They should take single matcher during construction, and their match method should take a generic range, using the new generic matcher support.

Expected usage:

REQUIRE_THAT(get_keys(), AllMatch(KeyPattern({1, 2, 3})));
REQUIRE_THAT(get_numbers(), NoneMatch(IsOdd{}));
REQUIRE_THAT(get_strings(), AnyMatch(Contains("webscale") && !Contains("MongoDB")));

the matching semantics

We've had these four methods as far back as NUnit source history goes. The double? overloads are the same as the first two overloads except that they throw InvalidOperationException if you pass null. Since they can't be used to pass null, they don't do anything that the safer double overloads don't do.

Should we obsolete them or fix them? What would fixing them look like?

name

Issue Classification

• [x ] Feature request
• Bug report

Feature Request

When generating pacts for use as a stub server the response can be bigger than the default set by Popiscle.
Popiscle supports the setting of maxBufferSize, however there currently no way of passing the value from pactJS.
I would like to add an option for this.
Just wondering anyone has an issue with thi

I would like to drop Spring Boot support for 1.5.x. It is EOL https://spring.io/blog/2018/07/30/spring-boot-1-x-eol-aug-1st-2019
I would also add some notes in the docs, that we adhere to the spring boot lifecycle in order to be transparent about dropping support for versions.

TravisCI (org) is dropping support for OSS builds at the end of this month, meaning they must be transferred to travis-ci.com, which uses a credit system. Builds may fail (and already are) if the number of credits is exhausted within th emonth.

We are recommending switching to GH Actions, but the choice of CI provider is up to the project maintainer.

See also:

• https://mailchi.mp/3d439ee

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