This work was supported in part by National Natural Science Foundation of China (Grant Nos. 61672470, 61640221, 61562026).
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Figure 1
(Color online) Schematic of GKSR.
Figure 2
(Color online) Example of an R&C pair.
Figure 3
(Color online) Flowchart of contents of Section 3.
Figure 4
Evaluation strategy.
Figure 5
(Color online) Development process of the code search.
| Component | Query results | ||
| GK-based component | $c_{1}$ | $c_{2}$ | $c_{3}$ |
| API-based component | $c_{1}$ | $c_{2}$ | $a_{3}$ |
| CK-based component | $b_{1}$ | $c_{2}$ | $a_{3}$ |
| Relevance rating | Relevance score | Similarity score (%) | Tag |
| 4 | $15~=~2^{4}-1$ | $>85$ | Most relevant |
| 3 | $7~=~2^{3}-1$ | 70–85 | Relevant |
| 2 | $3~=~2^{2}-1$ | 60–70 | Irrelevant |
| 1 | $0~=~2^{0}-1$ | $<60$ | Most irrelevant |
| rank | qid | $f_{1}$ | $f_{2}$ | $f_{3}$ |
| 2 | 1 | 0.673 | 0.725 | 0 |
| 1 | 1 | 0.849 | 0 | 0.784 |
| Tuning set | Training set | Testing set |
| 8850 artificial Q&R pairs | 4425 artificial Q&R pairs | 4425 artificial Q&R pairs; 54 real Q&R pairs |
| Real testing set | Artificial testing set | ||||
| Metrics | Methods | Top-1 | Top-5 | Top-1 | Top-5 |
| GKSR$_{\rm~noSVM}$ | $\textbf{0.757}^{+0.003,0.002}$ | $\textbf{0.743}^{+0.002,0.002}$ | $\textbf{0.771}^{+0.005,0.003}$ | $\textbf{0.756}^{+0.003,0.001}$ | |
| Precision | QECK | 0.659 | 0.603 | 0.666 | 0.620 |
| CodeHow | 0.623 | 0.572 | 0.632 | 0.589 | |
| GKSR$_{\rm~noSVM}$ | $\textbf{0.6914}^{+0.004,0.002}$ | $\textbf{0.6795}^{+0.003,0.002}$ | $\textbf{0.7123}^{+0.006,0.005}$ | $\textbf{0.6917}^{+0.002,0.002}$ | |
| NDCG | QECK | 0.5663 | 0.5092 | 0.5785 | 0.5302 |
| CodeHow | 0.5196 | 0.4611 | 0.5398 | 0.4821 | |
The
| Query terms (number of times that occur) | ||
| APIs | Crowd knowledge | |
| CodeHow | multiple (1) | |
| QECK | screenshot (76), Android (49) | |
| GKSR$_{\rm~noSVM}$ | multiple (6) | screenshot (18), Android (4) |
| Real testing set | Artificial testing set | ||||
| Metrics | Methods | Top-1 | Top-5 | Top-1 | Top-5 |
| GKSR | $\textbf{0.822}^{+0.006}$ | $\textbf{0.804}^{+0.004}$ | $\textbf{0.832}^{+0.005}$ | $\textbf{0.803}^{+0.003}$ | |
| Precision | GKSR$_{\rm~noSVM}$ | 0.757 | 0.743 | 0.771 | 0.756 |
| GKSR | $\textbf{0.8013}^{+0.005}$ | $\textbf{0.7733}^{+0.004}$ | $\textbf{0.8189}^{+0.003}$ | $\textbf{0.7795}^{+0.003}$ | |
| NDCG | GKSR$_{\rm~noSVM}$ | 0.6914 | 0.6795 | 0.7123 | 0.6917 |
The
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