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Towards a Cost-Effective Estimation of Uncaught Exceptions in SML Programsby: Kwangkeun Yi, Sukyoung Ryu
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Abstract. We present a static analysis that detects potential runtime exceptions that are raised and never handled inside Standard ML (SML) programs. This analysis will predict abrupt termination of SML programs, which is SML's only one "safety hole." Even though SML program's control flow and exception flow are in general mutually dependent, analyzing the two flows are safely decoupled. Program's control-flow is firstly estimated from a set of equations defined by simple case analysis of call...
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