Since it seems to be some interest on the subject and to avoid duplicated work, here is a rewrite of sparse's construction of the SSA form. It's not using one of the classical algorithm but is using something newer, simpler and often faster. It's main advantage beyond the simplicity is that you don't need to first build the whole CFG & linearized code to to directly throw it away (or heavily transform it) as it builds the SSA form directly during the linearization. It's not finished code but it's working well (and is effectively a bit faster and use less memory). What's interesting for sparse now is that: - the phi-noes are correctly placed - uninitialized variables can be handled much more easily. I don't feel it's needed to patchbomb the ML for the moment so I'll only give the URL to the repo: git://github.com/lucvoo/sparse.git sssa -- To unsubscribe from this list: send the line "unsubscribe linux-sparse" in the body of a message to majordomo@xxxxxxxxxxxxxxx More majordomo info at http://vger.kernel.org/majordomo-info.html
