Abstract We present VeriAbsL, a reachability verifier that performs verification in three stages. First, it slices the input code using a combination of two slicers, then it verifies the slices using predicted strategies, and at last, it composes the result of verifying the individual slices. We introduce a novel shallow slicing technique that uses variable reference information of the program, and data and control dependencies of the entry function to generate slices. We also introduce a novel strategy prediction technique that uses machine learning to predict a strategy. It uses boolean features to describe a program to a neural network that predicts a strategy. We use the portfolio of VeriAbs, a reachabiltiy verifier with manually defined strategies. In sv-comp 2023, VeriAbsL verified 227 (Without witness validation.) more programs than VeriAbs, and 475 (Without witness validation.) programs that VeriAbs could not verify.

Abstract VeriAbs is a strategy selection-based reachability verifier for C programs. The selection of a suitable strategy is from a pre-defined set of strategies and by taking into account the syntax and semantics of the code to be verified. This year we present VeriAbs version 1.4.1 in which a novel preprocessor to strategy selection is introduced. The preprocessor checks for the feasibility of performing a lightweight slicing of the input code using function call graph and variable reference information. By this if the program is found to besliceable, sub-programs or slices are generated, and the known strategy selection algorithm of VeriAbs is applied to each slice. The verification results of each slice are then composed to derive that of the entire program. This compositional verification has improved the scalability of VeriAbs and presented in this paper.