HSelect: Effective Selection of Heterogeneous Software for Common Mode Failure Mitigation

With the growing risk of Common Mode Failure (CMF), N -versioning has become a key strategy for improving fault tolerance and security in software systems. While studies often assume the availability of off-the-shelf heterogeneous variants, practical N -versioning systems are typically built using different versions of the same software. Selecting heterogeneous variants is a key challenge in building robust N -versioning systems. This work introduces HSelect, a novel approach for selecting N versioning variants by measuring software heterogeneity. HSelect detects code changes at file and block levels, generating a heterogeneity matrix to select maximally diverse variants. Evaluation on eight projects shows HSelect more effectively measures heterogeneity and mitigates CMF vulnerabilities than traditional methods.

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Publication Details

Published
2025-03-21
DOI
https://doi.org/10.1109/iscait64916.2025.11010357
Citations
1
Primary Topic
Software Reliability and Analysis Research
Type
article
Field-Weighted Citation Impact
2.31
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HSelect: Effective Selection of Heterogeneous Software for Common Mode Failure Mitigation

Xianglong Kong, Yi Cao, Xinyuan Miao, Jiayu Du et al.
1 citations
Software Reliability and Analysis Research
2.31
article

HSelect: Effective Selection of Heterogeneous Software for Common Mode Failure Mitigation

Xianglong Kong, Yi Cao, Xinyuan Miao, Jiayu Du, Wei Bo Huang, Zhiyuan Yu
article en
1 citations

Abstract

With the growing risk of Common Mode Failure (CMF), N -versioning has become a key strategy for improving fault tolerance and security in software systems. While studies often assume the availability of off-the-shelf heterogeneous variants, practical N -versioning systems are typically built using different versions of the same software. Selecting heterogeneous variants is a key challenge in building robust N -versioning systems. This work introduces HSelect, a novel approach for selecting N versioning variants by measuring software heterogeneity. HSelect detects code changes at file and block levels, generating a heterogeneity matrix to select maximally diverse variants. Evaluation on eight projects shows HSelect more effectively measures heterogeneity and mitigates CMF vulnerabilities than traditional methods.

Purple Mountain Laboratories (CN), Southeast University (CN)
Climate action
Openalex Percentile: Top 14%
Software Reliability and Analysis Research
2.31
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