Are there any projects on codeberg that are getting banned and actually have significant human interest?

If codeberg decided to kick out spammers, nobody would decry the loss, so what's being lost here? Is it strictly slippery slope?

The 1.8% feels high if it's trivially dead. When I've run simple static analysis on decent codebases before, it's been much lower. For non-trivial dead code, it might be low. E.g. a lot of projects have piles of "dead" code behind ancient feature flags that would never be switched.

A small amount of dead code is fine. E.g. it might not be worth deleting utility methods that you happen to remove the last use of if they are simple and you might re-add a use later. Generated code is often dead since it's not worth specifying to the generator exactly what will be used. Other times, deleting dead code can lead to a valuable cascade of other deletions and simplifications.

    static JsonObject of(Map map);

    static JsonObject of(Map map);

It does seem like any serious application is going to use another library, and this will be useful for very simple json usage or single-file hello-world type programs (e.g. to go along with Implicitly Defined Classes and the Flexible Launch Protocol).

All the surrounding systems still run at full speed. You can travel large distances and still arrive soon enough to matter in the fight. You can also die, respawn in another system, rejoin the fight, and barely miss anything. The positions in the fight therefore move even slower than time-dilation since ships on both sides are replaced so quickly.

Large groups have a massive advantage over small groups, so alliances are very large and join various alliances-of-alliances. The playerbase is often organized into only 2-3 major coalitions. At some points in history, nearly all the alliances have joined the same coalition, which leads to a strange pax-Romana called the "blue donut" (referring to all the ownable outer-systems being "blue" or allied with each other).

Also, nearly every player in a large fight just follows simple orders. Orbit A and shoot B. There are just a few people calling the shots.

Fights sometimes end just because people are bored, need to sleep, or go to work.

If you use ordinary READ COMMITTED transactions, they will advance their xmin horizons on each query (and allow old version cleanups) up until their own transaction id but unfortunately not beyond that. For a given table, this is important since that transaction is uncommitted and it might modify the table. If you could make long-running transactions readonly on those specific tables, then you could use a different xmin horizon specifically for those tables. It would require a lot of duplicative bookkeeping in shared memory though. You could probably fake this today by using 2 databases on the same machine and using two-phase-commit+dblink/fdw for cross-database transactions/queries (fdw uses repeatable read in transactions, so it won't allow the xmin to advance).

It seems like most customers are returning the oven, which would normally be an extremely strong signal that there is a quality problem. In the SaaS world, the equivalent would be churn, but it's not always as straightforward since if users quit before they sign up (e.g. by reading a review or using a free trial), then they don't show up in that metric.

This could all be optics as well to try to give the appearance of a defensible moat. E.g. they can claim to investors that they are able to protect a significant chunk of their intellectual property this way. I'm not sure if anyone has a study about how significant the summarization is to distillation.

1. No overlay networks. 1 IP per machine. pods use dynamically allocated ports, and the kubelet enforces pods listen only on their assigned ports using seccomp.

2. No kube-proxy or equivalent Layer-4 "load-balancer". It's not good, but it's often used. You should use some kind of Layer-7 load balancing instead. Also you need to look up the port number from (1). This also greatly lessens the need for DNS.

3. A better config language. YAML and helm templates are terrible. kustomize is built into kubectl, but it's frustratingly limiting and also still very complicated. Something like nix would have been great. This can make it easier to upgrade third party configs since you can have more logic to validate and merge your settings with upstream defaults or templates.

4. Maybe an EBF-like for the api server? If the built-in k8s objects don't have a setting for something, then you need to write an operator or control loop yourself and then run that too, which is a big lift. Over time, k8s just keeps adding more and more built-in things and then revising them, which creates a ton of churn. If you could easily script simple operations, then they wouldn't have to build in every permutation ahead of time. E.g. the HorizontalPodAutoscaler has 24 config object types with several fields each, but all it does is set replicas based on data read from the api-server, so it could be replaced by some kind of flexible script that runs in the control plane.

1: https://finance.yahoo.com/markets/stocks/articles/alphabet-s...

This is also a really extreme version of the prisoners dilemma. In the standard formula, there are 2 prisoners, so it's somewhat practical to not defect, but there are hundreds of thousands of qualified candidates for working at Meta in these roles, so your personal decision to defect or not has likely no effect on the ultimate outcome. I.e. for the second option to work, you actually need to organize a unified labor movement with no defectors, which is probably impossible.

E.g. the jwt auth example has some major problems since the verification rules aren't fully specified in the spec. The jwt-token verified rule only checks that the string isn't empty, but it doesn't actually verify that it is correctly parsed, non-expired, and signed by a trusted key. The authenticated-user rule doesn't check that the user-id actually came from the jwt. If you hand-wrote your constructor, you would ensure these things. Similarly, all the other constructors allow passing in whatever values you like instead of checking the connections of the real objects.

By calling the constructor for these types, you are making an assertion about the relationship of the parameter values. If AI is calling the constructor, then it's able to make it's own assertions and derive whatever result it wants. That seems backwards. AI should use the result of tenant-access to deduce that a user is a member of tenant, but if they can directly call `(tenant-access user-id tenant-id true)`, then they can "prove" tenant-access for anything. In the past, we have named the constructors for these types `TenantAccess.newUnverified`, and then heavily scrutinized all callers (typically just jwt-parsers and specific database lookups). You can then use `TenantAccess.{userId,tenantId}` without scrutiny elsewhere.

If you don't drop any spans from a trace, you can completely disambiguate a collision since the trace will have two distinct root spans. If you are missing spans, you might have a break in the parent-child links.

Even with infinite retention, your analysis will bucket by time somehow, so a collision might have no effect if the collision doesn't happen at a proximate time. If you are manually looking at traces, it will be very obvious there is a collision unless they happen at the same time.

Also, birthday paradox only expresses probability that there is a collision somewhere, but if you are filtering or looking at single spans, then the probabiliy that you actually see a collision is greatly reduced.

I think for basically all systems, an additional 64-bits has insignificant additional cost, so you may as well prevent collisions, but I think it could be a reasonable tradeoff if it mattered.

I wonder if this phrase has different connotations among other English readers? A lot of these comments are fairly early for US timezones.