A Local Search Approach for Batch Repair With Configuration Neighbor and Sub-Degree in Circuit System

Meng Liu,Naiyu Tian,Dantong Ouyang,Hua Li

doi:10.1109/access.2020.2975070

Abstract

The goal of automated troubleshooting is to diagnose and fix a system by repairing its abnormal behaviors, and this process has wide application. Heuristic search is an efficient way to solve troubleshooting problems, such as the batch repair problem (BRP), and heuristic search aims to minimize the costs of repairing a circuit system. The local search method is an efficient search approach and has very good performance in many areas. The key to this method is the modeling of “neighbor” and the search strategy. This paper proposes a local search approach for batch repair with configuration neighbors and sub-degree (CNASD). First, we define configuration neighbors in the BRP. Second, we propose three strategies to guide the search process, namely, best diagnosis with the highest probability component (BDHC), configuration neighbor with aspiration (CNA) and minimal sub-degree. Experimentally, compared with state-of-the-art batch repair algorithms that use heuristic search, our algorithm performs better in terms of the average / maximum repair cost and average / maximum runtime (decreased by up to one order of magnitude) on ISCAS’85 and ITC’99 systems, which are the standard combinational circuit systems.

Highlights

Diagnosing a system refers to identifying the root causes of encountered errors
We propose the strategies of: best diagnosis with the highest probability component (BDHC), configuration neighbor with aspiration (CNA) and minimal sub-degree
A LOCAL SEARCH APPROACH FOR BATCH REPAIR we propose a novel local search approach for batch repair problem (BRP), namely, configuration neighbors and sub-degree (CNASD)

Summary

INTRODUCTION

Diagnosing a system refers to identifying the root causes of encountered errors. Because the precondition of the BRP is that the system must have been fixed, only considering diagnoses or components is not reasonable for obtaining minimal costs. Considering components ignores the reasonable premise that diagnosis can explain the current abnormal behavior of the system This approach blindly pursues low costs but ignores the precondition of the BRP (the system is fixed). Shinitzky et al [1] propose that the BRP can be modeled as a combinatorial optimization problem of searching for the optimal batch repair action. These authors do not find the universal winner with A*, HC or depth-limited breadth-first search. The sub-degree of a diagnosis shows the ‘‘distance’’ from the set of components γ to this diagnosis, to some extent

THREE STRATEGIES FOR BATCH REPAIR

EXPERIMENTAL EVALUATIONS

CONCLUSION