Reproducing experimental results is a core tenet of the scientific method. Unfortunately, the increasing complexity of the system we build, deploy and evaluate makes it difficult to reproduce results and hence is one of the greatest impairments for the progress of science in general and distributed systems in particular.
The complexity stems not only from the increasing complexity of the systems under study, but also from the inherent complexity of capturing and controlling all variables that can potentially affect experimental results.
We argue that this can only be addressed with a systematic approach to all the stages of the evaluation process. Angainor is a step in this direction.
Our goal is to address the following challenges: i) precisely describe the environment and variables affecting the experiment, ii) minimize the number of (uncontrollable) variables affecting the experiment and iii) have the ability to subject the system under evaluation to controlled fault patterns.
May 20th 2019 Open PhD position check here for more details.
November 05th 2017 Open Postdoc position check here for more details. A Ph.D. position is expected to open soon.
July 27th 2018 - Miguel Matos will be giving a keynote at the ApPLIED Workshop - Advanced tools, programming languages, and PLatforms for Implementing and Evaluating algorithms for Distributed systems held in conjunction with PODC-2018 Paper Slides
June 1st 2018 - The Angainor project officially started. Check the Team and Funding below for more details.
An early alpha version of the platform is available here.
This project is supported by Fundo Europeu de Desenvolvimento Regional (FEDER) through Programa Operacional Regional de Lisboa and by Fundação para a Ciência e Tecnologia (FCT) through projects with reference UID/CEC/50021/2013 and LISBOA-01-0145-FEDER-031456.