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- Britto, Ricardo, 1982-, et al.
(author)
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Experiences from Measuring Learning and Performance in Large-Scale Distributed Software Development
- 2016
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In: Proceedings of the 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement. - New York, NY, USA : ACM Digital Library. - 9781450344272
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Conference paper (peer-reviewed)abstract
- Background: Developers and development teams in large-scale software development are often required to learn continuously. Organizations also face the need to train and support new developers and teams on-boarded in ongoing projects. Although learning is associated with performance improvements, experience shows that training and learning does not always result in a better performance or significant improvements might take too long.Aims: In this paper, we report our experiences from establishing an approach to measure learning results and associated performance impact for developers and teams in Ericsson.Method: Experiences reported herein are a part of an exploratory case study of an on-going large-scale distributed project in Ericsson. The data collected for our measurements included archival data and expert knowledge acquired through both unstructured and semi-structured interviews. While performing the measurements, we faced a number of challenges, documented in the form of lessons learned.Results: We aggregated our experience in eight lessons learned related to collection, preparation and analysis of data for further measurement of learning potential and performance in large-scale distributed software development.Conclusions: Measuring learning and performance is a challenging task. Major problems were related to data inconsistencies caused by, among other factors, distributed nature of the project. We believe that the documented experiences shared herein can help other researchers and practitioners to perform similar measurements and overcome the challenges of large-scale distributed software projects, as well as proactively address these challenges when establishing project measurement programs.
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- Hovsepyan, Aram, et al.
(author)
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Is Newer Always Better?: The Case of Vulnerability Prediction Models
- 2016
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In: ESEM '16 Proceedings of the 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement. - New York, NY, USA : Association for Computing Machinery. - 1949-3770 .- 1949-3789. - 9781450344272
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Conference paper (peer-reviewed)abstract
- © 2016 ACM. Finding security vulnerabilities in the source code as early as possible is becoming more and more essential. In this respect, vulnerability prediction models have the potential to help the security assurance activities by identifying code locations that deserve the most attention. In this paper, we investigate whether prediction models behave like milk (i.e., they turn with time) or wine (i.e., the improve with time) when used to predict future vulnerabilities. Our findings indicate that the recall values are largely in favor of predictors based on older versions. However, the better recall comes at the price of much higher file inspection ratio values.
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- Knauss, Eric, 1977, et al.
(author)
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Continuous Integration Beyond the Team: A Tooling Perspective on Challenges in the Automotive Industry
- 2016
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In: Proceedings of the 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM '16). - New York, NY, USA : ACM. - 1949-3770 .- 1949-3789. - 9781450344272
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Conference paper (peer-reviewed)abstract
- The practice of Continuous Integration (CI) has a big impact on how software is developed today. Shortening integration and feedback cycles promises to increase software quality, feature throughput, and customer satisfaction. Thus, it is not a surprise that companies try to embrace CI in domains where it is rather difficult to implement. In this paper we present our findings from two rounds of interviews with a car manufacturer on the use of tools in system engineering and how these tools would support wider adoption of CI. Our findings suggest a complex tool landscape with immense requirements that are not easily fulfilled by existing tools; this holds also for tools that well support CI in other domains. From this notion, we fur- ther explore what makes the automotive domain challeng- ing when it comes to CI (namely complexity of system and value chain). We hope that our findings will help address such challenges.
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- Wohlin, Claes
(author)
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Is there a Future for Empirical Software Engineering?
- 2016
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In: Proceedings of the 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement. - : ACM/IEEE. - 9781450344272
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Conference paper (other academic/artistic)
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