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|---|---|---|---|---|---|---|---|---|---|---|---|---|
bloat | 293791420dc4a1f6b3e3372f93b42337f6978e24ea5df1fac450e830f4373af9 | [
"Table 1. The evolution of our initial dataset [Alfadel M 2020] after applying each step of our data collection and data analysis approach.",
"Table 2. Statistics on the resolved and unresolved external calls during our stitching process.",
"Table 3. The status of our pull requests, proposing the removal of blo... | [
{
"Step": {
"0": "",
"1": "Data Collection",
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"3": "Data Analysis",
"4": "",
"5": ""
},
"Operation": {
"0": "Initial dataset of Python GitHub projects",
"1": "Filtering inaccessible projects",
"2": "Dependency resolution",
"3": "Partial... | [
{
"Step": {
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"1": "Data Collection",
"2": "",
"3": "Data Analysis",
"4": "",
"5": ""
},
"Operation": {
"0": "Initial dataset of Python GitHub projects",
"1": "Filtering inaccessible projects",
"2": "Dependency resolution",
"3": "Partial... | [] | [
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"caption": "Fig. 1. The overview of our approach for studying bloated code in PyPI ecosystem.",
"reason": "not_struct... | true | null | [
"Fig. 5. The distribution of bloat metrics per granularity. Each entry indicates the percentage of bloated entities (e.g., files, methods), and the size of bloated dependency code compared to the overall LoC.",
"Fig. 6. The distribution of bloat metrics per vulnerability exposure. Each entry indicates the relatio... | [
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"data": {
"Package": {
"Bloated LoC": {
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"q1": 6,
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"mean": 34,
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"Bloated entries": {
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"q1": 33,
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... | [
"{\"data\": {\"Package\": {\"Bloated LoC\": {\"min_whisker\": \"<obf>\", \"q1\": \"<obf>\", \"median\": \"<obf>\", \"mean\": \"<obf>\", \"q3\": \"<obf>\", \"max_whisker\": \"<obf>\"}, \"Bloated entries\": {\"min_whisker\": \"<obf>\", \"q1\": \"<obf>\", \"median\": \"<obf>\", \"mean\": \"<obf>\", \"q3\": \"<obf>\", ... |
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