That would be a way to go, though iterating through all possibilities of a
similar letter misspell would take significantly more processing (4x3x3
= 36 total possibilities, only to cull it back to 2, in your example), than
iterating through a list of pre-calculated possibilities. It's definitely
no
Hi Brooks,
I've been already thinking about eat -> cat typing mistake. Actually there
may be simplier solution than having wordlist with duplicated words.
Because there's already a mapping of similar characters in the source code
(currently only in unit test, but it can be moved), when user type a
The problem with this is that you might have word A which is similar to B,
but B is also similar to C. So we scrub B from the list, someone enters B,
and we have no way to know if it means A or C. It leads to a much more
complicated scheme to ensure that all errors are correctable.
Scrubbing A,
I was inspired to join the mailing list to comment on some of these
discussions about BIP39, which I think will have great use in the Bitcoin
community and outside it as a way to transcribe binary data.
The one thought I had as the discussions about similar characters are
resulting in culling word
I've just pushed updated wordlist which is filtered to similar characters
taken from this matrix.
BIP39 now consider following character pairs as similar:
similar = (
('a', 'c'), ('a', 'e'), ('a', 'o'),
('b', 'd'), ('b', 'h'), ('b', 'p'), ('b', 'q'), ('b', 'r'),
I think this is a good idea; I just pushed new unit test test_similarity()
to github which finds such similar words. Right now it identifies ~90
similar pairs in current wordlist, I'll update wordlist tomorrow to pass
this test.
slush
On Sat, Oct 19, 2013 at 1:52 AM, jan wrote:
>
> I think avoi
On 19/10/13 01:58, Gregory Maxwell wrote:
> https://people.xiph.org/~greg/wordlist.visual.py
>> I've included the search utility I used below.
Yeah, there are lots of tools on the Internet. Posting links to them is
not helping. Sending pull requests with particular changesets with
explanation is.
some fairly old wordlist solver code of mine:
https://people.xiph.org/~greg/wordlist.visual.py
it has a 52x52 letter visual similarity matrix in it (along with a citation)
On Fri, Oct 18, 2013 at 4:52 PM, jan wrote:
>
> The words 'public', 'private' and 'secret' could be confusing when
> encodi
The words 'public', 'private' and 'secret' could be confusing when
encoding public and private keys. eg. a private key that begins with
the word 'public'.
I think avoiding words that could look similar when written down would
be a good idea aswell. I searched for words that only differ by the
let
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