Title
Conquering the extensional scalability problem for value-flow analysis frameworks
Abstract
ABSTRACTModern static analyzers often need to simultaneously check a few dozen or even hundreds of value-flow properties, causing serious scalability issues when high precision is required. A major factor to this deficiency, as we observe, is that the core static analysis engine is oblivious of the mutual synergy among the properties being checked, thus inevitably losing many optimization opportunities. Our work is to leverage the inter-property awareness and to capture redundancies and inconsistencies when many properties are considered at the same time. We have evaluated our approach by checking twenty value-flow properties in standard benchmark programs and ten real-world software systems. The results demonstrate that our approach is more than 8× faster than existing ones but consumes only 1/7 of the memory. Such substantial improvement in analysis efficiency is not achieved by sacrificing the effectiveness: at the time of writing, thirty-nine bugs found by our approach have been fixed by developers and four of them have been assigned CVE IDs due to their security impact.
Year
DOI
Venue
2020
10.1145/3377811.3380346
International Conference on Software Engineering
Keywords
DocType
ISSN
Static bug finding, demand-driven analysis, compositional program analysis, value-flow analysis
Conference
0270-5257
ISBN
Citations 
PageRank 
978-1-7281-6519-6
1
0.35
References 
Authors
29
4
Name
Order
Citations
PageRank
Shi Qingkai110.35
Rongxin Wu252819.69
Gang Fan3151.92
Charles Zhang451228.97