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Scaling Context-Sensitive Points-to Analysis: Novel ideas to tame the scalability challenges - Softcover
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Pointer analysis is one of the key static analyses during compilation and affects scalability and precision of several client transformations. Recent advances still lack an efficient and scalable context-sensitive inclusion-based pointer analysis. In this work, we propose four novel techniques to improve the scalability of context-sensitive points-to analysis for C/C++ programs. First, we develop an efficient way of storing the approximate points-to information using a multi-dimensional bloom filter (multibloom). Second, we devise a sound randomized algorithm that processes a group of constraints in a less precise but efficient manner and the remaining constraints in a more precise manner. Third, we transform the points-to analysis problem into finding a solution to a system of linear equations. Finally, we observe that the order in which points-to constraints are processed plays a vital role in the algorithm efficiency and propose a greedy heuristic based on the amount of points-to information computed by a constraint to prioritize the constraints. We illustrate that our algorithms help in scaling the state-of-the-art pointer analyses.
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Über die Autorin bzw. den Autor
Rupesh Nasre is an Assistant Professor at IIT Madras. He received Ph.D. from IISc, Bangalore. His research interests include Compilers and Parallelization. He is a recipient of the Young Faculty Recognition Award at IIT Madras, NVIDIA special prize in CodeForScience, a winner of the Yahoo! University Hack Day and holds five US patents.
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Scaling Context-Sensitive Points-to Analysis
Verlag:
LAP LAMBERT Academic Publishing Okt 2016, 2016
ISBN 10: 3659977187
ISBN 13: 9783659977183
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Pointer analysis is one of the key static analyses during compilation and affects scalability and precision of several client transformations. Recent advances still lack an efficient and scalable context-sensitive inclusion-based pointer analysis. In this work, we propose four novel techniques to improve the scalability of context-sensitive points-to analysis for C/C++ programs. First, we develop an efficient way of storing the approximate points-to information using a multi-dimensional bloom filter (multibloom). Second, we devise a sound randomized algorithm that processes a group of constraints in a less precise but efficient manner and the remaining constraints in a more precise manner. Third, we transform the points-to analysis problem into finding a solution to a system of linear equations. Finally, we observe that the order in which points-to constraints are processed plays a vital role in the algorithm efficiency and propose a greedy heuristic based on the amount of points-to information computed by a constraint to prioritize the constraints. We illustrate that our algorithms help in scaling the state-of-the-art pointer analyses. 212 pp. Englisch. Bestandsnummer des Verkäufers 9783659977183
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Scaling Context-Sensitive Points-to Analysis
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ISBN 10: 3659977187
ISBN 13: 9783659977183
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Nasre RupeshRupesh Nasre is an Assistant Professor at IIT Madras. He received Ph.D. from IISc, Bangalore. His research interests include Compilers and Parallelization. He is a recipient of the Young Faculty Recognition Award at IIT M. Bestandsnummer des Verkäufers 151429952
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Scaling Context-Sensitive Points-to Analysis : Novel ideas to tame the scalability challenges
Verlag:
LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659977187
ISBN 13: 9783659977183
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Pointer analysis is one of the key static analyses during compilation and affects scalability and precision of several client transformations. Recent advances still lack an efficient and scalable context-sensitive inclusion-based pointer analysis. In this work, we propose four novel techniques to improve the scalability of context-sensitive points-to analysis for C/C++ programs. First, we develop an efficient way of storing the approximate points-to information using a multi-dimensional bloom filter (multibloom). Second, we devise a sound randomized algorithm that processes a group of constraints in a less precise but efficient manner and the remaining constraints in a more precise manner. Third, we transform the points-to analysis problem into finding a solution to a system of linear equations. Finally, we observe that the order in which points-to constraints are processed plays a vital role in the algorithm efficiency and propose a greedy heuristic based on the amount of points-to information computed by a constraint to prioritize the constraints. We illustrate that our algorithms help in scaling the state-of-the-art pointer analyses. Bestandsnummer des Verkäufers 9783659977183
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Scaling Context-Sensitive Points-to Analysis: Novel ideas to tame the scalability challenges
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LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659977187
ISBN 13: 9783659977183
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Scaling Context-Sensitive Points-to Analysis
Verlag:
LAP LAMBERT Academic Publishing Okt 2016, 2016
ISBN 10: 3659977187
ISBN 13: 9783659977183
Neu
Taschenbuch
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Pointer analysis is one of the key static analyses during compilation and affects scalability and precision of several client transformations. Recent advances still lack an efficient and scalable context-sensitive inclusion-based pointer analysis. In this work, we propose four novel techniques to improve the scalability of context-sensitive points-to analysis for C/C++ programs. First, we develop an efficient way of storing the approximate points-to information using a multi-dimensional bloom filter (multibloom). Second, we devise a sound randomized algorithm that processes a group of constraints in a less precise but efficient manner and the remaining constraints in a more precise manner. Third, we transform the points-to analysis problem into finding a solution to a system of linear equations. Finally, we observe that the order in which points-to constraints are processed plays a vital role in the algorithm efficiency and propose a greedy heuristic based on the amount of points-to information computed by a constraint to prioritize the constraints. We illustrate that our algorithms help in scaling the state-of-the-art pointer analyses.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 212 pp. Englisch. Bestandsnummer des Verkäufers 9783659977183
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