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1	Dynamic Dead Variable Analysis Lewis, Micah S. 18 August 2005 (has links) (PDF) Dynamic dead variable analysis (DDVA) extends traditional static dead variable analysis (SDVA) in the context of model checking through the use of run-time information. The analysis is run multiple times during the course of model checking to create a more precise set of dead variables. The DDVA is evaluated based on the amount of memory used to complete model checking relative to SDVA while considering the extra overhead required to implement DDVA. On several models with a complex control flow graph, DDVA reduces the amount of memory needed by 38-88MB compared to SDVA with a cost of 36 bytes of memory verhead. On several models with loops, DDVA achieved no additional reduction compared to SDVA while requiring no more memory than SDVA. static analysis model checking abstraction live variable analysis dead variable analysis verification Computer Sciences
2	On-the-Fly Dynamic Dead Variable Analysis Self, Joel P. 22 March 2007 (has links) (PDF) State explosion in model checking continues to be the primary obstacle to widespread use of software model checking. The large input ranges of variables used in software is the main cause of state explosion. As software grows in size and complexity the problem only becomes worse. As such, model checking research into data abstraction as a way of mitigating state explosion has become more and more important. Data abstractions aim to reduce the effect of large input ranges. This work focuses on a static program analysis technique called dead variable analysis. The goal of dead variable analysis is to discover variable assignments that are not used. When applied to model checking, this allows us to ignore the entire input range of dead variables and thus reduce the size of the explored state space. Prior research into dead variable analysis for model checking does not make full use of dynamic run-time information that is present during model checking. We present an algorithm for intraprocedural dead variable analysis that uses dynamic run-time information to find more dead variables on-the-fly and further reduce the size of the explored state space. We introduce a definition for the maximal state space reduction possible through an on-the-fly dead variable analysis and then show that our algorithm produces a maximal reduction in the absence of non-determinism. model checking computer science static static analysis dynamic analysis analysis program program analysis Estes GDB dead variable analysis dead variable live variable live variable analysis CFG abstraction data abstraction on-the-fly static program analysis control flow graph software model checking state space depth first search state explosion state explosion problem Computer Sciences

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Dynamic Dead Variable Analysis

On-the-Fly Dynamic Dead Variable Analysis