Abstract
Establishing API mappings between libraries is a prerequisite stepfor library migration tasks. Manually establishing API mappings istedious due to the large number of APIs to be examined, and existingmethods based on supervised learning requires unavailable alreadyported or functionality similar applications. Therefore, we proposean unsupervised deep learning based approach to embed both APIusage semantics and API description (name and document) semantics into vector space for inferring likely analogical API mappingsbetween libraries. We implement a proof-of-concept website SimilarAPI (https://similarapi.appspot.com) which can recommend analogical APIs for 583,501 APIs of 111 pairs of analogical Java librarieswith diverse functionalities. Video: https://youtu.be/EAwD6l24vLQ.
Original language | English |
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Title of host publication | Proceedings - 2020 ACM/IEEE 42nd International Conference on Software Engineering |
Subtitle of host publication | Companion Proceedings, ICSE-Companion 2020 |
Editors | Hyunsook Do, Tien N. Nguyen |
Place of Publication | New York NY USA |
Publisher | IEEE, Institute of Electrical and Electronics Engineers |
Pages | 37-40 |
Number of pages | 4 |
ISBN (Electronic) | 9781450371223 |
DOIs | |
Publication status | Published - 2020 |
Event | International Conference on Software Engineering 2020 - Online, Seoul, Korea, South Duration: 27 Jun 2020 → 19 Jul 2020 Conference number: 42nd https://dl.acm.org/doi/proceedings/10.1145/3377811 (Proceedings) https://conf.researchr.org/home/icse-2020 (Website) |
Conference
Conference | International Conference on Software Engineering 2020 |
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Abbreviated title | ICSE 2020 |
Country/Territory | Korea, South |
City | Seoul |
Period | 27/06/20 → 19/07/20 |
Internet address |
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Keywords
- Analogical API
- Skip thoughts
- Word embedding