Valgrind

Valgrind is an instrumentation framework for building dynamic analysis tools. There are Valgrind tools that can automatically detect many memory management and threading bugs, and profile your programs in detail. You can also use Valgrind to build new tools. The Valgrind distribution currently includes six production-quality tools: a memory error detector, two thread error detectors, a cache and branch-prediction profiler, a call-graph generating cache and branch-prediction profiler, and a heap profiler. It also includes three experimental tools: a heap/stack/global array overrun detector, a second heap profiler that examines how heap blocks are used, and a SimPoint basic block vector generator. It runs on the following platforms: X86/Linux, AMD64/Linux, ARM/Linux, PPC32/Linux, PPC64/Linux, S390X/Linux, ARM/Android (2.3.x), X86/Darwin and AMD64/Darwin (Mac OS X 10.6 and 10.7).


References in zbMATH (referenced in 63 articles )

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  1. Coelho, Vitor Nazário; Koochaksaraei, Roozbeh Haghnazar: Non-dominated solutions for time series learning and forecasting. Generating models with a generic two-phase Pareto loca search with VND (2022)
  2. Francalanza, Adrian: A theory of monitors (2021)
  3. Kulesza, Joel A.; Solomon, Clell J.; Kiedrowski, Brian C.: Discrete ordinates analysis of the forced-flight variance reduction technique in Monte Carlo neutral particle transport simulations (2021)
  4. Manthey, Norbert: The \textscMergeSatsolver (2021)
  5. Shvets, P. A.; Voevodin, V. V.: “Endless” workload analysis of large-scale supercomputers (2021)
  6. Weng, Min-Hsien; Malik, Robi; Utting, Mark: Automatic proofs of memory deallocation for a Whiley-to-C compiler (2021)
  7. Banović, Mladen; Vasilopoulos, Ilias; Walther, Andrea; Meyer, Marcus: Algorithmic differentiation of an industrial airfoil design tool coupled with the adjoint CFD method (2020)
  8. Konshin, I. N.; Terekhov, K. M.; Vassilevski, Yu. V.: Numerical modelling via INMOST software platform (2020)
  9. Alpirez Bock, Estuardo; Bos, Joppe W.; Brzuska, Chris; Hubain, Charles; Michiels, Wil; Mune, Cristofaro; Sanfelix Gonzalez, Eloi; Teuwen, Philippe; Treff, Alexander: White-box cryptography: don’t forget about grey-box attacks (2019)
  10. Andrei V. Novikov: PyClustering: Data Mining Library (2019) not zbMATH
  11. Potter, Samuel F.; Cameron, Maria K.: Ordered line integral methods for solving the eikonal equation (2019)
  12. Valentin Niess, Anne Barnoud, Cristina Cârloganu, Olivier Martineau-Huynh: TURTLE: A C library for an optimistic stepping through a topography (2019) arXiv
  13. Banović, Mladen; Mykhaskiv, Orest; Auriemma, Salvatore; Walther, Andrea; Legrand, Herve; Müller, Jens-Dominik: Algorithmic differentiation of the Open CASCADE technology CAD kernel and its coupling with an adjoint CFD solver (2018)
  14. Cosme, Iria C. S.; Fernandes, Isaac F.; de Carvalho, João L.; Xavier-de-Souza, Samuel: Memory-usage advantageous block recursive matrix inverse (2018)
  15. Feyzi, Farid; Parsa, Saeed: A program slicing-based method for effective detection of coincidentally correct test cases (2018)
  16. Gonzaga de Oliveira, Sanderson L.; Nogueira, Jéssica Renata: An evaluation of point-insertion sequences for incremental Delaunay tessellations (2018)
  17. Hück, Alexander; Bischof, Christian; Sagebaum, Max; Gauger, Nicolas R.; Jurgelucks, Benjamin; Larour, Eric; Perez, Gilberto: A usability case study of algorithmic differentiation tools on the ISSM ice sheet model (2018)
  18. Jordan, Charles; Joswig, Michael; Kastner, Lars: Parallel enumeration of triangulations (2018)
  19. Jurgelucks, Benjamin; Claes, Leander; Walther, Andrea; Henning, Bernd: Optimization of triple-ring electrodes on piezoceramic transducers using algorithmic differentiation (2018)
  20. Dowsley, Rafael; Michalas, Antonis; Nagel, Matthias; Paladi, Nicolae: A survey on design and implementation of protected searchable data in the cloud (2017)

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