Trending: Prepare static content for the new UTI

[csit.git] / docs / cpta / methodology / trend_analysis.rst

diff --git a/docs/cpta/methodology/trend_analysis.rst b/docs/cpta/methodology/trend_analysis.rst
index 5a48136..2bb5499 100644 (file)
--- a/docs/cpta/methodology/trend_analysis.rst
+++ b/docs/cpta/methodology/trend_analysis.rst
@@ -11,65 +11,12 @@ is called a trend for the group.
 All the analysis is based on finding the right partition into groups
 and comparing their trends.
 
 All the analysis is based on finding the right partition into groups
 and comparing their trends.
 

-Trend Compliance
-~~~~~~~~~~~~~~~~
-
-.. _Trend_Compliance:
-
-Trend compliance metrics are targeted to provide an indication of trend
-changes, and hint at their reliability (see Common Patterns below).
-
-There is a difference between compliance metric names used in this document,
-and column names used in :ref:`Dashboard` tables and Alerting emails.
-In cases of low user confusion risk, column names are shortened,
-e.g. Trend instead of Last Trend.
-In cases of high user confusion risk, column names are prolonged,
-e.g. Long-Term Change instead of Trend Change.
-(This document refers to a generic "trend",
-so the compliance metric name is prolonged to Last Trend to avoid confusion.)
-
-The definition of Reference for Trend Change is perhaps surprising.
-It was chosen to allow both positive difference on progression
-(if within last week), but also negative difference on progression
-(if performance was even better somewhere between 3 months and 1 week ago).
-
-In the table below, "trend at time <t>", shorthand "trend[t]"
-means "the group average of the group the sample at time <t> belongs to".
-Here, time is usually given as "last" or last with an offset,
-e.g. "last - 1week".
-Also, "runs[t]" is a shorthand for "number of samples in the group
-the sample at time <t> belongs to".
-
-The definitions of compliance metrics:
-
-+-------------------+-------------------+---------------------------------+-------------+-----------------------------------------------+
-| Compliance Metric | Legend Short Name | Formula                         | Value       | Reference                                     |
-+===================+===================+=================================+=============+===============================================+
-| Last Trend        | Trend             | trend[last]                     |             |                                               |
-+-------------------+-------------------+---------------------------------+-------------+-----------------------------------------------+
-| Number of runs    | Runs              | runs[last]                      |             |                                               |
-+-------------------+-------------------+---------------------------------+-------------+-----------------------------------------------+
-| Trend Change      | Long-Term Change  | (Value - Reference) / Reference | trend[last] | max(trend[last - 3mths]..trend[last - 1week]) |
-+-------------------+-------------------+---------------------------------+-------------+-----------------------------------------------+
-
-Caveats
--------
-
-Obviously, if the result history is too short, the true Trend[t] value
-may not by available. We use the earliest Trend available instead.
-
-The current implementation does not track time of the samples,
-it counts runs instead.
-For "- 1week" we use "10 runs ago, 5 runs for topo-arch with 1 TB",
-for "- 3mths" we use "180 days or 180 runs ago, whatever comes first".
-

 Anomalies in graphs
 ~~~~~~~~~~~~~~~~~~~
 
 Anomalies in graphs
 ~~~~~~~~~~~~~~~~~~~
 

-In graphs, the start of the following group is marked
-as a regression (red circle) or progression (green circle),
-if the new trend is lower (or higher respectively)
-then the previous group's.
+In graphs, the start of the following group is marked as a regression (red
+circle) or progression (green circle), if the new trend is lower (or higher
+respectively) then the previous group's.

 
 Implementation details
 ~~~~~~~~~~~~~~~~~~~~~~
 
 Implementation details
 ~~~~~~~~~~~~~~~~~~~~~~


@@ -77,18 +24,17 @@ Implementation details
 Partitioning into groups
 ------------------------
 
 Partitioning into groups
 ------------------------
 

-While sometimes the samples within a group are far from being
-distributed normally, currently we do not have a better tractable model.
+While sometimes the samples within a group are far from being distributed
+normally, currently we do not have a better tractable model.

 
 

-Here, "sample" should be the result of single trial measurement,
-with group boundaries set only at test run granularity.
-But in order to avoid detecting causes unrelated to VPP performance,
-the current presentation takes average of all trials
-within the run as the sample.
-Effectively, this acts as a single trial with aggregate duration.
+Here, "sample" should be the result of single trial measurement, with group
+boundaries set only at test run granularity. But in order to avoid detecting
+causes unrelated to VPP performance, the current presentation takes average of
+all trials within the run as the sample. Effectively, this acts as a single
+trial with aggregate duration.

 
 

-Performance graphs show the run average as a dot
-(not all individual trial results).
+Performance graphs show the run average as a dot (not all individual trial
+results).

 
 The group boundaries are selected based on `Minimum Description Length`_.
 
 
 The group boundaries are selected based on `Minimum Description Length`_.