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26th International Conference on Software Engineering (ICSE'04)
Skoll: Distributed Continuous Quality Assurance
Edinburgh, Scotland, United Kingdom
May 23-May 28
ISBN: 0-7695-2163-0
A. Memon, University of Maryland at College Park
A. Porter, University of Maryland at College Park
C. Yilmaz, University of Maryland at College Park
A. Nagarajan, University of Maryland at College Park
D. Schmidt, Vanderbilt University
B. Natarajan, Vanderbilt University
Quality assurance (QA) tasks, such as testing, profiling, and performance evaluation, have historically been done in-house on developer-generated workloads and regression suites. Since this approach is inadequate for many systems, tools and processes are being developed to improve software quality by increasing user participation in the QA process. A limitation of these approaches is that they focus on isolated mechanisms, not on the coordination and control policies and tools needed to make the global QA process efficient, effective, and scalable. To address these issues, we have initiated the Skoll project, which is developing and validating novel software QA processes and tools that leverage the extensive computing resources of worldwide user communities in a distributed, continuous manner to significantly and rapidly improve software quality. This paper provides several contributions to the study of distributed continuous QA. First, it illustrates the structure and functionality of a generic around-the-world, around-the-clock QA process and describes several sophisticated tools that support this process. Second, it describes several QA scenarios built using these tools and process. Finally, it presents a feasibility study applying these scenarios to a 1MLOC+ software package called ACE+TAO. While much work remains to be done, the study suggests that the Skoll process and tools effectively manage and control distributed, continuous QA processes. Using Skoll we rapidly identified problems that had taken the ACE+TAO developers substantially longer to find and several of which had previously not been found. Moreover, automatic analysis of QA task results often provided developers information that quickly led them to the root cause of the problems.
Citation:
A. Memon, A. Porter, C. Yilmaz, A. Nagarajan, D. Schmidt, B. Natarajan, "Skoll: Distributed Continuous Quality Assurance," icse, pp.459-468, 26th International Conference on Software Engineering (ICSE'04), 2004
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