Split up test vectors into per-algo files and app into botan-test for

the tests and botan for everything else.

1 files changed, 94 insertions, 0 deletions

diff --git a/src/tests/data/hash/adler32.vec b/src/tests/data/hash/adler32.vec
new file mode 100644
index 000000000..d4ce3ccad
--- /dev/null
+++ b/src/tests/data/hash/adler32.vec
@@ -0,0 +1,94 @@
+[Adler32]
+In = 
+Out = 00000001
+
+In = 35
+Out = 00360036
+
+In = 5EC8
+Out = 01860127
+
+In = 679496
+Out = 02F60192
+
+In = B32AB23D
+Out = 04EF01CD
+
+In = 8CA9455795
+Out = 07770267
+
+In = D37EAD077220
+Out = 0B3B0298
+
+In = E2210CD33A1068
+Out = 0BB90295
+
+In = 5BB33F53C9D00795
+Out = 111503D6
+
+In = 537A0E6291C9DF5E4B
+Out = 130F0420
+
+In = 387900E329FB770A78FB
+Out = 167204AD
+
+In = 0CE184B96C789E7E0A6EEC
+Out = 207D058F
+
+In = 773870CD456F8797BC61EB73
+Out = 2547063A
+
+In = E5FB7B41CDAA1C4FB21D195467
+Out = 33B00622
+
+In = 60D382B3CB4341FB141360855BD8
+Out = 367006F2
+
+In = E48EBC5C8730639FFB47C12D238856
+Out = 41FA0775
+
+In = 4A25B557982801088B8B4E45AFD7DC0B
+Out = 30AC065B
+
+In = A864D51DA8BE2CED6E2498FFB1E56C4EAF
+Out = 54D809A6
+
+In = 580E32B4D34F21CC2978076EB3A6D0FCCFC4
+Out = 47CB092A
+
+In = 5B32E288EE8AA4E866678D65DDF844F5B3CAB1
+Out = 70720BF7
+
+In = B014940A8D58C8550E9E1BAB1E96540ED0AFA6DB
+Out = 54DA08ED
+
+In = 2A085FB051FD798552D6E1F60DE222AC5F595AAF73
+Out = 6F340A7E
+
+In = C1A30E3E8EEB24B5350A75D1D38255FE834CFE6C638D
+Out = 7D950B59
+
+In = A8BE4CC3005FD904F6E58D5DD60AF8AAC3928F2FBB2B45
+Out = 97790C37
+
+In = C6D1E2B2B546867A22ADD3A422F2111ECE6ED49CE85F0ABB
+Out = B12A0D68
+
+In = A28FC69AE1044743338EAEB08DD876267B9DE4780182568D82
+Out = A7F70C7D
+
+In = 5C575A7D25204220C994D3E130B48E14650477D64FE646890033
+Out = 8F750AB6
+
+In = C3AEDA730EBFBFE54DCE695AD46CA06C4D2D197680C4C42645D60E
+Out = D2A40DBA
+
+In = D28292D1255B080A66BE9CD5C213844C2564DB843A95416E5A8DC215
+Out = BE1F0CA8
+
+In = A8E22320693BCB2368267AC0F4D448825F36A080CA2C6DFD67DA66D124
+Out = CFAD0E6B
+
+In = 41BA45D14C618EBE7C0AE0150F1D18EA457E54164DD6E3FE8227EC874D65A085A5BC9B06C5399B4C5D47A5D639B9F2E1C1211C46DDD56728D2269C7FBC1E9EA82B1DB5FE2974AF83D33F5E7039E3C44DFCD9359492DE314514068E483EAF1637ABD215117D53755229962A37B91176170EFD1AA0DC751B53059D32DD4FAB3C0AAF52375854B9FFD2BBB303CCF617874B60CA368AF6AA6C149BABF22885F443F0D2870EE9A8E5E429BC00B7AA0942025838D8ED1489114D4BBA666678BCB6C75B66902559186BA330ED378EA5905DC8B41C474ACAF54BF191A0B20FCAE96DABAD046241C58324A6C1CCA5F50D1FC4C35FD565B53693D0FBD874D5959C8327CCAFF79760FCEDF5C0CDE1721054B443FDE8D771B5621A9AFB0F935409F5C63638FAAFB99BD5A3519408A30452A5BFF41AA62DD077AEF418942F076F730D10277ECDA8C1A71A4E16FDA1F61FE45660AA554E530D31562818EC961EB116AD5161687A23B8DAD5E0F016BD7AE0AB63E710B20AFAE8928C616292D5DF207042617BE830401C30A49FF8308D9060AB7E124417B139FAA303AD73C7B102DF81D763CD239C5EEF3A5FB60C374216263A48B68C9CC02121CF90AE72F906BE21C87315FD88A24237215A725992F4B18855D2217A4D033F4597440567736AE9BCCA4A7187479399B03E75CA828736614209FE0D3F71A9C90CA6310BBBF387F983BE221729763B290C986B8B43BEBE7F3AF9A895BA29663C4B204935C0F7182549E96D96252DA545ED4C54EEE6C1A174AC74CE9C22DF29159F8EB12771CB8396E6F07D0FC43EAF930C0AF228D53527235637E5408A234B785A9E2CC8A30C7E27E1FC55FE6FAB0B3465616F5EFC59B1B52F2FE8A4BCEA7EE470AC47E148165CF025B99808494865D5FFE9263150821C10BD916423101EE3B8640CFAA74A4EEBC86349DB8C8726ECFD1F4B603E6755FFA0586304196A11EFDB7F892B5C7E0EF1A41E99ED60ABE3402D5017240869A26F0447017A313922932FFA53E56BE913A0EA465A95E0370C0B5A8418733BCC2FD7D294F23C474E3C3D331E2B7F42051E7BAF2026295B56837F497865D4D60B02EB2E76058756D2E306519046B6A3B7152236D73B2C698A8F0155C4E8F1D634D5737C3D7005B5557E2FDF1EC77B2B16239B5C21D105AF86B8BE5BFBF52E00D63349568CBE25E6735BABF057E3B01CAB9520D5D03D2C4F7CEDBB7C6FE4943B95B27CECF671AEA54B8740074445D4F14C17C9B9A12E581B559CB17149A131613FD35ADF9ADE4DE981DD01E45262002B480B2FD524E39B307BD5A6D1CF9178B59B98F2B43EA4CDED27513AAC550E1754DD6452A9434BB59B1186F9DA61E174D6610C2B286AECDBAE9E6CBD4D2BFCABE0B83627A13F87288ABE927A891E372163A87A437CD1F4AFC91A940FF55F5DC6CFA5AADF689946192050BE7C
+Out = 9DA7EB84
+