Proceedings of ISP RAS


C# static analysis framework

V. Koshelev (ISP RAS, Moscow, Russia)
V. Ignatyev(ISP RAS, Moscow, Russia)
A. Borzilov (ISP RAS, Moscow, Russia)

Abstract

The paper describes static analysis techniques that are used for defect detection in C# programs. The goal of proposed analysis approaches is to catch more defects within an acceptable amount of time. Although the paper contains a description of full analysis cycle, it mainly focuses on special aspects that distinguish C# analysis approaches from well-known Java and C++ techniques. The paper illustrates methods that allow taking into account C# specialties of all analysis stages: call graph and control flow graph construction, data flow analysis, context- and path-sensitive interprocedural analysis. We propose an adaptation of symbolic execution methods inspired by Bounded Model Checking and Saturn Software Analysis Project. The paper also explains the organization of memory model, which is suitable for both a precise intraprocedural analysis and a creation of compact function-bound conditions used for interprocedural analysis. Special attention is paid to optimization of condition size and simplicity during a path sensitive-analysis. The conditions produced by a path-sensitive analysis are supposed to be solved by modern SMT solvers like Microsoft Z3 Prover. Different approaches to external functions modeling are covered. All proposed approaches are implemented in the SharpChecker static analysis tool and, as evaluated on several open source C# projects of varying size (1K - 1.35M lines of code), display good results and scalability.

Keywords

static analysis; null pointer dereference; path-sensitive analysis; context-sensitive analysis; function summary; bug detection; Roslyn; C#

Edition

Proceedings of the Institute for System Programming, vol. 28, issue 1, 2016, pp. 21-40.

ISSN 2220-6426 (Online), ISSN 2079-8156 (Print).

DOI: 10.15514/ISPRAS-2016-28(1)-2

Full text of the paper in pdf (in Russian) Back to the contents of the volume