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research-article

Leveraging the Crowd: How 48,000 Users Helped Improve Lync Performance

Published: 01 July 2013 Publication History

Abstract

Performance is a critical component of customer satisfaction with network-based applications. Unfortunately, accurately evaluating the performance of collaborative software that operates in extremely heterogeneous environments is difficult with traditional techniques such as modeling workloads or testing in controlled environments. To evaluate performance of an application in the wild during development, the authors deployed early versions of the software, collecting performance data from application users for key usage scenarios. The analysis package they used produces visualizations to help development teams identify and prioritize performance issues by focusing on performance early in the development cycle, evaluating progress, identifying defects, and estimating timelines.

Cited By

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  • (2022)Context- and Fairness-Aware In-Process Crowdworker RecommendationACM Transactions on Software Engineering and Methodology10.1145/348757131:3(1-31)Online publication date: 7-Mar-2022
  • (2019)iSENSEProceedings of the 41st International Conference on Software Engineering10.1109/ICSE.2019.00097(912-923)Online publication date: 25-May-2019
  • (2017)Crowdsourced exploration of mobile app featuresProceedings of the 39th International Conference on Software Engineering: Software Engineering in Society Track10.1109/ICSE-SEIS.2017.8(57-66)Online publication date: 20-May-2017
  • Show More Cited By

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Information & Contributors

Information

Published In

cover image IEEE Software
IEEE Software  Volume 30, Issue 4
July 2013
99 pages

Publisher

IEEE Computer Society Press

Washington, DC, United States

Publication History

Published: 01 July 2013

Author Tags

  1. Analytical models
  2. Customer satisfaction
  3. Performance evaluation
  4. Software development
  5. Software quality
  6. data analysis
  7. data collection
  8. performance monitoring
  9. software analytics
  10. software data visualization
  11. software performance

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Cited By

View all
  • (2022)Context- and Fairness-Aware In-Process Crowdworker RecommendationACM Transactions on Software Engineering and Methodology10.1145/348757131:3(1-31)Online publication date: 7-Mar-2022
  • (2019)iSENSEProceedings of the 41st International Conference on Software Engineering10.1109/ICSE.2019.00097(912-923)Online publication date: 25-May-2019
  • (2017)Crowdsourced exploration of mobile app featuresProceedings of the 39th International Conference on Software Engineering: Software Engineering in Society Track10.1109/ICSE-SEIS.2017.8(57-66)Online publication date: 20-May-2017
  • (2017)Domain adaptation for test report classification in crowdsourced testingProceedings of the 39th International Conference on Software Engineering: Software Engineering in Practice Track10.1109/ICSE-SEIP.2017.8(83-92)Online publication date: 20-May-2017
  • (2016)Software visualization todayProceedings of the 20th International Academic Mindtrek Conference10.1145/2994310.2994327(262-271)Online publication date: 17-Oct-2016
  • (2016)Local-based active classification of test report to assist crowdsourced testingProceedings of the 31st IEEE/ACM International Conference on Automated Software Engineering10.1145/2970276.2970300(190-201)Online publication date: 25-Aug-2016
  • (2016)Towards Effectively Test Report Classification to Assist Crowdsourced TestingProceedings of the 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement10.1145/2961111.2962584(1-10)Online publication date: 8-Sep-2016
  • (2016)The bones of the systemProceedings of the 38th International Conference on Software Engineering Companion10.1145/2889160.2889231(92-101)Online publication date: 14-May-2016
  • (2016)The emerging role of data scientists on software development teamsProceedings of the 38th International Conference on Software Engineering10.1145/2884781.2884783(96-107)Online publication date: 14-May-2016
  • (2014)What makes a good app description?Proceedings of the 6th Asia-Pacific Symposium on Internetware10.1145/2677832.2677842(45-53)Online publication date: 17-Nov-2014
  • Show More Cited By

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