Name
Abstract | ||
|---|---|---|
Ubiquitous embedded systems are often resource-constrained. Developing software for these systems should take into account resources such as memory space. In this paper, we develop and implement an analysis framework to infer statically stack usage bounds for assembly-level programs in abstract Java Byte code. Our stack bound inference process, extended from a theoretical framework proposed earlier by some of the authors, is composed of deductive inference rules in multiple passes. Based on these rules, a usable tool has been developed for processing programs to capture the stack memory needs of each procedure in terms of the symbolic values of its parameters. The final result contains path-sensitive information to achieve better precision. The tool invokes a Presburger solver to perform fixed point analysis for loops and recursive procedures. Our initial experiments have confirmed the viability and power of the approach. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/TASE.2010.24 | TASE |
Keywords | Field | DocType |
usable tool,fixpoint analysis,deductive inference rule,fixed point analysis,recursive procedure,abstract java bytecode,theoretical framework,memory inference,analysis framework,inference mechanisms,presburger solver,java bytecode,inference process,stack bound inference process,abstract java byte code,memory space,assembly-level program,stack boundary,program analysis,program diagnostics,program control structures,memory need,stack bound inference,program assemblers,java,point analysis,ubiquitous system,tool,fixed point,data structures,embedded system,inference rule,estimation,watermarking | Data structure,Programming language,Computer science,Inference,Call stack,Theoretical computer science,Stack trace,Java bytecode,Solver,Java,Stack-based memory allocation | Conference |
ISBN | Citations | PageRank |
978-1-4244-7847-7 | 2 | 0.36 |
References | Authors | |
12 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shengyi Wang | 1 | 2 | 0.36 |
| Zongyan Qiu | 2 | 436 | 41.04 |
| Shengchao Qin | 3 | 711 | 62.81 |
| Wei-Ngan Chin | 4 | 868 | 63.37 |