Currently the "introduced in version xyz" documentation placeholder uses format "... in Catch X.Y.Z". It should use "Catch2" instead, because that is the name of the project, and we should keep our documentation consistent.

Changes needed;

• Update tools/scripts/releaseCommon.py to look for, and write out, new placeholder
• Update docs/contributing.md to mention the new plac

If I create a test using a testcase source with a name "{m} (unique attribute)" and pass that test in through -testlist argument the test will not be discovered. If there is no space "{m}(unique attribute)" this works fine. The problem is in the TextRunner.MakeRunSetting when its building the prefilter list from the test list it is not trimming the sub string so the parent of the tests are not bei

In a pact-node consumer test, I have -

describe('edit a policy', () => {
    const REQUEST_BODY = {
      name: 'account-holder',
      version: '2020-07-10T01:22:09.488Z',
    };
    const RESPONSE_BODY = {
      name: Matchers.like('account-holder'),
      version: Matchers.ISO8601_DATETIME_WITH_MILLIS_FORMAT,
      additionalAttributes: Matchers.like({}),
    };
    beforeEach(

Hi,
Currently I am using spring boot version 2.1.6 and chaos monkey version 2.1.1

I have a final class with @component annotation, unfortunately it is imported from a third party library and thus cannot be made "non-final".

The issue I am facing is as follows:
When I start my application the SpringComponentAspect tries to do a pointcut on all the classes in my application that ha

As part of the process of making the Pact docs more user friendly, we'd like to start writing feature documentation once, and providing code examples for each of the languages, rather than everyone having to write the same docs over and over again in each language.

The documentation for the consumer version selectors can be our first opportunity to give this approach a try. I have written the beh

Feature request

Is your feature request related to a problem? Please describe

The analysis.py script provides just one confidence interval: 95%. While that is related to the 2-sigma interval of normal distribution, so in theory allows for easy estimation of bigger confidence intervals (like 3, 4, 5-sigma), it assumes a normal distribution, which the differences don't follow, and may be