kannangce

I'm trying out a code generation problem using open-source transformer models. With almost all of the models, the context window size seems to be a problem.

I had a thought that, instead of generating the code for the target language directly, what if we can generate a concise code and transpile it? In that approach, I feel generation could be in some LISP dialect and from there transpilation could be to any language. Of course APL can be an intermediate language here but that has other challanges like learning, custom keyboard, etc.

Does this approach seems viable?

It's being mentioned that Io language is homoiconic.

To me homoiconic means "Expressing the language in the data-structure of the same langage" . For exp, LISP, is all LISP list.

I'm trying to understand Io is homoiconic?

Though I can see that the Io programs are objects and message, a given statement is not a data-structure of the language per se.

For example, can someone explain how this statement is homoiconic,

``` Number / := method (i, if (i != 0, self origDiv(i), 0) )

```

For one of my use case, we have to render pages generated from almost a static data available in DB.

I'm wondering if we can have hugo(/any static site) to use DB as a datasource to get the data from DB for site generation. Do we have a plugin that could support that?

I was going through the paper [Password Security: A Case History][1] By Robert Morris and Ken Thompson on authentication. It has been mentioned in the First Scheme that the first encryption used m209, in which they used the user password as the key.

The respective excerpt is,

> Most of the standard encryption methods used (in the past) for > encryption of messages are rather easy to invert. A convenient and > rather good encryption program happened to exist on the system at the > time; it simulated the M-209 cipher machine [1] used by the U.S. Army > during World War II. It turned out that the M-209 program was usable, > but with a given key, the ciphers produced by this program are trivial > to invert. It is a much more difficult matter to find out the key > given the cleartext input and the enciphered output of the program. > Therefore, the password was used not as the text to be encrypted but > as the key, and a constant was encrypted using this key. The encrypted > result was entered into the password file.

As read through the m209 further, seems like the key wheel can have 6 wheels, in which we can set/unset a specific alphabet.

There are some constraints here, - Only alphabets can be used in the key. - They are case insensitive. - Not all the wheels contain all the alphabets that are needed.

Given these constraints, any idea what were the constraints on the passwords imposed by the first generation encryption of the password?

  [1]: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.128.1635&rep=rep1&type=pdf

I'm playing around with Kerberos SSO. As experimented so far,

-When I open a web app that is configured with Kerberos, from the browser, it prompts me for the username and credential, once I enter, I'm logged into the web app .

- When I do a kinit from the terminal and give my credentials, I'm signed into the KDC for the given user. After kinit, when I open a web app I'm signed into the web app, without any credentials.

One possible explanation is, when I do a kinit, the TGT is stored in the OS which is available for other clients in the host machine so that my browser was able to use that TGT without prompting me for password.

Now my questions are,

- Will I be able to cache the TGT without using kinit? - If yes, how can I do it using a Java client? - If the answer for the first question is yes, will I be able to do it from my web app opened in the browser?

Related SoF:

https://stackoverflow.com/questions/58912508/caching-tgt-from-browser-other-krb5-client

I am in the process of choosing data storage for my event-series DB. There are various opinions on using RDMS, NoSQL or Columnar. Was there any exploration done on using Time-series DB for event-sourcing other than TimeScaleDB(https://blog.timescale.com/time-series-data-why-and-how-to-use-a-relational-database-instead-of-nosql-d0cd6975e87c/)? Or is it even a good idea to use Time-Series DB for event sourcing?