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Rozšíření nástroje ANaConDa pro dynamickou analýzu paralelních programů
Horňák, Michal ; Češka, Milan (oponent) ; Vojnar, Tomáš (vedoucí práce)
Cieľom tejto práce bolo implementácia algoritmu FastTrack pre dynamickú analízu viacvláknových programov v jazyku C/C++. Ide o algoritmus detekujúci chyby typu data race. Je založený na relácii happens-before zakódovanej do tzv. vektor-klokov. Tie umožňujú extrapolovať beh programu a odhaľovať tak potenciálne chyby, ktoré sa v aktuálnom behu nevyskytli, ale v iných exekúciách by sa mohli vyskytnúť. Algoritmus je implementovaný v prostredí ANaConDA. Jedná sa o nástroj slúžiaci pre jednoduchšie implementovanie dynamických analizátorov monitorujúcich paralelné program na binárnej úrovni. ANaConDA poskytuje analyzátorom potrebné informácie o behu programu, ktoré detektory následne využívajú k odhaľovaniu chýb.
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Rozšíření nástroje ANaConDa pro dynamickou analýzu paralelních programů
Horňák, Michal ; Křena, Bohuslav (oponent) ; Vojnar, Tomáš (vedoucí práce)
Cieľom tejto práce bolo implementácia algoritmu FastTrack pre dynamickú analízu viac-vláknových programov v jazyku C/C++. Ide o algoritmus detekujúci chyby typu data race. Je založený na relácii happens-before zakódovanej do tzv. vektor-klokov. Tie umožňujú extrapolovať beh programu a odhaľovať tak potenciálne chyby, ktoré sa v aktuálnom behu nevyskytli, ale v iných exekúciách by sa mohli vyskytnúť. Algoritmus je implementovaný v prostredí ANaConDA. Jedná sa o nástroj slúžiaci pre jednoduchšie implementovanie dynamických analizátorov monitorujúcich paralelné programy na binárnej úrovni. ANaConDA poskytuje analyzátorom potrebné informácie o behu programu, ktoré detektory následne využívaju k odhaľovaniu chýb.
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Support of Run-time Monitoring of Processes in ANaConDA Framework
Mužikovská, Monika ; Rogalewicz, Adam (oponent) ; Smrčka, Aleš (vedoucí práce)
This work extends ANaConDA framework for dynamic analysis of multi-threaded programs with support for multi-process monitoring. This thesis summarizes ANaConDA's approach to analysis and differences between threads and processes. The most important ones involve inter-process communication, separate logical address spaces, and synchronisation with general semaphores. The implemented extension provides API for inter-process communication via shared memory, monitors operations with shared memory in order to translate virtual addresses to their unique representation among processes, and monitors synchronisation operations with semaphores and provides information about them to analysers. The extension significantly simplifies the development of multi-process analysers. This is shown on implementation of two analysers for data race detection, AtomRace and FastTrack, which were, until now, available for multi-threaded programs only. The implementation of FastTrack algorithm uses happens-before relation for general semaphores which is also defined in this thesis. Proposed and implemented solutions were verified on a set of automatic tests and the two analysers were used for experiments on a set of students' projects. Experiments showed that ANaConDA framework is now able to detect concurrency-related errors in multi-process programs and, as such, provide support with implementation of large category of parallel programs.
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Static Analysis in the Frama-C Environment Focused on Deadlock Detection
Dacík, Tomáš ; Holík, Lukáš (oponent) ; Vojnar, Tomáš (vedoucí práce)
This thesis presents a design of a new static analyser focused on deadlock detection, implemented as a plugin of the Frama-C platform. Together with the core algorithm of deadlock detection, we also present a light-weight method that allows one to analyse (not only for the purposes of deadlock detection) multi-threaded programs using sequential analysers of Frama-C. Results of experiments show that our tool is able to handle real-world C code with high precision. Moreover, we demonstrate its extensibility by so-far experimental implementation of data race detection.
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Statická analýza v nástroji Meta Infer zaměřená na detekci souběhu nad daty
Svobodová, Lucie ; Fiedor, Jan (oponent) ; Vojnar, Tomáš (vedoucí práce)
Modern software systems often use concurrent programs to improve performance and increase efficiency. However, ensuring the reliability and safety of such systems can be challenging due to the increased potential for bugs, including data races, to arise. In this thesis, we introduce a new static data race detector, DarC, designed for programs written in C using the Pthreads library. The proposed detector is implemented as an analyser plugin in Meta Infer, a static analysis framework with an emphasis on compositional, incremental, and consequently highly-scalable analysis. Our approach involves recording a set of accesses that occur in the analysed program along with information about the set of locks held during these accesses. The tool then identifies pairs of accesses that may lead to data races and reports them to the user. Our tool was successfully evaluated on a set of benchmarking programs as well as on real-life projects, showing its potential for effectively detecting data races in C programs.
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Support of Run-time Monitoring of Processes in ANaConDA Framework
Mužikovská, Monika ; Rogalewicz, Adam (oponent) ; Smrčka, Aleš (vedoucí práce)
This work extends ANaConDA framework for dynamic analysis of multi-threaded programs with support for multi-process monitoring. This thesis summarizes ANaConDA's approach to analysis and differences between threads and processes. The most important ones involve inter-process communication, separate logical address spaces, and synchronisation with general semaphores. The implemented extension provides API for inter-process communication via shared memory, monitors operations with shared memory in order to translate virtual addresses to their unique representation among processes, and monitors synchronisation operations with semaphores and provides information about them to analysers. The extension significantly simplifies the development of multi-process analysers. This is shown on implementation of two analysers for data race detection, AtomRace and FastTrack, which were, until now, available for multi-threaded programs only. The implementation of FastTrack algorithm uses happens-before relation for general semaphores which is also defined in this thesis. Proposed and implemented solutions were verified on a set of automatic tests and the two analysers were used for experiments on a set of students' projects. Experiments showed that ANaConDA framework is now able to detect concurrency-related errors in multi-process programs and, as such, provide support with implementation of large category of parallel programs.
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Static Analysis in the Frama-C Environment Focused on Deadlock Detection
Dacík, Tomáš ; Holík, Lukáš (oponent) ; Vojnar, Tomáš (vedoucí práce)
This thesis presents a design of a new static analyser focused on deadlock detection, implemented as a plugin of the Frama-C platform. Together with the core algorithm of deadlock detection, we also present a light-weight method that allows one to analyse (not only for the purposes of deadlock detection) multi-threaded programs using sequential analysers of Frama-C. Results of experiments show that our tool is able to handle real-world C code with high precision. Moreover, we demonstrate its extensibility by so-far experimental implementation of data race detection.
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Rozšíření nástroje ANaConDa pro dynamickou analýzu paralelních programů
Horňák, Michal ; Křena, Bohuslav (oponent) ; Vojnar, Tomáš (vedoucí práce)
Cieľom tejto práce bolo implementácia algoritmu FastTrack pre dynamickú analízu viac-vláknových programov v jazyku C/C++. Ide o algoritmus detekujúci chyby typu data race. Je založený na relácii happens-before zakódovanej do tzv. vektor-klokov. Tie umožňujú extrapolovať beh programu a odhaľovať tak potenciálne chyby, ktoré sa v aktuálnom behu nevyskytli, ale v iných exekúciách by sa mohli vyskytnúť. Algoritmus je implementovaný v prostredí ANaConDA. Jedná sa o nástroj slúžiaci pre jednoduchšie implementovanie dynamických analizátorov monitorujúcich paralelné programy na binárnej úrovni. ANaConDA poskytuje analyzátorom potrebné informácie o behu programu, ktoré detektory následne využívaju k odhaľovaniu chýb.
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Rozšíření nástroje ANaConDa pro dynamickou analýzu paralelních programů
Horňák, Michal ; Češka, Milan (oponent) ; Vojnar, Tomáš (vedoucí práce)
Cieľom tejto práce bolo implementácia algoritmu FastTrack pre dynamickú analízu viacvláknových programov v jazyku C/C++. Ide o algoritmus detekujúci chyby typu data race. Je založený na relácii happens-before zakódovanej do tzv. vektor-klokov. Tie umožňujú extrapolovať beh programu a odhaľovať tak potenciálne chyby, ktoré sa v aktuálnom behu nevyskytli, ale v iných exekúciách by sa mohli vyskytnúť. Algoritmus je implementovaný v prostredí ANaConDA. Jedná sa o nástroj slúžiaci pre jednoduchšie implementovanie dynamických analizátorov monitorujúcich paralelné program na binárnej úrovni. ANaConDA poskytuje analyzátorom potrebné informácie o behu programu, ktoré detektory následne využívajú k odhaľovaniu chýb.
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