ff146a9362
Reference papers on API mapping, migration, and evolution collected during PhD research (2018). Topics include: API usage adaptation (LibSync), statistical API mapping mining (StaMiner, MAM), API mapping via vector representations (Word2Vec), text mining for API mappings (TMAP), library migration graphs, framework evolution (AURA), class library migration refactoring, and API specification inference (Doc2Spec).
1.0 KiB
category, type, person, date, source
| category | type | person | date | source |
|---|---|---|---|---|
| academic | academic | Yanxin Lu | 2010 | zhong_10_mam.pdf |
Mining API Mapping for Language Migration
Hao Zhong, Suresh Thummalapenta, Tao Xie, Lu Zhang, Qing Wang (Chinese Academy of Sciences, Peking University, NC State)
ICSE 2010
To address business requirements, companies often have to release different versions of their projects in different languages. Manually migrating projects (e.g., from Java to C#) is tedious and error-prone. This paper proposes MAM (Mining API Mapping), a novel approach that automatically mines how APIs of one language are mapped to APIs of another using API client code. MAM accepts a set of projects each with two versions in two languages and mines API mapping relations between those two languages based on how APIs are used by the two versions. Results show that the tool mines 25,805 unique mapping relations of APIs between Java and C# with more than 80% accuracy, and the mined relations help reduce 54.4% compilation errors and 43.0% defects during migration with Java2CSharp.