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LS-Lab
KeYmaeraX-release
Scala2018–2022
LS-Lab / KeYmaeraX-release

KeYmaeraX-release

KeYmaera X: An aXiomatic Tactical Theorem Prover for Hybrid Systems (release)

2Distinct people
2Mentions
0Explicit recommenders
105GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

KeYmaera X: An aXiomatic Tactical Theorem Prover for Hybrid Systems (release)

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

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This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year2 dated mentions

Observed mentions: 2018-09-24 15:41:19 UTC to 2022-11-30 23:04:01 UTC.

012018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20182019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments20202021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2022

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC101
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC000
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC000
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC000
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC101

What Hacker News says

2 sources
No offense taken, I totally understand that it can come across as odd. I hope my clarification makes more sense. Once I learned more about say, why leibniz and newton came up with their formulations, and what say, the inverse of the square root of the determinant of the jacobian actually allows one to formulate (how a space "dilate" when a continuous distortion is applied to it, for example), calculus (applied calculus) became a much more interesting topic for me. While I only got so far in proving stuff about a cyber-physical I was working on, but this was really fun to learn: https://github.com/LS-Lab/KeYmaeraX-release See also: http://lfcps.org/lfcps/
In Why I am learning category theory
This was a great comment. The fact that new notations/representations (be that tests, simulations, formal methods, etc.) must justify their additional cognitive overhead is a great point. Aside from unit and integration tests, I think that substantial new notation/infrastructure is most justifiable when the second notation/setting allows you to model parts of the problem that can't be modeled in the original notation. Embedded software is a good example. Although there are some tools that allow you to model the physical system alongside the control software, typically the code is written in C and so there's no way of expressing very important aspects of the problem in the implementation language. So a second notation can help. For example, simulators and HiL setups for testing or things like https://github.com/LS-Lab/KeYmaeraX-release for
Read the rest
formal methods. Security is another good example. Typically code does not include an explicit threat model or explicit security properties, and these aspects of the problem are often scattered across the code and difficult to reason about. So being able to capture those things directly in a second notation can add a lot. For example, automatic vulnerbaility scaners for testing or https://tamarin-prover.github.io/ for formal methods. Distributed/fault-tolerant systems are yet another example where it's very hard to state the thing you want to state in the implementation language. Netflix's chaos monkey comes to mind.
In How did software get so reliable without proof? (1996) [pdf]

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