Bravonin

• Open Prediction Project Ebooks

1. Gyimothy, T., Ferenc, R., Siket, I.: Empirical Validation of Object-Oriented Metrics on Open Source Software for Fault Prediction. TSE 30(10), 897–910 (2005)Google Scholar
2. Kitchenham, B.A., Pretorius, R., Budgen, D., Brereton, O.P., Turner, M., Niazi, M., Linkman, S.: Systematic literature reviews in software engineering- A tertiary study. Information and Software Technology 52(8), 792–805 (2010)CrossRefGoogle Scholar
3. Catal, C., Diri, B.: A systematic review of software fault prediction studies. Expert Systems with Applications 36(4), 7346–7354 (2009)CrossRefGoogle Scholar
4. Shatnawi, R., Li, W.: The effectiveness of software metrics in identifying error-prone classes in post-release software evolution. TSE 81(11), 1868–1882 (2008)Google Scholar
5. Turhan, B., Menzies, T., Bener, A.B., Stefano, J.D.: On the relative value of cross-company and within-company data for defect prediction. ESEM 14(5), 540–578 (2009)Google Scholar
6. Subramanyan, R., Krishnan, M.S.: Empirical Analysis of CK Metrics for Object-Oriented Design Complexity: Implications for Software Defects. TSE 29(4), 297–310 (2003)Google Scholar
7. Catal, C.: Software fault prediction: A literature review and current trends. Expert Systems with Applications 38(4), 4626–4636 (2011)CrossRefGoogle Scholar
8. Capiluppi, A., Adams, P.J.: Reassessing Brooks Law for the Free Software Community. IFIP AICT, pp. 274–283 (2009)Google Scholar
9. English, M., Exton, C., Rigon, I., Cleary, B.: Fault detection and prediction in an open-source project. In: PROMISE (2009)Google Scholar
10. Askari, M., Holt, R.: Information theoretic evaluation of change prediction models for large-scale software. In: MSR, pp. 126–132 (2006)Google Scholar
11. Knab, P., Pinzger, M., Bernstein, A.: Predicting Defect Densities in Source Code Files with Decision Tree Learners. In: MSR, pp. 119–125 (2006)Google Scholar
12. Ratzinger, J., Sigmund, T., Vorburger, P., Gall, H.: Mining Software Evolution to Predict Refactoring. In: ESEM, pp. 354–363 (2007)Google Scholar
13. Nakakoji, K., Yamamoto, Y., Nishinaka, Y., Kishida, K., Ye, Y.: Evolution Patterns of Open-Source Software Systems and Communities. In: IWPSE, pp. 76–85 (2002)Google Scholar
14. Bettenburg, N., Hassan, A.E.: Studying the Impact of Social Structures on Software Quality. In: ICPC, pp. 124–133 (2010)Google Scholar

Open Prediction Project Ebooks

For the adoption of Open Source Software (OSS) components, knowledge of the project development and associated risks with their use is needed. That, in turn, calls for reliable prediction models to support preventive maintenance and building quality software. IT Predictions. We will see a continued convergence of networking and security. We can see this in specialized hardware such as the SpiNNaker project, Brainchip's Akida, and Blue Brain's neuromorphic cortical columns. While AI is not real yet, we're starting to see early evidence of the shift. These changes will open. This eBook is no longer available for sale. This book is the second and final edited volume of publications of this Predictive Modelling project. It brings together technical papers on developing new methods for predictive modelling and appliance in cultural heritage management in the Netherlands.