These tests are the most common way to empirically identify carriers of the virus, and urgently need to be conducted on a large scale. Today, patients are granted a test if deemed necessary by the government and are carried out individually, i.e., every sample is tested separately. The problem is that the number of samples gathered today supersedes the amount of tests that can be conducted daily; Moreover, the worldwide shortage in equipment and resources prevents a much-needed increase in the number of daily tests. As a result, the testing system today is at full capacity, and falls short of the need. Two recent developments are relevant to the solution that we describe here: 1. Data regarding tests and the patients behind them has been gathered (over 120,000 tests in Israel as of Mid.

PCS is a CSP solver that can produce a machine-checkable deductive proof in case it decides that the input problem is unsatisfiable. The roots of the proof may be nonclausal constraints, whereas the rest of the proof is based on resolution of signed clauses, ending with the empty clause. PCS uses parameterized, constraint-specific inference rules in order to bridge between the nonclausal and the clausal parts of the proof. The consequent of each such rule is a signed clause that is 1) logically implied by the nonclausal premise, and 2) strong enough to be the premise of the consecutive proof steps. The resolution process itself is integrated in the learning mechanism, and can be seen as a generalization to CSP of a similar solution that is adopted by competitive SAT solvers.