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Tests and status

Test system

The code now (as of March 2016) comes with a trivial regression test, which is to take the text of a book of the Aeneid and run it through WORDS, comparing it with a saved copy of the output from an earlier date. This catches quite a few bugs, and is automatically incorporated in the Travis continuous integration testing of WORDS.

In the future, there will be a suite of unit tests for WORDS, operating via AUnit. If you know Latin and a little programming (you don’t really need to know Ada), and are willing to help out with this, please get in contact.

The commentary below is from Whitaker’s original collateral distributed with the WORDS source code; it is largely still valid.


The program has been run against common classical texts. Initially this was mostly a check of the process and reliability of the program. It is now possible to run real texts and get valid statistics. Relatively few texts have been run multiple times in order to understand exactly where failure occurred and to regression test the solutions. Such testing has taken place on texts totaling well over a million words. The best results come from those which have been run the most times. Caesar and the Vulgate are essentially without unknowns (excluding proper names), Suetonius and Virgil are at the 0.1% level, Varro and Pliny have somewhat more than 1% unknowns due to their specialized vocabulary. While this is a mechanical test and does not assure that the form and meaning reported by the program is always correct, the actual number of misses found by limited detailed examination is vanishingly small.

A far larger test (with feedback) has been made by John White in the development of his Blitz Latin. While not using WORDS, he has a program from much the same basis, incorporating approximately the WORDS dictionary. He has run a much larger set of texts, including both classical and medieval, to the extent of 20 million Latin words, and provided significant unknowns to be included in WORDS.

The hardest test is against another dictionary. While getting a 97+% hit rate on long classical texts, a run against a large dictionary might fall to 85-90%, the missing words being in those letters which the update has not reached. This is to be expected, since we both have the 10000 most common words and have made somewhat different additions beyond that. So large electronic wordlists are a check on the program, and have been reserved for that purpose, not simply incorporated as such.

We have gone so far that this is no longer significant and wordlists can be integrated. The only real impact has been the inclusion of modern Latin words which come from such lists, and not from scans of texts.

English-to-Latin Tests

So far there have been no formal validation of the English-to-Latin capability. There have been numerous individual checks and anecdotal testing, as well as some mechanical performance tests, but nothing fundamental.

The first test proposed is to take a small English-to-Latin dictionary, say from the back of an introductory textbook, and check that the Latin suggested for each entry is found in the top six returned by WORDS. It is expected that there will be a high correspondence (to be shown). Taking a much larger example may give a different result. It may be that the Latin words chosen by WORDS are not the same as the paper dictionary.

Current Status and Future Plans

The present phase of refinement has incorporated the Oxford Latin Dictionary and Lewis and Short entries into D (about a fourth). Periodically, when I need a change of task, I run a major author to check the effectiveness of the code. I may then include some words which turn up frequently as unknowns, but this is done as the spirit moves me. Smaller sections of later authors may also be processed, giving some growth in medieval Latin entries. Recently I have worked the Vulgate of St. Jerome.

John White in support of his Blitz Latin program has run a very large body of Latin text, including much medieval legal documents. He provides input to the dictionary as he finds significant unknowns.