Dewayne E. Perry
Harvey P. Siy
Abstract
An essential characteristic of large-scale software development is parallel development by teams of developers. How this parallel development is structured and supported has a profound effect on both the quality and timeliness of the product. We conduct an observational case study in which we collect and analyze the change and configuration management history of a legacy system to delineate the boundaries of, and to understand the nature of, the problems encountered in parallel development. The results of our studies are (1) that the degree of parallelism is very highhigher than considered by tool builders; (2) there are multiple levels of parallelism, and the data for some important aspects are uniform and consistent for all levels; (3) the tails of the distributions are long, indicating the tail, rather than the mean, must receive serious attention in providing solutions for these problems; and (4) there is a significant correlation between the degree of parallel work on a given component and the number of quality problems it has. Thus, the results of this study are important both for tool builders and for process and project engineers.
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Index Terms
- Parallel changes in large-scale software development: an observational case study
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Stanley G. Siegel
Conflict-free modification, correction and integration of changes for extremely large, long-lived, multi-version software systems developed in parallel by large teams poses severe problems with respect to avoiding logical and semantic interference of changes. This paper describes the first phase of the Code Decay Project, a long-range, multidisciplinary and multi-institution project. Based on change and quality history data (from April 1984 to April 1996) from one of the 50 subsystems of Lucent Technologies’ 5ESS, involving 50 to 200 developers, the authors propose and prove several interesting hypotheses about the interference of changes in parallel versions: Up to 60 percent of the system’s modules were affected by changes At certain times some modules existed in 2 to 16 parallel versions Frequently, multiple levels of parallel development are found, involving several change requests and many modules 12.5 percent of changes are performed by different developers (due to different change requests) on the same files There is a significant correlation between files with a high degree of parallel development and the number of defects The distribution of most of the data shows a very wide spread, even for rather small medians The paper is well written, instructive and highly relevant for change teams, software management (especially configuration management), and for developers of configuration and version management tools. It is also a very instructive prototype of quantitative research in software engineering, giving software research a more scientific basis. Online Computing Reviews Service
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