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2012 16th European Conference on Software Maintenance and Reengineering
Identifier-Based Context-Dependent API Method Recommendation
Szeged, Hungary
March 27-March 30
ISBN: 978-0-7695-4666-7
| ASCII Text | x | ||
| Lars Heinemann, Veronika Bauer, Markus Herrmannsdoerfer, Benjamin Hummel, "Identifier-Based Context-Dependent API Method Recommendation," 2011 15th European Conference on Software Maintenance and Reengineering, pp. 31-40, 2012 16th European Conference on Software Maintenance and Reengineering, 2012. | |||
| BibTex | x | ||
| @article{ 10.1109/CSMR.2012.14, author = {Lars Heinemann and Veronika Bauer and Markus Herrmannsdoerfer and Benjamin Hummel}, title = {Identifier-Based Context-Dependent API Method Recommendation}, journal ={2011 15th European Conference on Software Maintenance and Reengineering}, volume = {0}, year = {2012}, issn = {1534-5351}, pages = {31-40}, doi = {http://doi.ieeecomputersociety.org/10.1109/CSMR.2012.14}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - 2011 15th European Conference on Software Maintenance and Reengineering TI - Identifier-Based Context-Dependent API Method Recommendation SN - 1534-5351 SP31 EP40 A1 - Lars Heinemann, A1 - Veronika Bauer, A1 - Markus Herrmannsdoerfer, A1 - Benjamin Hummel, PY - 2012 KW - software reuse KW - recommendation system KW - identifier KW - data mining VL - 0 JA - 2011 15th European Conference on Software Maintenance and Reengineering ER - | |||
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CSMR.2012.14
Reuse recommendation systems support the developer by suggesting useful API methods, classes or code snippets based on code edited in the IDE. Existing systems based on structural information, such as type and method usage, are not effective in case of general purpose types such as String. To alleviate this, we propose a recommendation system based on identifiers that utilizes the developer's intention embodied in names of variables, types and methods. We investigate the impact of several variation points of our recommendation algorithm and evaluate the approach for recommending methods from the Java and Eclipse APIs in 9 open source systems. Furthermore, we compare our recommendations to those of a structure-based recommendation system and describe a metric for predicting the expected precision of a recommendation. Our findings indicate that our approach performs significantly better than the structure-based approach.
Index Terms:
software reuse, recommendation system, identifier, data mining
Citation:
Lars Heinemann, Veronika Bauer, Markus Herrmannsdoerfer, Benjamin Hummel, "Identifier-Based Context-Dependent API Method Recommendation," csmr, pp.31-40, 2012 16th European Conference on Software Maintenance and Reengineering, 2012
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