Anelli, G., Antchev, G., Aspell, P., Avati, V., Bagliesi, M. G., Berardi, V., ... & Brücken, E. (2008). The totem experiment at the cern large hadron collider. Journal of Instrumentation, 3(08), S08007.

Bächle, M., & Kirchberg, P. (2007). Ruby on rails. IEEE software, 24(6).

Batsov, B. (2012). RuboCop | A Ruby static code analyzer. [online] Batsov.com. Available at: http://batsov.com/rubocop/ [Accessed 12 Feb. 2017].

Beller, M., Bholanath, R., McIntosh, S., & Zaidman, A. (2016, March). Analyzing the state of static analysis: A large-scale evaluation in open source software. In Software Analysis, Evolution, and Reengineering (SANER), 2016 IEEE 23rd International Conference on (Vol. 1, pp. 470-481). IEEE.

Berube, D. (2007). What Is RubyGems?. In , Practical Ruby Gems (p. 3). doi:10.1007/978-1-4302-0193-9_1

Breiman, L. (1996). Bagging predictors. Machine learning, 24(2), 123-140.

Ćilimković, M. (2017). Is Ruby dead? Hell no! - Analyzing RubyGems stats for 2016. [online] Infinum.co. Available at: https://infinum.co/the-capsized-eight/analyzing-rubygems-stats-v2016 [Accessed 11 Feb. 2017].

Elish, M. O., Aljamaan, H., & Ahmad, I. (2015). Three empirical studies on predicting software maintainability using ensemble methods. Soft Computing, 19(9), 2511-2524.

Fowler, M., & Beck, K. (1999). Refactoring: improving the design of existing code. Addison-Wesley Professional.

Gilb, T. (1977). Software metrics.

Hassan, A. E. (2006, September). Mining software repositories to assist developers and support managers. In Software Maintenance, 2006. ICSM'06. 22nd IEEE International Conference on (pp. 339-342). IEEE.

Hayes, B. (2014). Doing Data Science.

Hassan, A. E. (2008, September). The road ahead for mining software repositories. In Frontiers of Software Maintenance, 2008. FoSM 2008. (pp. 48-57). IEEE.

IEEE. (1990). Standard Glossary of Software Engineering Terminology. IEEE Software Engineering Standards & Collection. IEEE, 610-12.

Kluyver, T., Ragan-Kelley, B., Pérez, F., Granger, B., Bussonnier, M., Frederic, J., ... & Ivanov, P. (2016). Jupyter Notebooks—a publishing format for reproducible computational workflows. Positioning and Power in Academic Publishing: Players, Agents and Agendas, 87.

Khong, D. W. (2007). Orphan Works, Abandonware and the Missing Market for Copyrighted Goods. International Journal of Law and Information Technology, 15(1), 54-89.

Kluth, S., Seuster, R., Obreshkov, E., Martin-Haugh, S., Snyder, S., Stewart, G., & Roe, S. (2016). C++ Software Quality in the ATLAS Experiment: Tools and Experience (No. ATL-SOFT-SLIDE-2016-013). ATL-COM-SOFT-2016-004.

Kohavi, R. (1995, August). A study of cross-validation and bootstrap for accuracy estimation and model selection. In Ijcai (Vol. 14, No. 2, pp. 1137-1145).

Larman, C. (2012). Applying UML and Patterns: An Introduction to Object Oriented Analysis and Design and Interative Development. Pearson Education India.

Lohn, K. (2016). K Lars Lohn - Keynote - PyCon 2016. [online] YouTube. Available at: https://www.youtube.com/watch?v=bSfe5M_zG2s&t=1015s [Accessed 11 Feb. 2016].

Lozano Rodriguez, A. (2009). Assessing the effect of source code characteristics on changeability (Doctoral dissertation, The Open University).

Mandelbrot, B. B. (1967). How long is the coast of Britain. Science, 156(3775), 636-638.

Martin, R. C. (2009). Clean code: a handbook of agile software craftsmanship. Pearson Education.

Matsumoto, Y., & Ishituka, K. (2002). Ruby programming language.

McCabe, T. J. (1976). A complexity measure. IEEE Transactions on software Engineering, (4), 308-320.

Moser, R., Pedrycz, W., & Succi, G. (2008, May). A comparative analysis of the efficiency of change metrics and static code attributes for defect prediction. In Proceedings of the 30th international conference on Software engineering (pp. 181-190). ACM.

Nguyen, N., & Guo, Y. (2007, June). Comparisons of sequence labeling algorithms and extensions. In Proceedings of the 24th international conference on Machine learning (pp. 681-688). ACM.

Norman, D. A. (2005). Emotional design: Why we love (or hate) everyday things. Basic books.

Palomba, F., Bavota, G., Di Penta, M., Oliveto, R., Poshyvanyk, D., & De Lucia, A. (2015). Mining version histories for detecting code smells. IEEE Transactions on Software Engineering, 41(5), 462-489.

Palomba, F., Bavota, G., Di Penta, M., Oliveto, R., De Lucia, A., & Poshyvanyk, D. (2013, November). Detecting bad smells in source code using change history information. In Automated software engineering (ASE), 2013 IEEE/ACM 28th international conference on (pp. 268-278). IEEE.

Paulson, L. D. (2007). Developers shift to dynamic programming languages. Computer, 40(2).

Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., ... & Vanderplas, J. (2011). Scikit-learn: Machine learning in Python. Journal of Machine Learning Research, 12(Oct), 2825-2830.

Rapu, D., Ducasse, S., Gîrba, T., & Marinescu, R. (2004, March). Using history information to improve design flaws detection. In Software Maintenance and Reengineering, 2004. CSMR 2004. Proceedings. Eighth European Conference on (pp. 223-232). IEEE.

Reeves, J. W. (1992). What is software design. C++ Journal, 2(2), 14-12.

Riaz, M., Mendes, E., & Tempero, E. (2009, October). A systematic review of software maintainability prediction and metrics. In Proceedings of the 2009 3rd International Symposium on Empirical Software Engineering and Measurement (pp. 367-377). IEEE Computer Society.

Rosen, L. (2005). Open source licensing (Vol. 692). Prentice Hall.

Rößner, T. (2008). Reek: Code smell detector for Ruby. [online] GitHub. Available at: https://github.com/troessner/reek [Accessed 12 Feb. 2017].

Shakhnarovich, G., Indyk, P., & Darrell, T. (2006). Nearest-neighbor methods in learning and vision: theory and practice.

Spolsky, J. (2005). The Best Software Writing I. [electronic book]. Berkeley, CA : Joel Spolsky, 2005.

Tufano, M., Palomba, F., Bavota, G., Oliveto, R., Di Penta, M., De Lucia, A., & Poshyvanyk, D. (2015, May). When and why your code starts to smell bad. In Proceedings of the 37th International Conference on Software Engineering-Volume 1 (pp. 403-414). IEEE Press.

Van Rossum, G. (2007, June). Python Programming Language. In USENIX Annual Technical Conference (Vol. 41, p. 36).

Wittern, E., Suter, P., & Rajagopalan, S. (2016, May). A look at the dynamics of the JavaScript package ecosystem. In Proceedings of the 13th International Conference on Mining Software Repositories (pp. 351-361). ACM.

Why the lucky stiff. (2017, February). In Wikipedia, The Free Encyclopedia. Retrieved 13:38, February 13, 2017, from https://en.wikipedia.org/w/index.php?title=Why_the_lucky_stiff&oldid=763626986

Ying, A. T., Murphy, G. C., Ng, R., & Chu-Carroll, M. C. (2004). Predicting source code changes by mining change history. IEEE transactions on Software Engineering, 30(9), 574-586.

Zimmermann, T., Zeller, A., Weissgerber, P., & Diehl, S. (2005). Mining version histories to guide software changes. IEEE Transactions on Software Engineering, 31(6), 429-445.