Abstract
In various fields of computer science, rapidly growing hardware power, such as high-speed network, high-performance CPU, huge disk capacity, and large memory space, has been fruitfully harnessed. Examples of such usage are large scale data and web mining, grid computing, and multimedia environments. We propose that such rich hardware can also catapult software engineering to the next level. Huge amounts of software engineering data can be systematically collected and organized from tens of thousands of projects inside organizations, or from outside an organization through the Internet. The collected data can be analyzed extensively to extract and correlate multi-project knowledge for improving organization-wide productivity and quality. We call such an approach for software engineering Mega Software Engineering. In this paper, we propose the concept of Mega Software Engineering, and demonstrate some novel data analysis characteristic of Mega Software Engineering. We describe a framework for enabling Mega Software Engineering.
Keywords
- Software Engineering
- Software Engineer
- Software Project
- Collaborative Filter
- Global Software Development
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Inoue, K., Garg, P.K., Iida, H., Matsumoto, K., Torii, K. (2005). Mega Software Engineering. In: Bomarius, F., Komi-Sirviö, S. (eds) Product Focused Software Process Improvement. PROFES 2005. Lecture Notes in Computer Science, vol 3547. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11497455_32
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DOI: https://doi.org/10.1007/11497455_32
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26200-8
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