We lifted 19 functions out of this paper's own repositories and ran 0 of them in a sandbox. "Ran" means the function executed on a synthesized input and returned a value. It is not a reproduction of the paper's results.
| Repository | Role | Ran |
|---|---|---|
| microsoft/coderec_programming_states | canonical | 0 of 19 |
| Function | Status | Where it lives |
|---|---|---|
| bootstrap_confidence_interval | Not yet run | microsoft/coderec_programming_states/when_to_show/metrics_get.py code served (permissive licence) · get_code("ed19bdc4230daed5") |
| crude_label | Not yet run | microsoft/coderec_programming_states/when_to_show/get_code_label.py code served (permissive licence) · get_code("0490eac5bafb4137") |
| discretemap | Not yet run | microsoft/coderec_programming_states/between_the_lines/user_study_analysis/colorblind_colors.py code served (permissive licence) · get_code("81dc0848a2719a79") |
| entropy_single_probability | Not yet run | microsoft/coderec_programming_states/when_to_show/cdhf.py code served (permissive licence) · get_code("5397058661fb4a5c") |
| get_df_all | Not yet run | microsoft/coderec_programming_states/when_to_show/extended_logs/extended_logs_mass.py code served (permissive licence) · get_code("943614b7c2a70665") |
| get_embedding_list | Not yet run | microsoft/coderec_programming_states/when_to_show/generate_features.py code served (permissive licence) · get_code("213f0c818c404589") |
| get_extended_states | Not yet run | microsoft/coderec_programming_states/when_to_show/extended_logs/extended_logs_mass.py code served (permissive licence) · get_code("434292e5dfea98da") |
| get_features_labels | Not yet run | microsoft/coderec_programming_states/when_to_show/data_split.py code served (permissive licence) · get_code("e57f8705e5725835") |
| get_features_labels_user_study | Not yet run | microsoft/coderec_programming_states/when_to_show/data_split.py code served (permissive licence) · get_code("1bfeef7a43e6e84b") |
| get_index | Not yet run | microsoft/coderec_programming_states/between_the_lines/predict_cups/data_split.py code served (permissive licence) · get_code("53988409e494aa17") |
| local_entropy | Not yet run | microsoft/coderec_programming_states/between_the_lines/user_study_analysis/entropy_utils.py code served (permissive licence) · get_code("73a8698bc54cc3fb") |
| process_data_user_study | Not yet run | microsoft/coderec_programming_states/when_to_show/data_split.py code served (permissive licence) · get_code("4b248dd17b83c8a3") |
| retreive_logs | Not yet run | microsoft/coderec_programming_states/when_to_show/extended_logs/extended_logs.py code served (permissive licence) · get_code("380ce40e3722bc67") |
| stationary_distribution | Not yet run | microsoft/coderec_programming_states/between_the_lines/user_study_analysis/entropy_utils.py code served (permissive licence) · get_code("dfef76f9d70850bf") |
| text_features | Not yet run | microsoft/coderec_programming_states/when_to_show/generate_features.py code served (permissive licence) · get_code("6545175d9ac9fa91") |
| tol_cmap | Not yet run | microsoft/coderec_programming_states/between_the_lines/user_study_analysis/colorblind_colors.py code served (permissive licence) · get_code("9d13457c7a04bdb3") |
| tol_cset | Not yet run | microsoft/coderec_programming_states/between_the_lines/user_study_analysis/colorblind_colors.py code served (permissive licence) · get_code("52fb834d8edc9f71") |
| trajectory_entropy | Not yet run | microsoft/coderec_programming_states/between_the_lines/user_study_analysis/entropy_utils.py code served (permissive licence) · get_code("855f8589acc66aff") |
| traverse_tree | Not yet run | microsoft/coderec_programming_states/when_to_show/get_code_label.py code served (permissive licence) · get_code("cf65280e02f4e416") |
Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.
AI powered code-recommendation systems, such as Copilot and CodeWhisperer, provide code suggestions inside a programmer's environment (e.g., an IDE) with the aim of improving productivity. We pursue mechanisms for leveraging signals about programmers' acceptance and rejection of code suggestions to guide recommendations. We harness data drawn from interactions with GitHub Copilot, a system used by millions of programmers, to develop interventions that can save time for programmers. We introduce a utility-theoretic framework to drive decisions about suggestions to display versus withhold. The approach, conditional suggestion display from human feedback (CDHF), relies on a cascade of models that provide the likelihood that recommended code will be accepted. These likelihoods are used to selectively hide suggestions, reducing both latency and programmer verification time. Using data from 535 programmers, we perform a retrospective evaluation of CDHF and show that we can avoid displaying a significant fraction of suggestions that would have been rejected. We further demonstrate the importance of incorporating the programmer's latent unobserved state in decisions about when to display suggestions through an ablation study. Finally, we showcase how using suggestion acceptance as a reward signal for guiding the display of suggestions can lead to suggestions of reduced quality, indicating an unexpected pitfall.
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("2306.04930")
get_code_for_paper("2306.04930")
have("2306.04930")
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