Automated API Recommendation
Many libraries have been used in the software project. With the increasing number of libraries used in a software project, developers often have to search multiple online resources to learn the usage of the APIs if the developers have no prior knowledge of certain libraries. This may lead to an incr...
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| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
2017
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| Online Access: | http://hdl.handle.net/10356/70279 |
| _version_ | 1811676681465757696 |
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| author | Toh, Gao Han |
| author2 | Liu Yang |
| author_facet | Liu Yang Toh, Gao Han |
| author_sort | Toh, Gao Han |
| collection | NTU |
| description | Many libraries have been used in the software project. With the increasing number of libraries used in a software project, developers often have to search multiple online resources to learn the usage of the APIs if the developers have no prior knowledge of certain libraries. This may lead to an increase in development time.
Therefore, in this project, we developed Automated API Recommendation. Given the latest API detected, we will recommend APIs to the developers. To build the Automated API Recommendation, we had extracted the API sequence of every java source code file in the repository. We learned the usage pattern of the APIs by building the bigram model using the train datasets. Two techniques, MMR and kPrecision, were used to test the model. We were able to obtain an accuracy of 60.17% for kPrecision testing when k = 5 for forward bigram model. The benefit of Automated API Recommendation is that it gives instant recommendation to the users and it supports the usage of third-party java library. As long as the third-party API is in our API knowledge based, we will be able to recommend API. |
| first_indexed | 2024-10-01T02:25:20Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/70279 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T02:25:20Z |
| publishDate | 2017 |
| record_format | dspace |
| spelling | ntu-10356/702792023-03-03T20:28:58Z Automated API Recommendation Toh, Gao Han Liu Yang School of Computer Science and Engineering DRNTU::Engineering::Computer science and engineering Many libraries have been used in the software project. With the increasing number of libraries used in a software project, developers often have to search multiple online resources to learn the usage of the APIs if the developers have no prior knowledge of certain libraries. This may lead to an increase in development time. Therefore, in this project, we developed Automated API Recommendation. Given the latest API detected, we will recommend APIs to the developers. To build the Automated API Recommendation, we had extracted the API sequence of every java source code file in the repository. We learned the usage pattern of the APIs by building the bigram model using the train datasets. Two techniques, MMR and kPrecision, were used to test the model. We were able to obtain an accuracy of 60.17% for kPrecision testing when k = 5 for forward bigram model. The benefit of Automated API Recommendation is that it gives instant recommendation to the users and it supports the usage of third-party java library. As long as the third-party API is in our API knowledge based, we will be able to recommend API. Bachelor of Engineering (Computer Science) 2017-04-18T07:39:31Z 2017-04-18T07:39:31Z 2017 Final Year Project (FYP) http://hdl.handle.net/10356/70279 en Nanyang Technological University 42 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Computer science and engineering Toh, Gao Han Automated API Recommendation |
| title | Automated API Recommendation |
| title_full | Automated API Recommendation |
| title_fullStr | Automated API Recommendation |
| title_full_unstemmed | Automated API Recommendation |
| title_short | Automated API Recommendation |
| title_sort | automated api recommendation |
| topic | DRNTU::Engineering::Computer science and engineering |
| url | http://hdl.handle.net/10356/70279 |
| work_keys_str_mv | AT tohgaohan automatedapirecommendation |