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authorJeff Handley <jeffhandley@users.noreply.github.com>2025-10-03 12:36:43 -0400
committerHans Kristian Rosbach <hk-github@circlestorm.org>2025-10-07 12:47:44 +0200
commit3aaa0796aa84df7c96f8c4b73ebea34c00fffb72 (patch)
treefb290cf438cebff37ccbf97b282d8623a8c91644
parente68829579b1e01972c20e7d8b3b8203711c7af75 (diff)
downloadProject-Tick-3aaa0796aa84df7c96f8c4b73ebea34c00fffb72.tar.gz
Project-Tick-3aaa0796aa84df7c96f8c4b73ebea34c00fffb72.zip
Update terms in txtvsbin.txt
-rw-r--r--doc/txtvsbin.txt12
1 files changed, 6 insertions, 6 deletions
diff --git a/doc/txtvsbin.txt b/doc/txtvsbin.txt
index 3d0f0634f7..2a901eaa68 100644
--- a/doc/txtvsbin.txt
+++ b/doc/txtvsbin.txt
@@ -38,15 +38,15 @@ The Algorithm
The algorithm works by dividing the set of bytecodes [0..255] into three
categories:
-- The white list of textual bytecodes:
+- The allow list of textual bytecodes:
9 (TAB), 10 (LF), 13 (CR), 32 (SPACE) to 255.
- The gray list of tolerated bytecodes:
7 (BEL), 8 (BS), 11 (VT), 12 (FF), 26 (SUB), 27 (ESC).
-- The black list of undesired, non-textual bytecodes:
+- The block list of undesired, non-textual bytecodes:
0 (NUL) to 6, 14 to 31.
-If a file contains at least one byte that belongs to the white list and
-no byte that belongs to the black list, then the file is categorized as
+If a file contains at least one byte that belongs to the allow list and
+no byte that belongs to the block list, then the file is categorized as
plain text; otherwise, it is categorized as binary. (The boundary case,
when the file is empty, automatically falls into the latter category.)
@@ -84,9 +84,9 @@ consistent results, regardless what alphabet encoding is being used.
results on a text encoded, say, using ISO-8859-16 versus UTF-8.)
There is an extra category of plain text files that are "polluted" with
-one or more black-listed codes, either by mistake or by peculiar design
+one or more block-listed codes, either by mistake or by peculiar design
considerations. In such cases, a scheme that tolerates a small fraction
-of black-listed codes would provide an increased recall (i.e. more true
+of block-listed codes would provide an increased recall (i.e. more true
positives). This, however, incurs a reduced precision overall, since
false positives are more likely to appear in binary files that contain
large chunks of textual data. Furthermore, "polluted" plain text should