1. Does Distributed Development Affect Software Quality???? An Empirical Case Study of Windows Vista Christian Bird, Premkumar Devanbu, Harald Gall, Brendan Murphy In ICSE ’09: Proceedings of the 2009 IEEE 31st International Conference on Software Engineering

2. Distributed Software development is more riskier and challenging than collocated development  Reasons for distributed software development: skill set availability, acquisitions, government restrictions, increased code size, cost and complexity  Challenges faced : delayed feedback, restricted communication, less shared project awareness, difficulty of synchronous communication, inconsistent development and build environments  Post – Release Failure: The inability of a system or a component to perform its required functions within specified performance requirements  Individual executable and libraries are referred to as Binaries

3. Key Questions  Who or What is distributed at What level??  Are people or the artifacts distributed??  Are people dispersed individually or dispersed in groups??  Way the developers and other entities are distributed??  Distribution can be across geographical, organizational, temporal, or stakeholder boundaries Study involves  Distributed development at multiple levels of separation  Large Scale S/W development – thousands of binaries and developers  Complexity and maintenance characteristics of the distributed and collocated binaries  All sites involved in the study are part of the same company

4. Difficulties in Distributed Development  Communication  Coordination Breakdowns  Diversity in Operating Environments  Distance reduces team cohesion  Organizational and National Cultural barriers Testable Hypothesis  Binaries that are developed by teams of engineers that are distributed will have more post-release failures than developed by collocated engineers  Binaries that are distributed will be less complex and have fewer dependencies Popular Beliefs

5. Effects on Bug Resolution  The time to Resolution of Modification Requests (MRs)  For a single site – 5 days  For Distributed site – 12.7 days  On controlling factors like : No: of People working on MR, severity, size of the change, negative effect of distributed development was less significant  Distributed development indirectly introduces delay due to correlated factors such as team size and breadth of changes required  Feasible decisions must for the project  Testable hypotheses about productivity  People who are assigned work from many sources have lower productivity  MRs that require work in multiple modules take more time

6. Effects on Quality and Productivity  Relationship between Dispersion, development productivity and conformance quality  Inference: Projects that had more dispersion had lower levels of productivity and conformance quality  Key Actions necessary for success with global development: - Distribute entire things for entire life cycle - Plan to accommodate time and distance  Reduce intensive collaborations  Reduce national and organizational cultural distance  Reduce temporal distance

7. Methods and Analysis

8. Data Collection  Windows Vista  3300 binaries  Tens of MLOC  59 buildings 21 campuses in Asia, Europe, and North America  Data Collection Focus  Code Quality  Geographical location

9. Geographical Location based Separation  Hierarchy  Building  Cafeteria  Campus  Locality  Continent  World  Assignment to level of hierarchy  To lowest possible level which covers a threshold percentage of commits  Threshold percentage  75% of commits made

10. Geographical Location based Separation cont’d

11. Experiments and Results  Objective  Test the hypothesis that, there will be difference in code quality between distributed and collocated binary  Measure of Quality: Number of post release failures per binary

12. Results cont’d Result1: Increase of failures for geographic distribution is small (but not statistically insignificant) Result2: Effect of geographic separation can be controlled to some extent by controlling team size  Linear Regression Analysis to examine the effect of distributed development on the number of failures:  9.2% increase in failures when distributed  4.6% increase in failures when distributed but team-size is controlled

13. Analysis of Results  Arrived Conclusion “In the context in which Windows Vista was developed, teams that were distributed wrote code that had virtually same number of post-release failures as those that were collocated”  Factors that may be responsible  Difference between collocated and distributed binary?  Difference may come from  Size and complexity, Code Churn, Test Coverage, Dependencies, People  Finding: No significant difference except a small (statistically not significant) difference in team size metric.

14. How Is It Possible To Conduct Distributed Development Without Hampering Quality ?  Relationship between sites All sites work together, same pay, benefits  Cultural Barriers Engineers visit each other, work together, builds trust  Communication Maintain core working hours  Consistent Use Of Tools same source code management, documentation, defect tracking tools

15. Continued

16.  Distributed development can work for large software projects  Organizationally compact geographically distributed project is better than a geographically local organizationally distributed project  Microsoft Vista is an example which negates the popular belief about distributed development Conclusion

17. Thank You ! Questions !