Abstract
Many decision-makers in industry, government and academia routinely make decisions whose outcome depends on the evolution of software technology trends. Even though the stakes of these decisions are usually very high, decision makers routinely depend on expert opinions and qualitative assessments to model the evolution of software technology; both of these sources of decision-making information are subjective, are based on opinions rather than facts, and are prone to error. In this paper, we report on our ongoing work to build quantitative models of the evolution of software technology trends. In particular, we discuss how we took specific evolutionary models and merged them into a single (general-purpose) model. The original specific models are derived empirically using statistical methods on trend data we had collected over several years, and have been validated individually; in this paper we further validate the generic (general-purpose) model.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 4993-5009 |
| Number of pages | 17 |
| Journal | Information sciences |
| Volume | 181 |
| Issue number | 22 |
| DOIs | |
| State | Published - Nov 15 2011 |
All Science Journal Classification (ASJC) codes
- Software
- Control and Systems Engineering
- Theoretical Computer Science
- Computer Science Applications
- Information Systems and Management
- Artificial Intelligence
Keywords
- Bottom up approach
- Extrinsic factors
- Historical trends
- Intrinsic factors
- Software technology trends
- Successful trends