Gist to support https://www.youtube.com/watch?v=KsTMy0920go
https://github.com/darinpope/java-web-app
use the sonar
branch
class student{ | |
String ss; | |
String name; | |
public student(String ss){ | |
name = ss; | |
} | |
public student() | |
{ | |
name = "unknown"; | |
} |
Gist to support https://www.youtube.com/watch?v=KsTMy0920go
https://github.com/darinpope/java-web-app
use the sonar
branch
All Pull Requests need to reference an existing Issue. If one does not exist, first create the Issue to address your fix or additions
⛔ If you do not have access to the repo, start by forking the repo. The following can be completed on your fork.
🔑 If you do have access, the following can be done on the repo you are trying to edit.
All packages, except for Tini have been added to termux-root. To install them, simply pkg install root-repo && pkg install docker
. This will install the whole docker suite, left only Tini to be compiled manually.
The following are examples of the four types rate limiters discussed in the accompanying blog post. In the examples below I've used pseudocode-like Ruby, so if you're unfamiliar with Ruby you should be able to easily translate this approach to other languages. Complete examples in Ruby are also provided later in this gist.
In most cases you'll want all these examples to be classes, but I've used simple functions here to keep the code samples brief.
This uses a basic token bucket algorithm and relies on the fact that Redis scripts execute atomically. No other operations can run between fetching the count and writing the new count.
[Unit] | |
Description=Test NetworkNamespacePath with DynamicUser | |
After=network-online.target | |
Wants=network-online.target | |
[Service] | |
Type=simple | |
# Use DynamicUser to create a temporary user for the service | |
DynamicUser=true |
Forked from Michael Bruno
This research introduces Cohen’s Agentic Conjecture (CAC), proposing that an artificial intelligence system integrating fast, neural heuristics (System 1) with slow, symbolic logic (System 2) through a dynamic gating mechanism can exhibit emergent agentic properties. These properties include context-aware decision-making, self-directed learning, robust reasoning, and reflective self-correction. Drawing inspiration from dual-process cognitive theories and neuro-symbolic AI paradigms, this work formalizes CAC, presents a comprehensive Python implementation, and validates the conjecture through empirical experiments. The findings demonstrate that CAC-enhanced systems outperform purely neural or purely symbolic counterparts in terms of accuracy, interpretability, and adaptability. This framework lays the groundwork for developing next-generation AI agents capable of autonomous, reliable, and
# -------------------------------------------------------------------- | |
# Recursively find pdfs from the directory given as the first argument, | |
# otherwise search the current directory. | |
# Use exiftool and qpdf (both must be installed and locatable on $PATH) | |
# to strip all top-level metadata from PDFs. | |
# | |
# Note - This only removes file-level metadata, not any metadata | |
# in embedded images, etc. | |
# | |
# Code is provided as-is, I take no responsibility for its use, |
A list of resources for among us modding.
Getting started: go to https://docs.reactor.gg/docs
or: go to the website reactor.gg
, join the discord and see the pinned message in #modding