In:
International Journal of Software Engineering and Knowledge Engineering, World Scientific Pub Co Pte Ltd, Vol. 32, No. 08 ( 2022-08), p. 1203-1228
Kurzfassung:
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.
Materialart:
Online-Ressource
ISSN:
0218-1940
,
1793-6403
DOI:
10.1142/S0218194022500437
Sprache:
Englisch
Verlag:
World Scientific Pub Co Pte Ltd
Publikationsdatum:
2022
