CoCoME Literature Review

To understand how well existing studies on software evolution support research collaboration we conducted a literature review. We performed two selection iterations on the initial amount of 272 search hits, c.f., figure below. Each iteration was guided by defined inclusion and exclusion criteria. After the first iteration 105 papers were selected for further analysis. Within the second iteration 53 papers were identified.

The identified papers of the literature review are listed in the following.

Year:  
All :: 2001, ... , 2011, 2012, 2013, 2014
Michael Wuersch, Emanuel Giger and Harald C. Gall
Evaluating a Query Framework for Software Evolution Data
ACM Trans. Softw. Eng. Methodol., 22(4):38:1--38:38
2013
ISSN: 1049-331X
Aiko Yamashita and Leon Moonen
To what extent can maintenance problems be predicted by code smell detection? - An empirical study
Information and Software Technology, 55(12):2223 - 2242
2013
ISSN: 0950-5849
Iulian Neamtiu, Guowu Xie and Jianbo Chen
Towards a better understanding of software evolution: an empirical study on open-source software
Journal of Software: Evolution and Process, 25(3):193--218
2013
ISSN: 2047-7481
Dong Qiu, Bixin Li and Zhendong Su
An Empirical Analysis of the Co-evolution of Schema and Code in Database Applications
Proceedings of the 2013 9th Joint Meeting on Foundations of Software Engineering of ESEC/FSE 2013 , page 125--135.
Publisher: ACM, New York, NY, USA
2013
ISBN: 978-1-4503-2237-9
T. McDonnell, B. Ray and Miryung Kim
An Empirical Study of API Stability and Adoption in the Android Ecosystem
Software Maintenance (ICSM), 2013 29th IEEE International Conference on , page 70-79.
2013
S. Lehnert, Q. Farooq and M. Riebisch
Rule-Based Impact Analysis for Heterogeneous Software Artifacts
Software Maintenance and Reengineering (CSMR), 2013 17th European Conference on , page 209-218.
2013



Implementation Details for all CoCoME Variants

Fig 1: Lines of Code over Time
Fig 2: Changed Lines of Code over Time
Fig 3: Number of Java Classes over Time
Fig 4: Number of Java Methods over Time