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Adrian Sorin Baras

from Redmond, WA
Age ~47

Adrian Baras Phones & Addresses

  • 16314 NE 43Rd Ct, Redmond, WA 98052 (425) 444-7458
  • 4306 156Th Ave, Redmond, WA 98052 (425) 882-0110
  • Bellevue, WA

Work

Company: Google Sep 2013 Position: Software engineer

Education

Degree: Bachelors, Bachelor of Science School / High School: Politehnica University of Timisoara 1995 to 2000 Specialities: Computer Science

Skills

Microsoft Sql Server • Software Engineering • Software Development • Software Design • Distributed Systems • C# • Object Oriented Design • C++ • .Net • Algorithms • Databases • Visual Studio • Xml • Sql • Embedded Software

Industries

Computer Software

Resumes

Resumes

Adrian Baras Photo 1

Software Engineer

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Location:
4306 156Th Ave northeast, Redmond, WA 98052
Industry:
Computer Software
Work:
Google
Software Engineer

Microsoft Mar 2012 - May 2013
Software Development Lead

Microsoft May 2001 - Feb 2012
Software Engineer

Computer Voice Systems Mar 2000 - Apr 2001
Software Engineer

Cultural Srl Nov 1997 - Feb 2000
Software Engineer
Education:
Politehnica University of Timisoara 1995 - 2000
Bachelors, Bachelor of Science, Computer Science
Skills:
Microsoft Sql Server
Software Engineering
Software Development
Software Design
Distributed Systems
C#
Object Oriented Design
C++
.Net
Algorithms
Databases
Visual Studio
Xml
Sql
Embedded Software

Publications

Us Patents

System And Method For An Improved Type Inference

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US Patent:
7426503, Sep 16, 2008
Filed:
Apr 25, 2005
Appl. No.:
11/113708
Inventors:
Adrian S. Baras - Redmond WA, US
Michael Rys - Sammamish WA, US
Istvan Cseri - Redmond WA, US
Oliver N. Seeliger - Sammamish WA, US
Peter Kukol - Prescott AZ, US
Assignee:
Microsoft Corporation - Redmond WA
International Classification:
G06N 5/00
US Classification:
706 52, 706 45
Abstract:
An improved type inference may be calculated for a path expression that may be classified into a series of input expressions followed by steps. For each such series, the inference may be calculated based on input including a type for the input expression, an axis for the step, and a node test for the step. The cardinality of the input expression type is preserved for the calculation of the step type. Also, a set of one or more matching node types may be identified within the type repository. These matching node types are node types within the axis of the step that match the node test of the step. These matching node types are identified without calculating the full content type implied by the axis. Avoiding the calculation of the full content type of the axis may reduce the processing time required to perform the inference.

Relational Database Scalar Subquery Optimization

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US Patent:
7873627, Jan 18, 2011
Filed:
Jan 18, 2006
Appl. No.:
11/334655
Inventors:
Torsten Walther Grabs - Bellevue WA, US
Adrian Sorin Baras - Redmond WA, US
Cesar A. Galindo-Legaria - Redmond WA, US
Assignee:
Microsoft Corporation - Redmond WA
International Classification:
G06F 17/30
US Classification:
707713
Abstract:
When two or more scalar subtrees in an execution plan are directed towards the same data set, but request different data from the data set, the two subtrees are replaced in the execution plan with a new subtree which queries the data set only once. This new query to the data set covers all data required by the different subtrees. A pivoting step then is used to separate the data which would have been sought by each subtree. The pivoting step also yields data in the same form as would have resulted from the original subtrees.

Fuzzing System And Method For Exhaustive Security Fuzzing Within An Sql Server

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US Patent:
7953674, May 31, 2011
Filed:
May 17, 2007
Appl. No.:
11/750132
Inventors:
Jiazhen Wu - Sammamish WA, US
Raul Garcia - Kirkland WA, US
Craig Alan Gick - Woodinville WA, US
Erik Ismert - Shoreline WA, US
Adrian Sorin Baras - Redmond WA, US
Assignee:
Microsoft Corporation - Redmond WA
International Classification:
G06F 15/18
US Classification:
706 1
Abstract:
Systems and methods that incorporate fuzzing capabilities within an SQL server to facilitate penetration testing. A fuzzing component associated with the SQL server provides an entry point for accessing the fuzzing system to update explicit user specified parameters associated with SQL, wherein the server's in depth knowledge regarding semantics of the language code (e. g. , manner of parsing) can be employed to determine vulnerabilities thereof.

Static Typing Of Xquery Expressions In Lax Validation Content

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US Patent:
8606806, Dec 10, 2013
Filed:
Jul 25, 2008
Appl. No.:
12/179647
Inventors:
Adrian Sorin Baras - Redmond WA, US
Michael Rys - Issaquah WA, US
Assignee:
Microsoft Corporation - Redmond WA
International Classification:
G06F 7/00
G06F 17/30
US Classification:
707761
Abstract:
Systems and methods that extend static typing rules/algorithms of the World Wide Web Consortium (W3C) rules, with a more precise static typing algorithm that supplies knowledge for types occurring in the Lax validation section. The Lax validation can be identified, and associated expressions known with particularity, wherein types can be inferred for XQuery expressions that navigate down into the Lax validation section. An annotation component annotates elements (e. g. , wild card sections) with additional information about wild card sections, and a mapping component maps Lax wild cards to type systems.

System And Method For Compiling An Extensible Markup Language Based Query

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US Patent:
20050210002, Sep 22, 2005
Filed:
Mar 18, 2004
Appl. No.:
10/803283
Inventors:
Shankar Pal - Redmond WA, US
Istvan Cseri - Redmond WA, US
Oliver Seeliger - Sammamish WA, US
Gideon Schaller - Bellevue WA, US
Adrian Baras - Redmond WA, US
Wei Yu - Issaquah WA, US
Denis Churin - Sammamish WA, US
Peter Kukol - Scottsdale AZ, US
International Classification:
G06F007/00
US Classification:
707003000
Abstract:
An extensible markup language (XML) expression included in a query is parsed to yield an abstract syntax tree. The abstract syntax tree is then transformed into a unified tree including XML algebra operations. The unified tree is then converted into a relational tree including enhanced relational algebra operations. The relational tree is then forwarded to a query processor for optimization and execution of the query at the query processor.

Execution-Time Dynamic Range Partitioning Transformations

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US Patent:
20220358142, Nov 10, 2022
Filed:
Jul 25, 2022
Appl. No.:
17/814694
Inventors:
- Mountain View CA, US
Mikhail Entin - Redmond WA, US
Adrian Baras - Mountain View CA, US
Pavan Edara - Mountain View CA, US
Aleksandras Surna - Redmond WA, US
Assignee:
Google LLC - Mountain View CA
International Classification:
G06F 16/27
G06F 16/23
Abstract:
An example method includes receiving a data load request requesting loading and partitioning of an unknown quantity of user data for storage at a data storage system. The user data including a partitioning key; a total data size of the user data; a plurality of rows, each row of the plurality of rows associated with a value defined by the partitioning key; and one or more columns. The method also includes identifying one or more storage constraints for the data storage system. The method further includes, after receiving the user data, determining a plurality of partitioning quantiles defining respective ranges of values of the partitioning key based on the user data and the one or more storage constraints for the data storage system; and range partitioning each row of the user data into files based on the value associated with the row defined by the partitioning key, and the respective ranges of the values of the partitioning key defined by the plurality of partitioning quantiles.

Execution-Time Dynamic Range Partitioning Transformations

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US Patent:
20210349648, Nov 11, 2021
Filed:
May 11, 2020
Appl. No.:
16/872238
Inventors:
- Mountain View CA, US
Mikhail Entin - Redmond WA, US
Adrian Baras - Mountain View CA, US
Pavan Edara - Mountain View CA, US
Aleksandras Surna - Mountain View CA, US
Assignee:
Google LLC - Mountain View CA
International Classification:
G06F 3/06
Abstract:
A method for execution-time dynamic range partitioning includes receiving user data including a partitioning key and a clustering key. The user data includes a respective number of total rows defining a total data size for the user data. The method also includes identifying storage constraints for the data storage system. The storage constraints include a target file size and a target number of rows per file. The method further includes determining a plurality of split points for the user data based on the storage constraints. The method also includes generating partitioning quantiles from the plurality of split points that define a range between each split point of the plurality of split points. The method further includes range partitioning each row of the user data into files using the partitioning quantiles.
Adrian Sorin Baras from Redmond, WA, age ~47 Get Report