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Michael Gasch

dblp:283/7502 · DBLP profile ↗
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3ranked-venue papers
0as first author
2since 2021 · last 2022
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 3 · 2 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Software engineering, system software, and programming languages
2 papers
Software testing · 57% Programming languages and type systems · 43%
Computer architecture, parallel and distributed computing, and storage systems
2 papers
Cloud and datacenter computing · 100%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Software testing › non-functional testing
reliability testing
0.612022
Automatic Reliability Testing For Cluster Management Controllers · OSDI 2022
Cloud and datacenter computing › cluster resource management and scheduling
cluster resource management
0.612022
Automatic Reliability Testing For Cluster Management Controllers · OSDI 2022
Programming languages and type systems › programming paradigms
declarative programming
0.412020
Building Scalable and Flexible Cluster Managers Using Declarative Programming · OSDI 2020
Cloud and datacenter computing
cluster resource management and scheduling
0.412020
Building Scalable and Flexible Cluster Managers Using Declarative Programming · OSDI 2020

Methods — techniques the papers use, named apart from their topics

automatic reliability testing · 1.1declarative programming · 0.9
YearPublicationVenuePosition
2022 Automatic Reliability Testing For Cluster Management Controllers
Xudong Sun 0013, Wenqing Luo, Jiawei Tyler Gu, Aishwarya Ganesan, Ramnatthan Alagappan, Michael Gasch, Lalith Suresh 0001, Tianyin Xu
OSDI6
2021 Reasoning about modern datacenter infrastructures using partial histories
abstract
Modern datacenter infrastructures are increasingly architected as a cluster of loosely coupled services. The cluster states are typically maintained in a logically centralized, strongly consistent data store (e.g., ZooKeeper, Chubby and etcd), while the services learn about the evolving state by reading from the data store, or via a stream of notifications. However, it is challenging to ensure services are correct, even in the presence of failures, networking issues, and the inherent asynchrony of the distributed system. In this paper, we identify that partial histories can be used to effectively reason about correctness for individual services in such distributed infrastructure systems. That is, individual services make decisions based on observing only a subset of changes to the world around them. We show that partial histories, when applied to distributed infrastructures, have immense explanatory power and utility over the state of the art. We discuss the implications of partial histories and sketch tooling for reasoning about distributed infrastructure systems.
Xudong Sun 0013, Lalith Suresh 0001, Aishwarya Ganesan, Ramnatthan Alagappan, Michael Gasch, Lilia Tang, Tianyin Xu
HotOS5
2020 Building Scalable and Flexible Cluster Managers Using Declarative Programming
Lalith Suresh 0001, João Loff, Faria Kalim, Sangeetha Abdu Jyothi, Nina Narodytska, Leonid Ryzhyk, Sahan Gamage, Brian Oki, Pranshu Jain, Michael Gasch
OSDI10