Chronicler: Lightweight Recording to Reproduce Field Failures
In Proceedings of the 35th International Conference on Software Engineering (ICSE 2013).
A Large-Scale, Longitudinal Study of User Profiles in World of Warcraft
In Proceedings of the 5th International Workshop on Web Intelligence and Communities, co-located with The 22nd International World Wide Web Conference (WWW ’13).
The dataset for this paper is also available.
Fine-Grained Data Management Abstractions
We participated in developing novel technology that leverages the storage abstractions of
modern operating systems (e.g., the relational databases and object-relational mappings of
Android) to automatically detect fragments strewn across memory, files and databases that is part
of the same logical application object, such as an email and its attachments, without requiring
source code or any cooperation on the part of application developers. This substrate enabled the development of our prototype tools to check that application-level deletions in fact actually delete all the data fragments related to, say, a document or a photo; to hide (and later unhide) sensitive data, e.g., to protect business data at international border crossings; and to detect when an application collects more data than required by its functionality. In our case study, our system worked correctly on 42 out of 50 real-world applications, and lead to publication of “best practices” rules of thumb required for the approach to work on future applications — e.g., fully declare database schemas, use the database to index file storage, use standard storage libraries, which are admittedly obvious to anyone with the software engineering training that some “app” developers sadly lack.
Contact Professor Roxana Geambasu (roxana@cs.columbia.edu) for further information.
Team Members
Faculty
Roxana Geambasu
Gail Kaiser
Graduate Students
Riley Spahn
Former Graduate Students
Jonathan Bell
Links
Publications
Riley Spahn, Jonathan Bell, Michael Z. Lee, Sravan Bhamidipati, Roxana Geambasu and Gail Kaiser. Pebbles: Fine-Grained Data Management Abstractions for Modern Operating Systems. 11th USENIX Symposium on Operating Systems Design and Implementation, October 2014, pp. 113-129.
Towards using Cached Data Mining for Large Scale Recommender Systems
@incollection{genspace-cache.journal,
author = “Swapneel Sheth and Gail Kaiser”,
title = “{Towards Using Cached Data Mining for Large Scale Recommender Systems}”,
booktitle = “{Recent Progress in Data Engineering and Internet Technology, Volume 1}”,
editor = “{Ford Lumban Gaol}”,
series = “{Lecture Notes in Electrical Engineering}”,
volume = “156”,
pages = “349–357”, year = “2013”,
publisher = “Springer”,
doi = {10.1007/978-3-642-28807-4_49}
}
Data Quality Assurance and Performance Measurement of Data Mining for Preventive Maintenance of Power Grid
Leon Wu, Gail Kaiser, Cynthia Rudin, and Roger Anderson. Data Quality Assurance and Performance Measurement of Data Mining for Preventive Maintenance of Power Grid. In Proceedings of the ACM SIGKDD 2011 Workshop on Data Mining for Service and Maintenance, August 2011.
Estimation of System Reliability Using a Semiparametric Model
Leon Wu, Timothy Teräväinen, Gail Kaiser, Roger Anderson, Albert Boulanger, and Cynthia Rudin. Estimation of System Reliability Using a Semiparametric Model. In Proceedings of the IEEE EnergyTech 2011 (EnergyTech), May 2011.
Constructing Subtle Concurrency Bugs Using Synchronization-Centric Second-Order Mutation Operators
Leon Wu and Gail Kaiser. Constructing Subtle Concurrency Bugs Using Synchronization-Centric Second-Order Mutation Operators. In Proceedings of the 23th International Conference on Software Engineering and Knowledge Engineering (SEKE), July 2011.
BugMiner: Software Reliability Analysis Via Data Mining of Bug Reports
Leon Wu, Boyi Xie, Gail Kaiser, and Rebecca Passonneau. BugMiner: Software Reliability Analysis Via Data Mining of Bug Reports. In Proceedings of the 23th International Conference on Software Engineering and Knowledge Engineering (SEKE), July 2011.
Improving Efficiency and Reliability of Building Systems Using Machine Learning and Automated Online Evaluation
Leon Wu, Gail Kaiser, David Solomon, Rebecca Winter, Albert Boulanger, and Roger Anderson. Improving Efficiency and Reliability of Building Systems Using Machine Learning and Automated Online Evaluation. In Proceedings of the Eighth Annual IEEE Long Island Systems, Applications and Technology Conference (LISAT), May 2012.
An Autonomic Reliability Improvement System for Cyber-Physical Systems
Leon Wu and Gail Kaiser. An Autonomic Reliability Improvement System for Cyber-Physical Systems. In Proceedings of the IEEE 14th International Symposium on High-Assurance Systems Engineering (HASE), October 2012.