Startrekzky commented on code in PR #712:
URL: 
https://github.com/apache/incubator-devlake-website/pull/712#discussion_r1477998002


##########
docs/Metrics/CFR.md:
##########
@@ -25,7 +25,17 @@ The number of deployments affected by incidents/total number 
of deployments. For
 
 When there are multiple deployments triggered by one pipeline, tools like 
GitLab and BitBucket will generate more than one deployment. In these cases, 
DevLake will consider these deployments as ONE deployment and use the last 
deployment's finished date as the deployment finished date.
 
-Below are the benchmarks for different development teams from Google's report. 
However, it's difficult to tell which group a team falls into when the team's 
change failure rate is `18%` or `40%`. Therefore, DevLake provides its own 
benchmarks to address this problem:
+Below are the 2023 DORA benchmarks for different development teams from 
Google's report. However, it's difficult to tell which group a team falls into 
when the team's change failure rate is `13%` or `30%`. Therefore, DevLake 
provides its own benchmarks to address this problem:
+
+| Groups            | Benchmarks | DevLake Benchmarks |
+| ----------------- | ---------- | ------------------ |
+| Elite performers  | 5%        | 0%-5%              |

Review Comment:
   I suggest updating the the DevLake Benchmarks to a preciser manner, which is:
   ```
   (0, 5%]
   (5%, 10%]
   ...
   ```



##########
docs/Metrics/MTTR.md:
##########
@@ -23,7 +23,17 @@ MTTR = Total [incident age](./IncidentAge.md) (in 
hours)/number of incidents.
 
 If you have three incidents that happened in the given data range, one lasting 
1 hour, one lasting 2 hours and one lasting 3 hours. Your MTTR will be: (1 + 2 
+ 3) / 3 = 2 hours.
 
-Below are the benchmarks for different development teams from Google's report. 
However, it's difficult to tell which group a team falls into when the team's 
median time to restore service is `between one week and six months`. Therefore, 
DevLake provides its own benchmarks to address this problem:
+Below are the 2023 DORA benchmarks for different development teams from 
Google's report. However, it's difficult to tell which group a team falls into 
when the team's median time to restore service is `between one week and six 
months`. Therefore, DevLake provides its own benchmarks to address this problem:
+
+| Groups            | Benchmarks                   | DevLake Benchmarks        
   |
+| ----------------- | ---------------------------- | 
---------------------------- |
+| Elite performers  | Less than one hour           | Less than one hour        
   |
+| High performers   | Less one day                 | Less than one day         
   |

Review Comment:
   Less than one day?
   
![image](https://github.com/apache/incubator-devlake-website/assets/14050754/d748c046-bbbe-4d3c-a424-b8c0ab26083e)
   



##########
docs/Metrics/DeploymentFrequency.md:
##########
@@ -25,7 +25,20 @@ Deployment frequency is calculated based on the number of 
`deployment days`, not
 
 When there are multiple deployments triggered by one pipeline, tools like 
GitLab and BitBucket will generate more than one deployment. In these cases, 
DevLake will consider these deployments as ONE deployment and use the last 
deployment's finished date as the deployment finished date.
 
-Below are the benchmarks for different development teams from Google's report. 
DevLake uses the same benchmarks.
+Below are the 2023 DORA benchmarks for different development teams from 
Google's report. DevLake uses the same benchmarks.

Review Comment:
   The correct expression should be:
   ```
   ... from Google's report. However, it's difficult to tell which group a team 
falls into when the team's deployment frequency is `between once per week and 
once per month`. Therefore, DevLake provides its own benchmarks to address this 
problem:
   ```



##########
docs/Metrics/CFR.md:
##########
@@ -25,7 +25,17 @@ The number of deployments affected by incidents/total number 
of deployments. For
 
 When there are multiple deployments triggered by one pipeline, tools like 
GitLab and BitBucket will generate more than one deployment. In these cases, 
DevLake will consider these deployments as ONE deployment and use the last 
deployment's finished date as the deployment finished date.
 
-Below are the benchmarks for different development teams from Google's report. 
However, it's difficult to tell which group a team falls into when the team's 
change failure rate is `18%` or `40%`. Therefore, DevLake provides its own 
benchmarks to address this problem:
+Below are the 2023 DORA benchmarks for different development teams from 
Google's report. However, it's difficult to tell which group a team falls into 
when the team's change failure rate is `13%` or `30%`. Therefore, DevLake 
provides its own benchmarks to address this problem:

Review Comment:
   The correct expression should be:
   ```
   However, it's difficult to tell which group a team falls into when the 
team's change failure rate is between 15% and 64%. Therefore, DevLake provides 
its own benchmarks to address this problem:
   ```



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