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Amer Diwan

Amer Diwan

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    Meaningful availability
    Dan Ardelean
    Philipp Emanuel Hoffmann
    Tamás Hauer
    17th USENIX Symposium on Networked Systems Design and Implementation (NSDI'20) (2020)
    Preview abstract Accurate measurement of service availability is the cornerstone of good service management: it quantifies the gap between user expectation and system performance, and provides actionable data to prioritize development and operational tasks. We propose a novel metric, user-uptime, which is event- based but is time-sensitive and which approximates aggregated user-perceived reliability better than current metrics. For a holistic view of availability across timescales from minutes to months or quarters, we augment user-uptime with a novel aggregation and visualization paradigm: windowed uptime. Using an example from G Suite we demonstrate its effectiveness in differentiating between unreliability caused by flakiness and an extended outage. View details
    Why you should care about quantile regression
    Augusto Born De Oliveira
    Sebastian Fischmeister
    Matthias Hauswirth
    Peter Sweeney
    Architectural Support for Programming Languages and Operating Systems, ASPLOS '13, ACM (2013), pp. 207-218
    Preview
    Measuring Enforcement Windows with Symbolic Trace Interpretation: What Well-Behaved Programs Say
    Devin Coughlin
    Bor-Yuh Evan Chang
    Jeremy Siek
    Proceedings of the 2012 International Symposium on Software Testing and Analysis, ACM, pp. 276-286
    Preview
    Preview abstract Modern object-oriented languages have complex features that cause programmers to overspecify their programs. This overspecification hinders automatic optimizers, since they must preserve the overspecified semantics. If an optimizer knew which semantics the programmer intended, it could do a better job. Making a programmer clarify his intentions by placing assumptions into the program is rarely practical. This is because the programmer does not know which parts of the programs' overspecified semantics hinder the optimizer. Therefore, the programmer has to guess which assumption to add. Since the programmer can add many different assumptions to a large program, he will need to place many such assumptions before he guesses right and helps the optimizer. We present IOpt, a practical optimizer that uses a specification of the programmers' intended semantics to enable additional optimizations. That way, our optimizer can significantly improve the performance of a program. We present case studies in which we use IOpt to speed up two programs by over 50%. To make specifying the intended semantics practical, IOpt communicates with the programmer. IOpt identifies which assumptions the programmer textit{should} place, and where he should place them. IOpt ranks each assumption by (i) the likelyhood that the assumption conforms to the programmers' intended semantics and (ii) how much the assumption will help IOpt improve the programs' performance. IOpt proposes ranked assumptions to the programmer, who just picks those that conform to his intended semantics. With this approach, IOpt keeps the programmers' specification burden low. Our case studies show that the programmer just needs to add a few assumptions to realize the 50% speedup. View details
    Explaining Failures of Program Analyses
    Proceedings of PLDI (2008), pp. 10
    Simplifying Web Traversals by Recognizing Behavior Patterns
    Christian Doer
    Proceedings of Hypertext 2007, pp. 105-114
    Fast Online Pointer Analysis
    Martin Hirzel
    Michael Hind
    ACM Transactions on Programming Languages and Systems (TOPLAS), vol. 29 (2007), pp. 11
    Understanding the Behavior of Compiler Optimizations
    Han Lee
    J. Elliot B. Moss
    Software: Practice and Experience, vol. 36 (2006), pp. 835-844
    The DaCapo Benchmarks: Java Benchmarking Development and Analysis
    Stephen M. Blackburn
    Robin Garner
    Chris Hoffmann
    Asjad M. Khan
    Kathryn S. McKinley
    Rotem Bentzu
    Daniel Feinberg
    Daniel Frampton
    Samuel Z. Guyer
    Martin Hirzel
    Antony Hosking
    Maria Jump
    Han Lee
    J. Elliot B. Moss
    Aashish Phansalkar
    Darko Stefanovic
    Thomas VanDrunen
    Ben Wiedermann
    Proceedings of OOSPLA, ACM (2006)
    SUIF Explorer: An Interactive and Interprocedural Parallelizer
    Shih-Wei Liao
    Robert P. Bosch Jr.
    Anwar M. Ghuloum
    Monica S. Lam
    PPOPP (1999), pp. 37-48