Luc Teboul

Luc Teboul

New York, New York, United States
8K followers 500+ connections

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About

I look after Engineering for Transaction Banking, #TxB (https://txb.gs.com/) is the most…

Articles by Luc

Activity

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Experience

  • Goldman Sachs Graphic

    Goldman Sachs

    New York, New York, United States

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    New York, United States

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    Seattle, Washington, United States

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    New York, New York

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    Greater New York City Area

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    Greater New York City Area

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    New York, New York, United States

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    Paris Area, France

Education

Publications

  • A Pointcut Language for Control-Flow

    Springler

    In AOP, a pointcut matches base-program execution points where an advice must be executed. Most pointcut are method signatures. In AspectJ, pointcuts based on control-flow (e.g. the method foo when it is called during the method bar) can be defined with a cflow operator which also provides context passing (e.g., when foo is called, print the argument of the pending call to bar).
    In this article, we propose a pointcut language that extends the pointcut language of AspectJ for control-flow. We…

    In AOP, a pointcut matches base-program execution points where an advice must be executed. Most pointcut are method signatures. In AspectJ, pointcuts based on control-flow (e.g. the method foo when it is called during the method bar) can be defined with a cflow operator which also provides context passing (e.g., when foo is called, print the argument of the pending call to bar).
    In this article, we propose a pointcut language that extends the pointcut language of AspectJ for control-flow. We exemplify how it enables definition of useful pointcuts based on control-flow with context passing. We provide both an intuitive semantics based on post-mortem execution traces and an implementation based on program instrumentation. We also provide analyses for pointcut conflict and instrumentation optimization.

    Other authors
    • Remi Douence
    See publication

Patents

  • Method and System for Time Series Data Quality Management

    Filed US 72167.001036

    The ability to retrieve and store reliable and stable market levels is a necessary condition to produce reliable and accurate VaR numbers. This patent describes a set of methods and technics to tackle time series data quality at large scale.

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Languages

  • French

    Native or bilingual proficiency

  • English

    Native or bilingual proficiency

  • Hebrew

    Elementary proficiency

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