4 Search Results for "Kellogg, Martin"


Document
Artifact
Accumulation Analysis (Artifact)

Authors: Martin Kellogg, Narges Shadab, Manu Sridharan, and Michael D. Ernst

Published in: DARTS, Volume 8, Issue 2, Special Issue of the 36th European Conference on Object-Oriented Programming (ECOOP 2022)


Abstract
This artifact contains the data and analysis supporting the literature survey in section 4 of [Kellogg et al., 2022]. In our literature survey, we examined 187 papers from the literature that mention "typestate" and analyzed the typestate specifications they contained to determine whether or not they are accumulation typestate specifications. Our purpose in doing this literature survey was to determine whether typestate FSMs were accumulation or not. However, we believe that the collection of typestate automata in typestates.pdf might be useful to anyone interested in the sort of typestate automata that appear in the literature. If we had had access to such a collection (gathered for a different purpose), our classification of whether these typestate automata were accumulation would have been much simpler. Anyone interested in properties of typestate automata can re-use our work.

Cite as

Martin Kellogg, Narges Shadab, Manu Sridharan, and Michael D. Ernst. Accumulation Analysis (Artifact). In Special Issue of the 36th European Conference on Object-Oriented Programming (ECOOP 2022). Dagstuhl Artifacts Series (DARTS), Volume 8, Issue 2, pp. 22:1-22:3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)


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@Article{kellogg_et_al:DARTS.8.2.22,
  author =	{Kellogg, Martin and Shadab, Narges and Sridharan, Manu and Ernst, Michael D.},
  title =	{{Accumulation Analysis (Artifact)}},
  pages =	{22:1--22:3},
  journal =	{Dagstuhl Artifacts Series},
  ISSN =	{2509-8195},
  year =	{2022},
  volume =	{8},
  number =	{2},
  editor =	{Kellogg, Martin and Shadab, Narges and Sridharan, Manu and Ernst, Michael D.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DARTS.8.2.22},
  URN =		{urn:nbn:de:0030-drops-162209},
  doi =		{10.4230/DARTS.8.2.22},
  annote =	{Keywords: Typestate, finite-state property}
}
Document
Accumulation Analysis

Authors: Martin Kellogg, Narges Shadab, Manu Sridharan, and Michael D. Ernst

Published in: LIPIcs, Volume 222, 36th European Conference on Object-Oriented Programming (ECOOP 2022)


Abstract
A typestate specification indicates which behaviors of an object are permitted in each of the object’s states. In the general case, soundly checking a typestate specification requires precise information about aliasing (i.e., an alias or pointer analysis), which is computationally expensive. This requirement has hindered the adoption of sound typestate analyses in practice. This paper identifies accumulation typestate specifications, which are the subset of typestate specifications that can be soundly checked without any information about aliasing. An accumulation typestate specification can be checked instead by an accumulation analysis: a simple, fast dataflow analysis that conservatively approximates the operations that have been performed on an object. This paper formalizes the notions of accumulation analysis and accumulation typestate specification. It proves that accumulation typestate specifications are exactly those typestate specifications that can be checked soundly without aliasing information. Further, 41% of the typestate specifications that appear in the research literature are accumulation typestate specifications.

Cite as

Martin Kellogg, Narges Shadab, Manu Sridharan, and Michael D. Ernst. Accumulation Analysis. In 36th European Conference on Object-Oriented Programming (ECOOP 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 222, pp. 10:1-10:30, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)


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@InProceedings{kellogg_et_al:LIPIcs.ECOOP.2022.10,
  author =	{Kellogg, Martin and Shadab, Narges and Sridharan, Manu and Ernst, Michael D.},
  title =	{{Accumulation Analysis}},
  booktitle =	{36th European Conference on Object-Oriented Programming (ECOOP 2022)},
  pages =	{10:1--10:30},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-225-9},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{222},
  editor =	{Ali, Karim and Vitek, Jan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2022.10},
  URN =		{urn:nbn:de:0030-drops-162381},
  doi =		{10.4230/LIPIcs.ECOOP.2022.10},
  annote =	{Keywords: Typestate, finite-state property}
}
Document
Reverse Derivative Categories

Authors: Robin Cockett, Geoffrey Cruttwell, Jonathan Gallagher, Jean-Simon Pacaud Lemay, Benjamin MacAdam, Gordon Plotkin, and Dorette Pronk

Published in: LIPIcs, Volume 152, 28th EACSL Annual Conference on Computer Science Logic (CSL 2020)


Abstract
The reverse derivative is a fundamental operation in machine learning and automatic differentiation [Martín Abadi et al., 2015; Griewank, 2012]. This paper gives a direct axiomatization of a category with a reverse derivative operation, in a similar style to that given by [Blute et al., 2009] for a forward derivative. Intriguingly, a category with a reverse derivative also has a forward derivative, but the converse is not true. In fact, we show explicitly what a forward derivative is missing: a reverse derivative is equivalent to a forward derivative with a dagger structure on its subcategory of linear maps. Furthermore, we show that these linear maps form an additively enriched category with dagger biproducts.

Cite as

Robin Cockett, Geoffrey Cruttwell, Jonathan Gallagher, Jean-Simon Pacaud Lemay, Benjamin MacAdam, Gordon Plotkin, and Dorette Pronk. Reverse Derivative Categories. In 28th EACSL Annual Conference on Computer Science Logic (CSL 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 152, pp. 18:1-18:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)


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@InProceedings{cockett_et_al:LIPIcs.CSL.2020.18,
  author =	{Cockett, Robin and Cruttwell, Geoffrey and Gallagher, Jonathan and Lemay, Jean-Simon Pacaud and MacAdam, Benjamin and Plotkin, Gordon and Pronk, Dorette},
  title =	{{Reverse Derivative Categories}},
  booktitle =	{28th EACSL Annual Conference on Computer Science Logic (CSL 2020)},
  pages =	{18:1--18:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-132-0},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{152},
  editor =	{Fern\'{a}ndez, Maribel and Muscholl, Anca},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CSL.2020.18},
  URN =		{urn:nbn:de:0030-drops-116611},
  doi =		{10.4230/LIPIcs.CSL.2020.18},
  annote =	{Keywords: Reverse Derivatives, Cartesian Reverse Differential Categories, Categorical Semantics, Cartesian Differential Categories, Dagger Categories, Automatic Differentiation}
}
Document
Construction of Implicit Surfaces from Point Clouds Using a Feature-based Approach

Authors: Patric Keller, Oliver Kreylos, Eric S. Cowgill, Louise H. Kellogg, and Martin Hering-Bertram

Published in: Dagstuhl Follow-Ups, Volume 2, Scientific Visualization: Interactions, Features, Metaphors (2011)


Abstract
We present a novel feature-based approach to surface generation from point clouds in three-dimensional space obtained by terrestrial and airborne laser scanning. In a first step, we apply a multiscale clustering and classification of local point set neighborhoods by considering their geometric shape. Corresponding feature values quantify the similarity to curve-like, surface-like, and solid-like shapes. For selecting and extracting surface features, we build a hierarchical trivariate B-spline representation of this surface feature function. Surfaces are extracted with a variant of marching cubes (MC), providing an inner and outer shell that are merged into a single non-manifold surface component at the field’s ridges. By adapting the isovalue of the feature function the user may control surface topology and thus adapt the extracted features to the noise level of the underlying point cloud. User control and adaptive approximation make our method robust for noisy and complex point data.

Cite as

Patric Keller, Oliver Kreylos, Eric S. Cowgill, Louise H. Kellogg, and Martin Hering-Bertram. Construction of Implicit Surfaces from Point Clouds Using a Feature-based Approach. In Scientific Visualization: Interactions, Features, Metaphors. Dagstuhl Follow-Ups, Volume 2, pp. 129-143, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2011)


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@InCollection{keller_et_al:DFU.Vol2.SciViz.2011.129,
  author =	{Keller, Patric and Kreylos, Oliver and Cowgill, Eric S. and Kellogg, Louise H. and Hering-Bertram, Martin},
  title =	{{Construction of Implicit Surfaces from Point Clouds Using a Feature-based Approach}},
  booktitle =	{Scientific Visualization: Interactions, Features, Metaphors},
  pages =	{129--143},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-26-2},
  ISSN =	{1868-8977},
  year =	{2011},
  volume =	{2},
  editor =	{Hagen, Hans},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DFU.Vol2.SciViz.2011.129},
  URN =		{urn:nbn:de:0030-drops-33032},
  doi =		{10.4230/DFU.Vol2.SciViz.2011.129},
  annote =	{Keywords: 3D Point Clouds, Surface Reconstruction, Implicit Surfaces}
}
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