Compositional Static Callgraph Reachability Analysis for WhatsApp Android App Health

We report on an industrial use case of static callgraph reachability analysis to improve WhatsApp Android app health. We collaborated with engineers dedicated to app health to annotate/specify the source code. We leveraged the Infer static analyzer to prevent regressions during code changes and to periodically find pre-existing issues on the latest revision. Within three months, the analysis prevented almost a hundred regressions from being introduced and resulted in fixes for a handful of pre-existing issues, including examples with end-user measurable impact.

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Publication Details

Published
2025-06-13
DOI
https://doi.org/10.1145/3735544.3735583
Primary Topic
Advanced Malware Detection Techniques
Type
article
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article

Compositional Static Callgraph Reachability Analysis for WhatsApp Android App Health

R.C.T. Lee, Ákos Hajdu, Nilesh Agrawal, Jérémy Dubreil et al.
Advanced Malware Detection Techniques
article

Compositional Static Callgraph Reachability Analysis for WhatsApp Android App Health

R.C.T. Lee, Ákos Hajdu, Nilesh Agrawal, Jérémy Dubreil, Gavin Weng
article en

Abstract

We report on an industrial use case of static callgraph reachability analysis to improve WhatsApp Android app health. We collaborated with engineers dedicated to app health to annotate/specify the source code. We leveraged the Infer static analyzer to prevent regressions during code changes and to periodically find pre-existing issues on the latest revision. Within three months, the analysis prevented almost a hundred regressions from being introduced and resulted in fixes for a handful of pre-existing issues, including examples with end-user measurable impact.

Alpha Omega Alpha Medical Honor Society (US), Menlo School (US), Meta (United Kingdom) (GB)
Openalex Percentile: Top 85%
Advanced Malware Detection Techniques
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