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TestLoggingPractice

Description

This repository contains the dataset and scripts for replicating our research regarding the logging practice in test code.

RQ1

This directory contains the scripts for getting the data for rq1, including logging statements number per file, dynamic variable numbers per logging statement and static text length per logging statement.

How to run this script:

  1. Install postgresql and python 3.6+.
  2. Install libraries listed in requirements.
  3. Install cloc and srcML.
  4. Download the studied subjects (source code in head) to local.
  5. Configure the database settings in config.py.
  6. Run clone_and_save_project.py to initialize the database.
  7. Run main.py to get log numbers per file, run log_util.py to get details about the dynamic variable numbers and static text lengths of the logging statements (you need to comment and comment out some source code lines indicated in file.py and log.py).

RQ2

This directory contains the scripts that are used to analyze the histories of the studied repositories.

How to run this script:

  1. Install postgresql and python 3.6+.
  2. Install libraries listed in requirements.txt.
  3. Install cloc and srcML.
  4. Clone the studied repositories to a local path.
  5. Configure the database settings in config.py.
  6. Run clone_and_save_project.py to initialize the database.
  7. Run main.py and enter *1* to detect all the commits in the repositories.

RQ3

This directory contains the data regarding the firehouse email survey and the classification of the reasons that developers use test logging.

RQ4

This directory contains the scripts about how we extarct the log lines from the outputs and sample the log lines. It also contains the data regarding all the extrated log lines, the results of labelling the relationship and usefulness of the test logs.

Metrics Analysis

The scripts for analyzing the metrics with regard to RQ1 and RQ2 are presented in folder metrics_analysis.

Please refer to the filenames for the purpose of each script.

Database data

Please refer to here for the generated database data for RQ1 and RQ2.

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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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Repository files navigation
TestLoggingPractice
Description
This repository contains the dataset and scripts for replicating our research regarding the logging practice in test code.
RQ1
This directory contains the scripts for getting the data for rq1, including logging statements number per file, dynamic variable numbers per logging statement and static text length per logging statement.
How to run this script:
  1. Install postgresql and python 3.6+.
  2. Install libraries listed in requirements.
  3. Install cloc and srcML.
  4. Download the studied subjects (source code in head) to local.
  5. Configure the database settings in config.py.
  6. Run clone_and_save_project.py to initialize the database.
  7. Run main.py to get log numbers per file, run log_util.py to get details about the dynamic variable numbers and static text lengths of the logging statements (you need to comment and comment out some source code lines indicated in file.py and log.py).
RQ2
This directory contains the scripts that are used to analyze the histories of the studied repositories.
How to run this script:
  1. Install postgresql and python 3.6+.
  2. Install libraries listed in requirements.txt.
  3. Install cloc and srcML.
  4. Clone the studied repositories to a local path.
  5. Configure the database settings in config.py.
  6. Run clone_and_save_project.py to initialize the database.
  7. Run main.py and enter *1* to detect all the commits in the repositories.
RQ3
This directory contains the data regarding the firehouse email survey and the classification of the reasons that developers use test logging.
RQ4
This directory contains the scripts about how we extarct the log lines from the outputs and sample the log lines. It also contains the data regarding all the extrated log lines, the results of labelling the relationship and usefulness of the test logs.
Metrics Analysis
The scripts for analyzing the metrics with regard to RQ1 and RQ2 are presented in folder metrics_analysis.
Please refer to the filenames for the purpose of each script.
Database data
Please refer to here for the generated database data for RQ1 and RQ2.
About
Replication package for EMSE submission
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Readme
Activity
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3 stars
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5 watching
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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metrics_analysis
metrics_analysis
.DS_Store
.DS_Store
README.md
README.md
Repository files navigation
TestLoggingPractice
Description
This repository contains the dataset and scripts for replicating our research regarding the logging practice in test code.
RQ1
This directory contains the scripts for getting the data for rq1, including logging statements number per file, dynamic variable numbers per logging statement and static text length per logging statement.
How to run this script:
  1. Install postgresql and python 3.6+.
  2. Install libraries listed in requirements.
  3. Install cloc and srcML.
  4. Download the studied subjects (source code in head) to local.
  5. Configure the database settings in config.py.
  6. Run clone_and_save_project.py to initialize the database.
  7. Run main.py to get log numbers per file, run log_util.py to get details about the dynamic variable numbers and static text lengths of the logging statements (you need to comment and comment out some source code lines indicated in file.py and log.py).
RQ2
This directory contains the scripts that are used to analyze the histories of the studied repositories.
How to run this script:
  1. Install postgresql and python 3.6+.
  2. Install libraries listed in requirements.txt.
  3. Install cloc and srcML.
  4. Clone the studied repositories to a local path.
  5. Configure the database settings in config.py.
  6. Run clone_and_save_project.py to initialize the database.
  7. Run main.py and enter *1* to detect all the commits in the repositories.
RQ3
This directory contains the data regarding the firehouse email survey and the classification of the reasons that developers use test logging.
RQ4
This directory contains the scripts about how we extarct the log lines from the outputs and sample the log lines. It also contains the data regarding all the extrated log lines, the results of labelling the relationship and usefulness of the test logs.
Metrics Analysis
The scripts for analyzing the metrics with regard to RQ1 and RQ2 are presented in folder metrics_analysis.
Please refer to the filenames for the purpose of each script.
Database data
Please refer to here for the generated database data for RQ1 and RQ2.
About
Replication package for EMSE submission
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Readme
Activity
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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metrics_analysis
metrics_analysis
.DS_Store
.DS_Store
README.md
README.md
Repository files navigation
TestLoggingPractice
Description
This repository contains the dataset and scripts for replicating our research regarding the logging practice in test code.
RQ1
This directory contains the scripts for getting the data for rq1, including logging statements number per file, dynamic variable numbers per logging statement and static text length per logging statement.
How to run this script:
  1. Install postgresql and python 3.6+.
  2. Install libraries listed in requirements.
  3. Install cloc and srcML.
  4. Download the studied subjects (source code in head) to local.
  5. Configure the database settings in config.py.
  6. Run clone_and_save_project.py to initialize the database.
  7. Run main.py to get log numbers per file, run log_util.py to get details about the dynamic variable numbers and static text lengths of the logging statements (you need to comment and comment out some source code lines indicated in file.py and log.py).
RQ2
This directory contains the scripts that are used to analyze the histories of the studied repositories.
How to run this script:
  1. Install postgresql and python 3.6+.
  2. Install libraries listed in requirements.txt.
  3. Install cloc and srcML.
  4. Clone the studied repositories to a local path.
  5. Configure the database settings in config.py.
  6. Run clone_and_save_project.py to initialize the database.
  7. Run main.py and enter *1* to detect all the commits in the repositories.
RQ3
This directory contains the data regarding the firehouse email survey and the classification of the reasons that developers use test logging.
RQ4
This directory contains the scripts about how we extarct the log lines from the outputs and sample the log lines. It also contains the data regarding all the extrated log lines, the results of labelling the relationship and usefulness of the test logs.
Metrics Analysis
The scripts for analyzing the metrics with regard to RQ1 and RQ2 are presented in folder metrics_analysis.
Please refer to the filenames for the purpose of each script.
Database data
Please refer to here for the generated database data for RQ1 and RQ2.
About
Replication package for EMSE submission
Resources
Readme
Activity
Custom properties
Stars
3 stars
Watchers
5 watching
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0 forks
Report repository
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

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NameName
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metrics_analysis
metrics_analysis
.DS_Store
.DS_Store
README.md
README.md
Repository files navigation
TestLoggingPractice
Description
This repository contains the dataset and scripts for replicating our research regarding the logging practice in test code.
RQ1
This directory contains the scripts for getting the data for rq1, including logging statements number per file, dynamic variable numbers per logging statement and static text length per logging statement.
How to run this script:
  1. Install postgresql and python 3.6+.
  2. Install libraries listed in requirements.
  3. Install cloc and srcML.
  4. Download the studied subjects (source code in head) to local.
  5. Configure the database settings in config.py.
  6. Run clone_and_save_project.py to initialize the database.
  7. Run main.py to get log numbers per file, run log_util.py to get details about the dynamic variable numbers and static text lengths of the logging statements (you need to comment and comment out some source code lines indicated in file.py and log.py).
RQ2
This directory contains the scripts that are used to analyze the histories of the studied repositories.
How to run this script:
  1. Install postgresql and python 3.6+.
  2. Install libraries listed in requirements.txt.
  3. Install cloc and srcML.
  4. Clone the studied repositories to a local path.
  5. Configure the database settings in config.py.
  6. Run clone_and_save_project.py to initialize the database.
  7. Run main.py and enter *1* to detect all the commits in the repositories.
RQ3
This directory contains the data regarding the firehouse email survey and the classification of the reasons that developers use test logging.
RQ4
This directory contains the scripts about how we extarct the log lines from the outputs and sample the log lines. It also contains the data regarding all the extrated log lines, the results of labelling the relationship and usefulness of the test logs.
Metrics Analysis
The scripts for analyzing the metrics with regard to RQ1 and RQ2 are presented in folder metrics_analysis.
Please refer to the filenames for the purpose of each script.
Database data
Please refer to here for the generated database data for RQ1 and RQ2.
About
Replication package for EMSE submission
Resources
Readme
Activity
Custom properties
Stars
3 stars
Watchers
5 watching
Forks
0 forks
Report repository
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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10 Commits
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NameName
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RQ4
metrics_analysis
metrics_analysis
.DS_Store
.DS_Store
README.md
README.md
Repository files navigation
TestLoggingPractice
Description
This repository contains the dataset and scripts for replicating our research regarding the logging practice in test code.
RQ1
This directory contains the scripts for getting the data for rq1, including logging statements number per file, dynamic variable numbers per logging statement and static text length per logging statement.
How to run this script:
  1. Install postgresql and python 3.6+.
  2. Install libraries listed in requirements.
  3. Install cloc and srcML.
  4. Download the studied subjects (source code in head) to local.
  5. Configure the database settings in config.py.
  6. Run clone_and_save_project.py to initialize the database.
  7. Run main.py to get log numbers per file, run log_util.py to get details about the dynamic variable numbers and static text lengths of the logging statements (you need to comment and comment out some source code lines indicated in file.py and log.py).
RQ2
This directory contains the scripts that are used to analyze the histories of the studied repositories.
How to run this script:
  1. Install postgresql and python 3.6+.
  2. Install libraries listed in requirements.txt.
  3. Install cloc and srcML.
  4. Clone the studied repositories to a local path.
  5. Configure the database settings in config.py.
  6. Run clone_and_save_project.py to initialize the database.
  7. Run main.py and enter *1* to detect all the commits in the repositories.
RQ3
This directory contains the data regarding the firehouse email survey and the classification of the reasons that developers use test logging.
RQ4
This directory contains the scripts about how we extarct the log lines from the outputs and sample the log lines. It also contains the data regarding all the extrated log lines, the results of labelling the relationship and usefulness of the test logs.
Metrics Analysis
The scripts for analyzing the metrics with regard to RQ1 and RQ2 are presented in folder metrics_analysis.
Please refer to the filenames for the purpose of each script.
Database data
Please refer to here for the generated database data for RQ1 and RQ2.
About
Replication package for EMSE submission
Resources
Readme
Activity
Custom properties
Stars
3 stars
Watchers
5 watching
Forks
0 forks
Report repository
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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RQ1
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RQ3
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RQ4
metrics_analysis
metrics_analysis
.DS_Store
.DS_Store
README.md
README.md
Repository files navigation
TestLoggingPractice
Description
This repository contains the dataset and scripts for replicating our research regarding the logging practice in test code.
RQ1
This directory contains the scripts for getting the data for rq1, including logging statements number per file, dynamic variable numbers per logging statement and static text length per logging statement.
How to run this script:
  1. Install postgresql and python 3.6+.
  2. Install libraries listed in requirements.
  3. Install cloc and srcML.
  4. Download the studied subjects (source code in head) to local.
  5. Configure the database settings in config.py.
  6. Run clone_and_save_project.py to initialize the database.
  7. Run main.py to get log numbers per file, run log_util.py to get details about the dynamic variable numbers and static text lengths of the logging statements (you need to comment and comment out some source code lines indicated in file.py and log.py).
RQ2
This directory contains the scripts that are used to analyze the histories of the studied repositories.
How to run this script:
  1. Install postgresql and python 3.6+.
  2. Install libraries listed in requirements.txt.
  3. Install cloc and srcML.
  4. Clone the studied repositories to a local path.
  5. Configure the database settings in config.py.
  6. Run clone_and_save_project.py to initialize the database.
  7. Run main.py and enter *1* to detect all the commits in the repositories.
RQ3
This directory contains the data regarding the firehouse email survey and the classification of the reasons that developers use test logging.
RQ4
This directory contains the scripts about how we extarct the log lines from the outputs and sample the log lines. It also contains the data regarding all the extrated log lines, the results of labelling the relationship and usefulness of the test logs.
Metrics Analysis
The scripts for analyzing the metrics with regard to RQ1 and RQ2 are presented in folder metrics_analysis.
Please refer to the filenames for the purpose of each script.
Database data
Please refer to here for the generated database data for RQ1 and RQ2.
About
Replication package for EMSE submission
Resources
Readme
Activity
Custom properties
Stars
3 stars
Watchers
5 watching
Forks
0 forks
Report repository
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Contributors
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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TestLoggingPractice
Description
This repository contains the dataset and scripts for replicating our research regarding the logging practice in test code.
RQ1
This directory contains the scripts for getting the data for rq1, including logging statements number per file, dynamic variable numbers per logging statement and static text length per logging statement.
How to run this script:
  1. Install postgresql and python 3.6+.
  2. Install libraries listed in requirements.
  3. Install cloc and srcML.
  4. Download the studied subjects (source code in head) to local.
  5. Configure the database settings in config.py.
  6. Run clone_and_save_project.py to initialize the database.
  7. Run main.py to get log numbers per file, run log_util.py to get details about the dynamic variable numbers and static text lengths of the logging statements (you need to comment and comment out some source code lines indicated in file.py and log.py).
RQ2
This directory contains the scripts that are used to analyze the histories of the studied repositories.
How to run this script:
  1. Install postgresql and python 3.6+.
  2. Install libraries listed in requirements.txt.
  3. Install cloc and srcML.
  4. Clone the studied repositories to a local path.
  5. Configure the database settings in config.py.
  6. Run clone_and_save_project.py to initialize the database.
  7. Run main.py and enter *1* to detect all the commits in the repositories.
RQ3
This directory contains the data regarding the firehouse email survey and the classification of the reasons that developers use test logging.
RQ4
This directory contains the scripts about how we extarct the log lines from the outputs and sample the log lines. It also contains the data regarding all the extrated log lines, the results of labelling the relationship and usefulness of the test logs.
Metrics Analysis
The scripts for analyzing the metrics with regard to RQ1 and RQ2 are presented in folder metrics_analysis.
Please refer to the filenames for the purpose of each script.
Database data
Please refer to here for the generated database data for RQ1 and RQ2.
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Replication package for EMSE submission
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