Automated workarounds from Java program specifications based on SAT solving

Abstract

The failures that bugs in software lead to can sometimes be bypassed by the so called workarounds: when a (faulty) routine fails, alternative routines that the system offers can be used in place of the failing one, to circumvent the failure. Previous works have exploited this workarounds notion to automatically recover from runtime failures in some application domains. However, existing approaches that compute workarounds automatically either require the user to manually build an abstract model of the software under consideration, or to provide equivalent sequences of operations from which workarounds are computed, diminishing the automation of workaround-based system recovery. In this paper, we present two techniques that automatically compute workarounds from Java code equipped with formal specifications, avoiding abstract software models and user provided equivalences. These techniques employ SAT solving to compute workarounds on concrete program state characterizations. The first employs SAT solving to compute traditional workarounds, while the second directly exploits SAT solving to circumvent a failing method, building a state that mimics the (correct) behaviour of this failing routine. Our experiments, based on case studies involving implementations of collections and a library for date arithmetic, enable us to show that the techniques can effectively compute workarounds from complex contracts in an important number of cases, in time that makes them feasible to be used for run time repairs.

Optimum checkpoints for programs with loops

“…Despite their benefits, NVP and RB approaches are characterized by high development costs [33], which restricts their adoption to safety or reliability critical applications [34]. Despite attempts in addressing some drawbacks [28,29,[34][35][36], their associated costs are still high.…”