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Sudheendra Hangal

Researcher at Ashoka University

Publications -  29
Citations -  1645

Sudheendra Hangal is an academic researcher from Ashoka University. The author has contributed to research in topics: Shared memory & Consistency model. The author has an hindex of 14, co-authored 29 publications receiving 1599 citations. Previous affiliations of Sudheendra Hangal include Oracle Corporation & Stanford University.

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Proceedings ArticleDOI

Tracking down software bugs using automatic anomaly detection

TL;DR: DIDUCE, a practical and effective tool that aids programmers in detecting complex program errors and identifying their root causes, is introduced and suggests that detecting and checking program invariants dynamically is a simple and effective methodology for debugging many different kinds of program errors across a wide variety of application domains.
Journal ArticleDOI

TSOtool: A Program for Verifying Memory Systems Using the Memory Consistency Model

TL;DR: This paper describes a new polynomial time algorithm which is incorporated in TSOtool, a program to check the behavior of the memory subsystem in a shared memory multiprocessor and has been successful in detecting several bugs in the design of commercial microprocessors and systems, during both pre-silicon and post- silicon phases of validation.
Proceedings ArticleDOI

IODINE: a tool to automatically infer dynamic invariants for hardware designs

TL;DR: IODINE presents a way to automatically extract properties such as state machine protocols, request-acknowledge pairs, and mutual exclusion between signals from design simulations using dynamic analysis.
Patent

Method and Apparatus for Software Simulation

TL;DR: A software simulation method and program storage device for software defect detection and obtaining insight into software code is disclosed, where simulation consists of executing target software program code for multiple input values and multiple code paths at the same time, thus achieving 100% coverage over inputs and paths as mentioned in this paper.
Proceedings ArticleDOI

PrPl: a decentralized social networking infrastructure

TL;DR: Preliminary experimental results suggest that it is viable to enable sharing of private social data between close friends with a decentralized architecture, and can be written in a small number of lines of code using SociaLite.