSTRY-ACADEMIA PARTNERSHIP FOR IMPLEMENTATION OF NAT...
 
18. Training and prunning of horicultural crops.pptx
18. Training and prunning of horicultural crops.pptx18. Training and prunning of horicultural crops.pptx
18. Training and prunning of horicultural crops.pptx
 
Jason Potel In Media Res Media Component
Jason Potel In Media Res Media ComponentJason Potel In Media Res Media Component
Jason Potel In Media Res Media Component
 
Chi-Square Test Non Parametric Test Categorical Variable
Chi-Square Test Non Parametric Test Categorical VariableChi-Square Test Non Parametric Test Categorical Variable
Chi-Square Test Non Parametric Test Categorical Variable
 
Basic cosmetics prepared by my student Mr. Balamurugan, II Maths, 2023-2024
Basic cosmetics prepared by my student Mr. Balamurugan, II Maths, 2023-2024Basic cosmetics prepared by my student Mr. Balamurugan, II Maths, 2023-2024
Basic cosmetics prepared by my student Mr. Balamurugan, II Maths, 2023-2024
 
BÀI TẬP BỔ TRỢ 4 KĨ NĂNG TIẾNG ANH LỚP 8 - CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC ...
BÀI TẬP BỔ TRỢ 4 KĨ NĂNG TIẾNG ANH LỚP 8 - CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC ...BÀI TẬP BỔ TRỢ 4 KĨ NĂNG TIẾNG ANH LỚP 8 - CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC ...
BÀI TẬP BỔ TRỢ 4 KĨ NĂNG TIẾNG ANH LỚP 8 - CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC ...
 
Paul Dobryden In Media Res Media Component
Paul Dobryden In Media Res Media ComponentPaul Dobryden In Media Res Media Component
Paul Dobryden In Media Res Media Component
 
CHUYÊN ĐỀ ÔN THEO CÂU CHO HỌC SINH LỚP 12 ĐỂ ĐẠT ĐIỂM 5+ THI TỐT NGHIỆP THPT ...
CHUYÊN ĐỀ ÔN THEO CÂU CHO HỌC SINH LỚP 12 ĐỂ ĐẠT ĐIỂM 5+ THI TỐT NGHIỆP THPT ...CHUYÊN ĐỀ ÔN THEO CÂU CHO HỌC SINH LỚP 12 ĐỂ ĐẠT ĐIỂM 5+ THI TỐT NGHIỆP THPT ...
CHUYÊN ĐỀ ÔN THEO CÂU CHO HỌC SINH LỚP 12 ĐỂ ĐẠT ĐIỂM 5+ THI TỐT NGHIỆP THPT ...
 
(Part 2) CHILDREN'S DISABILITIES AND EXCEPTIONALITIES.pdf
(Part 2) CHILDREN'S DISABILITIES AND EXCEPTIONALITIES.pdf(Part 2) CHILDREN'S DISABILITIES AND EXCEPTIONALITIES.pdf
(Part 2) CHILDREN'S DISABILITIES AND EXCEPTIONALITIES.pdf
 
Healthy Minds, Flourishing Lives: A Philosophical Approach to Mental Health a...
Healthy Minds, Flourishing Lives: A Philosophical Approach to Mental Health a...Healthy Minds, Flourishing Lives: A Philosophical Approach to Mental Health a...
Healthy Minds, Flourishing Lives: A Philosophical Approach to Mental Health a...
 
Transdisciplinary Pathways for Urban Resilience [Work in Progress].pptx
Transdisciplinary Pathways for Urban Resilience [Work in Progress].pptxTransdisciplinary Pathways for Urban Resilience [Work in Progress].pptx
Transdisciplinary Pathways for Urban Resilience [Work in Progress].pptx
 
The Emergence of Legislative Behavior in the Colombian Congress
The Emergence of Legislative Behavior in the Colombian CongressThe Emergence of Legislative Behavior in the Colombian Congress
The Emergence of Legislative Behavior in the Colombian Congress
 
PART 1 - CHAPTER 1 - CELL THE FUNDAMENTAL UNIT OF LIFE
PART 1 - CHAPTER 1 - CELL THE FUNDAMENTAL UNIT OF LIFEPART 1 - CHAPTER 1 - CELL THE FUNDAMENTAL UNIT OF LIFE
PART 1 - CHAPTER 1 - CELL THE FUNDAMENTAL UNIT OF LIFE
 
4.9.24 Social Capital and Social Exclusion.pptx
4.9.24 Social Capital and Social Exclusion.pptx4.9.24 Social Capital and Social Exclusion.pptx
4.9.24 Social Capital and Social Exclusion.pptx
 
16. Discovery, function and commercial uses of different PGRS.pptx
16. Discovery, function and commercial uses of different PGRS.pptx16. Discovery, function and commercial uses of different PGRS.pptx
16. Discovery, function and commercial uses of different PGRS.pptx
 

Collaborative Bug Triaging

  • 1. N/A Katja Kevic, Sebastian C. Müller, Thomas Fritz, and Harald C. Gall Collaborative Bug Triaging CHASE „13, San Francisco – May 25, 2013
  • 2. Motivation How to support developers for collaborative bug triaging? 2 bug bug bug bug bug bug
  • 3. Related Work • Source code analysis [e.g. MCDonald 2000] • «One out of four bug reports required dicussion and negotiation..» [Carstensen, 1995] 3J. Anvik, L. Hiew, and G. C. Murphy, “Who should fix this bug?,” in Proceedings of the 28th International Conference on Software Engineering, ICSE ‟06. D. W. McDonald and M. S. Ackerman, “Expertise recommender: a flexible recommendation system and architecture,” in Proceedings of the 2000 ACM Conference on Computer Supported Cooperative Work, CSCW ‟00, Carstensen, P. H., Sorensen, C. and Tuikka, T., Let's talk about bugs! Scandanavian Journal of Information Systems, 1995. 7,1 33-54. • Information Retrieval or Machine Learning [e.g. Anvik 2006]
  • 4. Related Work • Source code analysis [e.g. MCDonald 2000] • «One out of four bug reports required dicussion and negotiation..» [Carstensen, 1995] 4J. Anvik, L. Hiew, and G. C. Murphy, “Who should fix this bug?,” in Proceedings of the 28th International Conference on Software Engineering, ICSE ‟06. D. W. McDonald and M. S. Ackerman, “Expertise recommender: a flexible recommendation system and architecture,” in Proceedings of the 2000 ACM Conference on Computer Supported Cooperative Work, CSCW ‟00, Carstensen, P. H., Sorensen, C. and Tuikka, T., Let's talk about bugs! Scandanavian Journal of Information Systems, 1995. 7,1 33-54. • Information Retrieval or Machine Learning [e.g. Anvik 2006]
  • 5. Collaborative Bug Triaging Collaboration IR + change set analysis Allow change set investigation 5
  • 6. Information Retrieval – Finding similar Bugs 0.78 0.72 0.71 cosine similarity threshold > 0.7 6
  • 7. Information Retrieval – Finding similar Bugs 0.78 cosine similarity threshold 7 > 0.75
  • 8. Information Retrieval – Finding similar Bugs 0.78 0.72 0.71 cosine similarity threshold 8 > 0.6
  • 9. Change Set Analysis – Finding Potential Experts 0.71 0.78 0.72 5.46 1.44 4.28 9 Developer 1 Developer 2 Developer 3 7 Change set 1 2 Change set 2 2 Change set 3 4 Change set 4 Similar bug 1 Similar bug 2 Similar bug 3
  • 13. Evaluation • Applied in our own software projects • Future work: user studies 13
  • 14. Summary 14 Collaboration IR + change set analysis Allow change set investigation For more details visit: http://www.ifi.uzh.ch/seal/people/kevic/researchprojects/CollabBugTriaging.html
  • 15. References 15 J. Anvik, L. Hiew, and G. C. Murphy, “Who should fix this bug?,” in Proceedings of the 28th International Conference on Software Engineering, ICSE ‟06, (New York, NY, USA), pp. 361–370, ACM, 2006. D. W. McDonald and M. S. Ackerman, “Expertise recommender: a flexible recommendation system and architecture,” in Proceedings of the 2000 ACM Conference on Computer Supported Cooperative Work, CSCW ‟00, (New York, NY, USA), pp. 231–240, ACM, 2000. Carstensen, P. H., Sorensen, C. and Tuikka, T., Let's talk about bugs! Scandanavian Journal of Information Systems, 1995. 7,1 33-54.

Hinweis der Redaktion

  1. Hello and welcome to my presentation. I’m KatjaKevic from the University of Zurich and today I’m talking about how to support collaborative bug triaging.
  2. In the MySQL project,asexample, on average500 bugs per monthareopenend. Eachbughastobeassessedbased on itsfeatures, such as title, priority, severityandaffectedcomponentsifitismeaningfulandthenidentify a developermostsuitedforfixingthebug. This processiswhatwecallbugtriaging.As evidencesuggests a lotofpeopleareinvolved in triagingbugs. As example in the MySQL projectover 250 developersclosedbugs. Toaround 20 different developersat least onebug was assignedonly in the last month. So, triaging so manybugscanbetedious, time-consuming, anderror-prone, ifitis not supportedbyeffectivemeans.In otherprojects, like Mozilla andEclipse, 37%-44% ofthebugsarereassigned. This reassignmentcanbeunderstoodas a hintthatbugtriagingis a implicitcollaborativetask, becauseitrevealsthatthereiscollectiveknowledgeaboutwhowould fit betterto fix thebugwhichleadstothe final assignment.Whatwetryto find out is, ifsupportingexplicitelythecollaborativenatureofbugtriagingcanenhancethisprocess.