Akbar Siami Namin
Akbar Siami Namin
Associate Professor of Computer Science - Texas Tech University
Verifierad e-postadress på ttu.edu - Startsida
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Using mutation analysis for assessing and comparing testing coverage criteria
JH Andrews, LC Briand, Y Labiche, AS Namin
IEEE Transactions on Software Engineering 32 (8), 608-624, 2006
5342006
Sufficient mutation operators for measuring test effectiveness
AS Namin, J Andrews, D Murdoch
2008 ACM/IEEE 30th International Conference on Software Engineering, 351-360, 2008
2202008
A comparison of ARIMA and LSTM in forecasting time series
S Siami-Namini, N Tavakoli, AS Namin
2018 17th IEEE International Conference on Machine Learning and Applications …, 2018
1862018
The influence of size and coverage on test suite effectiveness
AS Namin, JH Andrews
Proceedings of the eighteenth international symposium on Software testing …, 2009
1732009
Forecasting economics and financial time series: ARIMA vs. LSTM
S Siami-Namini, AS Namin
arXiv preprint arXiv:1803.06386, 2018
1282018
The use of mutation in testing experiments and its sensitivity to external threats
AS Namin, S Kakarla
Proceedings of the 2011 International Symposium on Software Testing and …, 2011
772011
The performance of LSTM and BiLSTM in forecasting time series
S Siami-Namini, N Tavakoli, AS Namin
2019 IEEE International Conference on Big Data (Big Data), 3285-3292, 2019
502019
Predicting vulnerable software components through n-gram analysis and statistical feature selection
Y Pang, X Xue, AS Namin
2015 IEEE 14th International Conference on Machine Learning and Applications …, 2015
452015
Finding sufficient mutation operators via variable reduction
AS Namin, JH Andrews
Second Workshop on Mutation Analysis (Mutation 2006-ISSRE Workshops 2006), 5-5, 2006
432006
A survey on the moving target defense strategies: An architectural perspective
J Zheng, AS Namin
Journal of Computer Science and Technology 34 (1), 207-233, 2019
422019
Trimming test suites with coincidentally correct test cases for enhancing fault localizations
X Xue, Y Pang, AS Namin
2014 IEEE 38th Annual Computer Software and Applications Conference, 239-244, 2014
322014
Prioritizing mutation operators based on importance sampling
M Sridharan, AS Namin
2010 IEEE 21st International Symposium on Software Reliability Engineering …, 2010
302010
On sufficiency of mutants
AS Namin, JH Andrews
29th International Conference on Software Engineering (ICSE'07 Companion), 73-74, 2007
302007
The core cyber-defense knowledge, skills, and abilities that cybersecurity students should learn in school: Results from interviews with cybersecurity professionals
KS Jones, AS Namin, ME Armstrong
ACM Transactions on Computing Education (TOCE) 18 (3), 1-12, 2018
292018
Forecasting economic and financial time series: Arima vs. LSTM
SS Namin, AS Namin
Machine Learning, 1-19, 2018
282018
Identifying effective test cases through k-means clustering for enhancing regression testing
Y Pang, X Xue, AS Namin
2013 12th International Conference on Machine Learning and Applications 2, 78-83, 2013
282013
Detecting phishing websites through deep reinforcement learning
M Chatterjee, AS Namin
2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC …, 2019
252019
Internet use and cybersecurity concerns of individuals with visual impairments
FA Inan, AS Namin, RL Pogrund, KS Jones
Journal of Educational Technology & Society 19 (1), 28-40, 2016
242016
Can machine/deep learning classifiers detect zero-day malware with high accuracy?
F Abri, S Siami-Namini, MA Khanghah, FM Soltani, AS Namin
2019 IEEE international conference on big data (Big Data), 3252-3259, 2019
232019
A comparative analysis of forecasting financial time series using arima, lstm, and bilstm
S Siami-Namini, N Tavakoli, AS Namin
arXiv preprint arXiv:1911.09512, 2019
232019
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Artiklar 1–20