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Improvement of Live Variable Analysis Using Points-to Analysis
Raiskup, Pavel ; Rogalewicz, Adam (referee) ; Dudka, Kamil (advisor)
Languages such as C use pointers very heavily. Implementation of operations on dynamically linked structures is, however, quite difficult. This can cause the programmer to make more mistakes than usual. One method for dealing with this situation is to use the static analysis tools. This thesis elaborates on the extension to the Code Listener architecture which is an interface for building static analysis tools. Code Listener is able to construct a call-graph or a control flow graph for a given source code and send it to the analyzing tool. One ability of the architecture is that it can conduct the live variable analysis internally. It detects places in the control flow graph where some subset of variables may be killed. The problem was that every variable for which a pointer address was assigned could not been killed, before. This decision had been made because there was no assurance that the variable could never been used through the pointer. So the goal of this work was to design and incorporate a points-to analysis which is able to exclude some references from the set of considered pointers to improve the live variable analysis.
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Scalable link-time optimization
Láska, Ladislav ; Hubička, Jan (advisor) ; Mareš, Martin (referee)
Both major open-source compilers, GCC and LLVM, have a mature link-time optimization framework usable on most current programs. They are however not free from many performance issues, which prevent them to perform certain analyses and optimizations. We analyze bottlenecks and identify multiple places for improvement, focusing on improving interprocedural points-to analysis. For this purpose, we design a new data structure derived from Bloom filters and use it to significantly improve performance and memory consumption of link-time optimization. Powered by TCPDF (www.tcpdf.org)
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Scalable link-time optimization
Láska, Ladislav ; Hubička, Jan (advisor) ; Mareš, Martin (referee)
Both major open-source compilers, GCC and LLVM, have a mature link-time optimization framework usable on most current programs. They are however not free from many performance issues, which prevent them to perform certain analyses and optimizations. We analyze bottlenecks and identify multiple places for improvement, focusing on improving interprocedural points-to analysis. For this purpose, we design a new data structure derived from Bloom filters and use it to significantly improve performance and memory consumption of link-time optimization. Powered by TCPDF (www.tcpdf.org)
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Improvement of Live Variable Analysis Using Points-to Analysis
Raiskup, Pavel ; Rogalewicz, Adam (referee) ; Dudka, Kamil (advisor)
Languages such as C use pointers very heavily. Implementation of operations on dynamically linked structures is, however, quite difficult. This can cause the programmer to make more mistakes than usual. One method for dealing with this situation is to use the static analysis tools. This thesis elaborates on the extension to the Code Listener architecture which is an interface for building static analysis tools. Code Listener is able to construct a call-graph or a control flow graph for a given source code and send it to the analyzing tool. One ability of the architecture is that it can conduct the live variable analysis internally. It detects places in the control flow graph where some subset of variables may be killed. The problem was that every variable for which a pointer address was assigned could not been killed, before. This decision had been made because there was no assurance that the variable could never been used through the pointer. So the goal of this work was to design and incorporate a points-to analysis which is able to exclude some references from the set of considered pointers to improve the live variable analysis.
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