Abstract
API recommendation is crucial to improve programmers’ productivity. A lot of work has been proposed to improve the accuracy of API recommendations. In the existing work, many metrics, such as Precision, Recall, and MAP are used to evaluate the accuracy of the recommendation. These metrics can well reflect the ability to distinguish useful APIs from the candidate set, but they cannot evaluate the ability to determine the priority of useful APIs with each other. The priority between related APIs directly determines whether the recommended results are practical for developers. From this perspective, inspired by the sequence-aware recommendation, this paper constructs an API recommendation method with sequence awareness and designs new metrics to evaluate the method’s ability to determine the priority of useful APIs. The experimental results show that, compared with the baseline, the proposed method not only achieves better results on the common widely-used metrics but also outperforms the baseline method concerning the newly proposed sequence metrics.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Software Engineering and Knowledge Engineering
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
