A study on the changes of dynamic feature code when fixing bugs: towards the benefits and costs of Python dynamic features
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Wanwangying Ma | Lin Chen | Baowen Xu | Yanhui Li | Wei Lin | Zhifei Chen
[1] Yuming Zhou,et al. Towards an understanding of change types in bug fixing code , 2017, Inf. Softw. Technol..
[2] Wanwangying Ma,et al. Empirical analysis of network measures for predicting high severity software faults , 2016, Science China Information Sciences.
[3] Baowen Xu,et al. Python probabilistic type inference with natural language support , 2016, SIGSOFT FSE.
[4] Baowen Xu,et al. Python predictive analysis for bug detection , 2016, SIGSOFT FSE.
[5] Baowen Xu,et al. An Empirical Study on the Characteristics of Python Fine-Grained Source Code Change Types , 2016, 2016 IEEE International Conference on Software Maintenance and Evolution (ICSME).
[6] Baowen Xu,et al. Tracking Down Dynamic Feature Code Changes against Python Software Evolution , 2016, 2016 Third International Conference on Trustworthy Systems and their Applications (TSA).
[7] Ming Wen,et al. Locus: Locating bugs from software changes , 2016, 2016 31st IEEE/ACM International Conference on Automated Software Engineering (ASE).
[8] Sukyoung Ryu,et al. Battles with False Positives in Static Analysis of JavaScript Web Applications in the Wild , 2016, 2016 IEEE/ACM 38th International Conference on Software Engineering Companion (ICSE-C).
[9] Tobias Wrigstad,et al. Measuring polymorphism in python programs , 2015, DLS.
[10] Zhendong Su,et al. An Empirical Study on Real Bug Fixes , 2015, 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering.
[11] Hong Mei,et al. A survey on bug-report analysis , 2015, Science China Information Sciences.
[12] Jim Baker,et al. Design and evaluation of gradual typing for python , 2014, DLS.
[13] Baowen Xu,et al. Hybrid Information Flow Analysis for Python Bytecode , 2014, 2014 11th Web Information System and Application Conference.
[14] Yi Sun,et al. Some Code Smells Have a Significant but Small Effect on Faults , 2014, TSEM.
[15] Yuming Zhou,et al. Dynamic Slicing of Python Programs , 2014, 2014 IEEE 38th Annual Computer Software and Applications Conference.
[16] Tobias Wrigstad,et al. Tracing dynamic features in python programs , 2014, MSR 2014.
[17] Lin Chen,et al. Identifying extract class refactoring opportunities for internetware , 2014, Science China Information Sciences.
[18] Gerardo Canfora,et al. How changes affect software entropy: an empirical study , 2014, Empirical Software Engineering.
[19] Baowen Xu,et al. Static Slicing for Python First-Class Objects , 2013, 2013 13th International Conference on Quality Software.
[20] Audris Mockus,et al. A large-scale empirical study of just-in-time quality assurance , 2013, IEEE Transactions on Software Engineering.
[21] Gail C. Murphy,et al. Why did this code change? , 2013, 2013 35th International Conference on Software Engineering (ICSE).
[22] Baowen Xu,et al. Finding shrink critical section refactoring opportunities for the evolution of concurrent code in trustworthy software , 2013, Science China Information Sciences.
[23] G. Antoniol,et al. An exploratory study of the impact of antipatterns on class change- and fault-proneness , 2012, Empirical Software Engineering.
[24] Jan Vitek,et al. The Eval That Men Do - A Large-Scale Study of the Use of Eval in JavaScript Applications , 2011, ECOOP.
[25] Mira Mezini,et al. Taming reflection: Aiding static analysis in the presence of reflection and custom class loaders , 2011, 2011 33rd International Conference on Software Engineering (ICSE).
[26] Romain Robbes,et al. How developers use the dynamic features of programming languages: the case of smalltalk , 2011, MSR '11.
[27] Yanhong A. Liu,et al. Alias analysis for optimization of dynamic languages , 2010, DLS '10.
[28] Jan Vitek,et al. An analysis of the dynamic behavior of JavaScript programs , 2010, PLDI '10.
[29] Baowen Xu,et al. A Constraint Based Bug Checking Approach for Python , 2009, 2009 33rd Annual IEEE International Computer Software and Applications Conference.
[30] Sunghun Kim,et al. Toward an understanding of bug fix patterns , 2009, Empirical Software Engineering.
[31] Katsuhisa Maruyama,et al. A change-aware development environment by recording editing operations of source code , 2008, MSR '08.
[32] Andreas Zeller,et al. Predicting faults from cached history , 2008, ISEC '08.
[33] Harald C. Gall,et al. Change Distilling:Tree Differencing for Fine-Grained Source Code Change Extraction , 2007, IEEE Transactions on Software Engineering.
[34] Abraham Bernstein,et al. Detecting similar Java classes using tree algorithms , 2006, MSR '06.
[35] Miryung Kim,et al. Program element matching for multi-version program analyses , 2006, MSR '06.
[36] Dewayne E. Perry,et al. Toward understanding the rhetoric of small source code changes , 2005, IEEE Transactions on Software Engineering.
[37] Jeffrey S. Foster,et al. Understanding source code evolution using abstract syntax tree matching , 2005, MSR.
[38] Lucian Voinea,et al. CVSscan: visualization of code evolution , 2005, SoftVis '05.
[39] Oege de Moor,et al. Measuring the dynamic behaviour of AspectJ programs , 2004, OOPSLA.
[40] Alessandro Orso,et al. A differencing algorithm for object-oriented programs , 2004, Proceedings. 19th International Conference on Automated Software Engineering, 2004..
[41] David Leon,et al. Dex: a semantic-graph differencing tool for studying changes in large code bases , 2004, 20th IEEE International Conference on Software Maintenance, 2004. Proceedings..
[42] Harald C. Gall,et al. Populating a Release History Database from version control and bug tracking systems , 2003, International Conference on Software Maintenance, 2003. ICSM 2003. Proceedings..
[43] M F Sanner,et al. Python: a programming language for software integration and development. , 1999, Journal of molecular graphics & modelling.
[44] Susan Horwitz,et al. Identifying the semantic and textual differences between two versions of a program , 1990, PLDI '90.
[45] R. Fisher. Statistical methods for research workers , 1927, Protoplasma.
[46] Yang Feng,et al. Mubug: a mobile service for rapid bug tracking , 2015, Science China Information Sciences.
[47] James Harland,et al. Evaluating the dynamic behaviour of Python applications , 2009, ACSC.
[48] M. Kendall. Statistical Methods for Research Workers , 1937, Nature.