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Santonu Sarkar

Bio: Santonu Sarkar is an academic researcher from Birla Institute of Technology and Science. The author has contributed to research in topics: Software as a service & Software system. The author has an hindex of 22, co-authored 125 publications receiving 2048 citations. Previous affiliations of Santonu Sarkar include Jadavpur University & Accenture.


Papers
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Proceedings ArticleDOI
13 May 2014
TL;DR: This paper proposes a framework and a tool to automatically discover invariants from application logs and to online detect their violation and shows the usefulness of the approach to detect runtime issues from logs in the form of violations of selected invariants.
Abstract: The increasing popularity of Software as a Service (SaaS) stresses the need of solutions to predict failures and avoid service interruptions, which invariably result in SLA violations and severe loss of revenue. A promising approach to continuously monitor the correct functioning of the system is to check the execution conformance to a set of invariants, i.e., properties that must hold when the system is deemed to run correctly. In this paper we propose a framework and a tool to automatically discover invariants from application logs and to online detect their violation. The framework has been applied on 9 months of log events from a real-world SaaS application. Results show that the proposed tool is able to automatically select 12 invariants with a stringent goodness of fit criteria out of more than 500 potential relationships. We also show the usefulness of our approach to detect runtime issues from logs in the form of violations of selected invariants, corresponding to silent errors that usually go unnoticed by the system maintenance personnel, even if they could represent symptoms of upcoming service failures.

11 citations

Patent
17 Feb 2011
TL;DR: In this article, a textual analysis system is configured to compare textual content of textual statements and to determine a level of correspondence between the first textual statement and the second textual statement based on the score.
Abstract: A textual analysis system is configured to compare textual content of textual statements. The textual analysis system is configured to score the textual content of a first textual statement and a second textual statement. Based on the score, the textual analysis system may determine a level of correspondence between the first textual statement and the second textual statement. The textual analysis system is configured to generate an interactive visual representation of the correspondence levels between the first statement and the second statement. The visual representation may be transmitted to a display.

9 citations

Journal ArticleDOI
TL;DR: This paper empirically determine the half-life of software engineering research topics from 1975 to 2010, using natural language processing techniques to semi-automatically identify and associate a set of topics with a paper.
Abstract: We all want to be associated with long lasting ideas; as originators, or at least, expositors. For a tyro researcher or a seasoned veteran, knowing how long an idea will remain interesting in the community is critical in choosing and pursuing research threads. In the physical sciences, the notion of half-life is often evoked to quantify decaying intensity. In this paper, we study a corpus of 19,000+ papers written by 21,000+ authors across 16 software engineering publication venues from 1975 to 2010, to empirically determine the half-life of software engineering research topics. In the absence of any consistent and well-accepted methodology for associating research topics to a publication, we have used natural language processing techniques to semi-automatically identify and associate a set of topics with a paper. We adapted measures of half-life already existing in the bibliometric context for our study, and also defined a new measure based on publication and citation counts. We find evidence that some of the identified research topics show a mean half-life of close to 15 years, and there are topics with sustaining interest in the community. We report the methodology of our study in this paper, as well as the implications and utility of our results.

9 citations

Patent
13 Jun 2012
TL;DR: In this article, the authors proposed a system for scalable bio-informatics sequence search on cloud, which comprises the steps of partitioning a genome data into a plurality of datasets and storing the plurality of data sets in a database.
Abstract: The present invention relates to a computer-implemented method, system and computer readable medium for providing a scalable bio-informatics sequence search on cloud. The method comprises the steps of partitioning a genome data into a plurality of datasets and storing the plurality of data sets in a database. Receiving at least one sequence search request input and searching for a genome sequence in the database corresponding to the search request input and scaling of the sequence search based on the sequence search request input.

9 citations

Journal ArticleDOI
TL;DR: A query language (VDDL) for VLSI database access and design description has been proposed and the salient features of the data model and its advantages have been explained.

9 citations


Cited by
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01 Jan 2016
TL;DR: The using multivariate statistics is universally compatible with any devices to read, allowing you to get the most less latency time to download any of the authors' books like this one.
Abstract: Thank you for downloading using multivariate statistics. As you may know, people have look hundreds times for their favorite novels like this using multivariate statistics, but end up in infectious downloads. Rather than reading a good book with a cup of tea in the afternoon, instead they juggled with some harmful bugs inside their laptop. using multivariate statistics is available in our digital library an online access to it is set as public so you can download it instantly. Our books collection saves in multiple locations, allowing you to get the most less latency time to download any of our books like this one. Merely said, the using multivariate statistics is universally compatible with any devices to read.

14,604 citations

Christopher M. Bishop1
01 Jan 2006
TL;DR: Probability distributions of linear models for regression and classification are given in this article, along with a discussion of combining models and combining models in the context of machine learning and classification.
Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

10,141 citations

Book
Michael R. Lyu1
30 Apr 1996
TL;DR: Technical foundations introduction software reliability and system reliability the operational profile software reliability modelling survey model evaluation and recalibration techniques practices and experiences and best current practice of SRE software reliability measurement experience.
Abstract: Technical foundations introduction software reliability and system reliability the operational profile software reliability modelling survey model evaluation and recalibration techniques practices and experiences best current practice of SRE software reliability measurement experience measurement-based analysis of software reliability software fault and failure classification techniques trend analysis in validation and maintenance software reliability and field data analysis software reliability process assessment emerging techniques software reliability prediction metrics software reliability and testing fault-tolerant SRE software reliability using fault trees software reliability process simulation neural networks and software reliability. Appendices: software reliability tools software failure data set repository.

1,068 citations