AMAP: automatically mining abbreviation expansions in programs to enhance software maintenance tools
Proceedings of the 2008 international working conference on Mining software repositories
Automatically capturing source code context of NL-queries for software maintenance and reuse
ICSE '09 Proceedings of the 31st International Conference on Software Engineering
Source code indexing for automated tracing
Proceedings of the 6th International Workshop on Traceability in Emerging Forms of Software Engineering
Information Systems Frontiers
Source code identifier splitting using Yahoo image and web search engine
Proceedings of the First International Workshop on Software Mining
Risk chain prediction metrics for predicting fault proneness in object oriented systems
Proceedings of the Second International Conference on Computational Science, Engineering and Information Technology
Supporting concept location through identifier parsing and ontology extraction
Journal of Systems and Software
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Informative identifiers are made up of full (natural language) words and (meaningful) abbreviations. Readers of programs typically have little trouble understanding the purpose of identifiers composed of full words. In addition, those familiar with the code can (most often) determine the meaning of abbreviations used in identifiers. However, when faced with unfamiliar code, abbreviations often carry little useful information. Furthermore, tools that focus on the natural language used in the code have a hard time in the presence of abbreviations. One approach to providing meaning to programmers and tools is to translate (expand) abbreviations into full words. This paper presents a methodology for expanding identifiers and evaluates the process on a code based of just over 35 million lines of code. For example, using phrase extraction, fs exists is expanded to file status exists illustrating how the expansion process can facilitate comprehension. On average, 16 percent of the identifiers in a program are expanded. Finally, as an example application, the approach is used to improve the syntactic identification of violations to Deiβenb篓ock and Pizka's rules for concise and consistent identifier construction.