Disjunctive image computation for sequential systems
View Patent ↗A symbolic disjunctive image computation method for software models which exploits a number of characteristics unique to software models. More particularly, and according to our inventive method, the entire software model is decomposed into a disjunctive set of submodules and a separate set of transition relations are constructed. An image/reachability analysis is performed wherein an original image computation is divided into a set of image computation steps that may be performed on individual submodules, independently from any others. Advantageously, our inventive method exploits variable locality during the decomposition of the original model into the submodules. By formulating this decomposition as a multi-way hypergraph partition problem, we advantageously produce a small set of submodules while simultaneously minimizing the number of live variable in each individual submodule. Our inventive method produces a set of disjunctive transition relations directly from the software model, without producing a conjunctive transition relation—as is necessary in the prior art. In addition, our inventive method exploits the exclusive use of live variables in addition to novel search strategies which provide still further benefit to our method.
1. A method for disjunctive image computation for software programs, the method comprising the steps of:
decomposing a model of a software program stored in a memory device by building disjunctive transition relations for the software program, wherein the step of building disjunctive transition relations is performed using a processor and includes:
dividing the basic blocks of the software program into subsets, so that a number of variables shared by subsets is minimized,
directly creating a transition relation disjunct for each subset of basic blocks, and
simplifying the transition relation disjunct by removing dead variables in each subset; and
conducting a symbolic image computation for each of the disjunctive transition relations.
2. The method of claim 1 wherein the basic blocks of the software program are divided into subsets through the use of hyper-graph partitioning.
3. The method of claim 1 further comprising the step of:
minimizing a number of live variables shared between subsets through the use of hyper-graph partitioning.
4. The method of claim 1 further comprising the step of:
minimizing the number of assigned variables shared between subsets through use of hyper-graph partitioning.
5. The method of claim 1 wherein said symbolic image computation comprises a reachability analysis and employs a BDD based representation.
6. The method of claim 1 wherein said symbolic image computation comprises a reachability analysis and employs multiple symbolic representations.