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| author | Jeff Handley <jeffhandley@users.noreply.github.com> | 2025-10-03 12:36:43 -0400 |
|---|---|---|
| committer | Hans Kristian Rosbach <hk-github@circlestorm.org> | 2025-10-07 12:47:44 +0200 |
| commit | 3aaa0796aa84df7c96f8c4b73ebea34c00fffb72 (patch) | |
| tree | fb290cf438cebff37ccbf97b282d8623a8c91644 /doc | |
| parent | e68829579b1e01972c20e7d8b3b8203711c7af75 (diff) | |
| download | Project-Tick-3aaa0796aa84df7c96f8c4b73ebea34c00fffb72.tar.gz Project-Tick-3aaa0796aa84df7c96f8c4b73ebea34c00fffb72.zip | |
Update terms in txtvsbin.txt
Diffstat (limited to 'doc')
| -rw-r--r-- | doc/txtvsbin.txt | 12 |
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 |
