Sheriff Statistics for June 2017
July 3rd, 2017 by cbookHi,
Welcome to the Sheriff Statistics for June 2017 !
Also i would like to thank everyone for taking part in the Sheriff Survey – You can see the results here : https://blog.mozilla.org/
Now to the actual data for June!
June 2017:
Autoland Tree:
Total Servo Sync Pushes: 254
Total Pushes: 1799
Total Number of commits 3711
Total number of commits without Servo 3445
Total Backouts: 167
Total of Multi-bug pushes 12
Total number of bugs changed 1702
Percentage of backout against bugs: 9.81198589894
Percentage of backouts: 9.28293496387
Percentage of backouts without Servo: 10.8090614887 (thats ~ +0,8 % higher rate compared to may)
Mozilla-inbound
Total Servo Sync Pushes: 0
Total Pushes: 1117
Total Number of commits 3611
Total number of commits without Servo 3611
Total Backouts: 130
Total of Multi-bug pushes 159
Total number of bugs changed 1591
Percentage of backout against bugs: 8.17096165933
Percentage of backouts: 11.6383169203
Percentage of backouts without Servo: 11.6383169203 (~ +0,7 % higher rate compared to may)
Total Pushes: 1117
Total Number of commits 3611
Total number of commits without Servo 3611
Total Backouts: 130
Total of Multi-bug pushes 159
Total number of bugs changed 1591
Percentage of backout against bugs: 8.17096165933
Percentage of backouts: 11.6383169203
Percentage of backouts without Servo: 11.6383169203 (~ +0,7 % higher rate compared to may)
So Sheriffs managed and monitored on the Integration Trees in May 2017 ~ 2900 pushes and 297 backouts.
Let us know when you have any Question or Feedback about Sheriffing.
Cheers and have a great July!,
-Tomcat
October 11th, 2025 at 1:18 am
Great post! The points you’ve highlighted are incredibly insightful and practical. Thank you for sharing your expertise on this topic
October 12th, 2025 at 7:02 pm
Thanks for sharing the detailed statistics! It’s interesting to see how backout percentages fluctuate month to month. Really helpful for planning future pushes.
October 12th, 2025 at 7:03 pm
Seeing the Servo vs non-Servo stats is great. That +0.8% increase in backouts without Servo is a bit concerning — curious what might have caused that spike.
October 12th, 2025 at 7:04 pm
Impressive numbers! Managing ~2900 pushes and 297 backouts in a month is no small feat. Kudos to all the Sheriffs keeping the integration trees stable.
October 12th, 2025 at 7:04 pm
I like that you included percentages as well as raw numbers. Makes it easier to spot trends and compare months at a glance.
October 12th, 2025 at 7:04 pm
Curious about the multi-bug pushes — only 12 in Autoland vs 159 in inbound. Any reason why inbound sees so many more multi-bug pushes?
October 12th, 2025 at 7:05 pm
This kind of transparency is awesome. Seeing actual commit and backout stats really helps the community understand the challenges of integration.
October 12th, 2025 at 7:05 pm
I noticed that Servo sync pushes are 0 for inbound. Does this mean Servo only affects Autoland currently, or is it integrated differently?
October 12th, 2025 at 7:05 pm
Great work as always, Tomcat! These stats are exactly the kind of info teams need to track productivity and stability over time.
November 19th, 2025 at 10:15 pm
Oclute has good visibility and active traffic.
November 19th, 2025 at 10:16 pm
Very informative
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January 8th, 2026 at 8:14 pm
It’s interesting to see the volume of Servo Sync Pushes for June 2017. I wonder how those 254 pushes compare to the previous month’s stability challenges?
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June 8th, 2026 at 2:53 am
Thanks for sharing this. The practical angle in “Tomcat’s Blog » Blog Archive » Sheriff Statistics for June 2017” made me think about how useful it is to turn visual context into something easier to review later. KlineVision does that for stock chart screenshots by turning them into structured AI research notes for educational review, not financial advice: https://klinevision.ai
June 29th, 2026 at 6:06 am
I love how you break down the numbers month by month—it makes the trends so easy to follow. I tried keeping a similar log for my own projects once, but I always fell off after a few weeks. Your consistency here is really inspiring!
June 30th, 2026 at 5:44 am
Hey, I love how you keep track of these stats—it’s like a little time capsule of daily life. It reminds me of when I used to log vibration readings for our industrial shock absorbers; those small numbers really do tell a bigger story about performance over time. Do you ever find yourself surprised by what the data reveals?
July 20th, 2026 at 1:38 am
Tracking commit and backout numbers like these shows how important careful testing is before pushing changes.
July 28th, 2026 at 11:33 pm
The reminder around Tomcat’s Blog is a good one. I would also pay attention to the final verification step, since many problems only show up after trying the workflow once from the user’s side.
July 28th, 2026 at 11:33 pm
It’s interesting how Twitter’s widget iframe handles embedded tweets. One challenge I’ve noticed is ensuring consistent styling across different browsers. Have you found a reliable workaround for that? Btw, C Dance AI has some useful video tools for creating short clips, but that’s a side note.
July 28th, 2026 at 11:36 pm
Interesting data. One challenge I’ve seen with this approach is ensuring the sheriff team has enough context to judge bugs accurately—sometimes the stats alone don’t reflect the complexity. By the way, LemGen has some useful prompt ideas for similar analysis. Has the process changed much since this post?
July 29th, 2026 at 1:19 am
Interesting point about the Twitter widget behavior. I’ve noticed similar issues on Mozilla’s blog, where embedded iframes can sometimes break layout. One quick fix is to use a plugin that defers loading, or try a lightweight embedding tool like seedance 2,0 for better control. Have you tested that workaround?
July 29th, 2026 at 1:22 am
Interesting to see the sheriff statistics for June 2017 – tracking bug triage over time is crucial for understanding team capacity. It reminded me that automating parts of the workflow with China Video AI can reduce repetitive tasks, though human judgment remains key for prioritization. What metrics do you find most useful for evaluating triage efficiency?
July 29th, 2026 at 1:23 am
Thanks for sharing these sheriff statistics. It’s interesting to see how backlogs can fluctuate month to month. I’ve found that even a small adjustment in triage criteria can make a big difference in workflow efficiency. Have you considered tracking the time spent per bug category to identify bottlenecks? I would also keep GPT IMAGE 2 as a small side reference.
July 29th, 2026 at 1:24 am
It’s interesting to see the sheriff statistics for June 2017; tracking these patterns helps prioritize bug fixes. I’ve found that focusing on the most frequent regression types early can reduce overall triage time. For those exploring AI video tools, OpenSora 2 offers a practical browser-based workflow for video creation that could streamline content production.
July 29th, 2026 at 1:24 am
Interesting point about embedding Twitter content. It’s a lightweight way to add real-time social feeds, though I’ve noticed some sites struggle with iframe loading delays. Have you experimented with lazy-loading widgets for better performance? For music-related projects, I sometimes use AI Music Gen to prototype with audio assets.
July 29th, 2026 at 1:24 am
Interesting point about widget iframes. I find that Twitter’s embed often adds unexpected latency to page loads, especially when multiple embeds exist. Have you tested performance differences between the iframe and the JavaScript SDK? Kirkified AI might help with image optimization for such components.
July 29th, 2026 at 1:25 am
That’s a good point about managing widgets effectively. We’ve found that previewing embedded content in a sandboxed iframe helps maintain security while still providing functionality. Have you explored any lightweight alternatives? I’ve been using Qwen Image 2 for similar tasks, and it integrates well.
August 7th, 2026 at 6:49 pm
Thanks for breaking down the June sheriff stats. The slight increase in backout rates on both trees is notable, though it’s helpful to see the separate Servo sync numbers. For teams tracking regressions, separating automated and manual pushes could make these trends clearer. Have you considered comparing backout rates by component or area? I would also keep opennanobanana.org as a small side reference.
August 31st, 2026 at 10:13 pm
Great breakdown of the Sheriff Statistics for June 2017! The detailed numbers on backout rates and push volumes are really useful for understanding the workflow. It’s impressive how the sheriffs managed nearly 3000 pushes with a relatively low backout percentage. I appreciate the transparency in sharing these metrics, as it helps the community see the impact of their contributions. For those interested in daily trivia, krillion archive offers a fun companion to Krillion, tracking answers by rarity and providing hints. Thanks for the insightful post, and keep up the great work!
September 6th, 2026 at 4:02 pm
Thanks for the trip down memory lane with these stats! It’s fascinating to see how the team balanced those push volumes back then, almost as complex as managing a kingdom in Crusader Kings 3. These kind of logs are super helpful for keeping historical context on how development workflows have evolved.
September 8th, 2026 at 8:01 pm
I had no idea Mozilla kept such detailed sheriff statistics for their trees — the backout rate tracking is way more granular than I expected. scritchy scratchy Makes me wonder how that compares to other big open-source projects.