Boosting the Performance of Alias-Aware IFDS Analysis with CFL-based Environment(…)
summary
Reinterprets access-path generation as a Context-Free Language and casts field sensitivity as an IDE problem, implements the idea in IDEDroid and compares it to FlowDroid on 24 large Android apps, reporting a 222× average speedup and per-app speedups from 2.1× to 2,368.4× while using less memory, producing far fewer data-flow facts, and reducing false positives by up to 20% fewer false positives; the paper includes proofs of increased precision and an efficient CFL-reachability checker and provides reproducible artifacts.
AI-written summary · about
chapters (9)
- 0:00Introduction
- 1:53Field-sensitive IFDS analysis
- 4:44Redundant propagations in access paths
- 6:55CFL-based field sensitivity
- 9:04Modeling field access with CFL
- 10:27Efficiency in CFL analysis
- 12:20Precision over traditional IFDS
- 13:46Experimental results
- 15:33Q&A
related talks
16mIncIDFA: An Efficient and Generic Algorithm for Incremental Iterative Dataflow Analysis
21mContext Sensitivity without Contexts: A Cut-Shortcut Approach to Fast and Precise(…)
17mA Better Approximation for Interleaved Dyck Reachability
01h 01mData Flow Analysis in IntelliJ IDEA: How the IDE Perceives Your Code
20mRelaxing Alias Analysis: Exploring the Unexplored Space
19mAn Incremental Algorithm for Algebraic Program Analysis
19mContext-Free Language Reachability via Skewed Tabulation
17mSoK: Multi-Layer Indirect Call Analysis in the Real World