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Pooyan Jamshidi
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2020 – today
- 2024
- [c68]Md Shahriar Iqbal, Jianhai Su, Lars Kotthoff, Pooyan Jamshidi:
FlexiBO: A Decoupled Cost-Aware Multi-objective Optimization Approach for Deep Neural Networks (Abstract Reprint). AAAI 2024: 22700 - [c67]Kamran Razavi, Saeid Ghafouri, Max Mühlhäuser, Pooyan Jamshidi, Lin Wang:
Sponge: Inference Serving with Dynamic SLOs Using In-Place Vertical Scaling. EuroMLSys@EuroSys 2024: 184-191 - [i55]Claire Le Goues, Sebastian G. Elbaum, David J. Anthony, Z. Berkay Celik, Mauricio Castillo-Effen, Nikolaus Correll, Pooyan Jamshidi, Morgan Quigley, Trenton Tabor, Qi Zhu:
Software Engineering for Robotics: Future Research Directions; Report from the 2023 Workshop on Software Engineering for Robotics. CoRR abs/2401.12317 (2024) - [i54]Md. Abir Hossen, Sonam Kharade, Jason M. O'Kane, Bradley R. Schmerl, David Garlan, Pooyan Jamshidi:
CURE: Simulation-Augmented Auto-Tuning in Robotics. CoRR abs/2402.05399 (2024) - [i53]Kamran Razavi, Saeid Ghafouri, Max Mühlhäuser, Pooyan Jamshidi, Lin Wang:
Sponge: Inference Serving with Dynamic SLOs Using In-Place Vertical Scaling. CoRR abs/2404.00704 (2024) - 2023
- [j32]Md Shahriar Iqbal, Jianhai Su, Lars Kotthoff, Pooyan Jamshidi:
FlexiBO: A Decoupled Cost-Aware Multi-Objective Optimization Approach for Deep Neural Networks. J. Artif. Intell. Res. 77: 645-682 (2023) - [j31]Md. Abir Hossen, Sonam Kharade, Bradley R. Schmerl, Javier Cámara, Jason M. O'Kane, Ellen C. Czaplinski, Katherine A. Dzurilla, David Garlan, Pooyan Jamshidi:
CaRE: Finding Root Causes of Configuration Issues in Highly-Configurable Robots. IEEE Robotics Autom. Lett. 8(7): 4115-4122 (2023) - [c66]Md Shahriar Iqbal, Ziyuan Zhong, Iftakhar Ahmad, Baishakhi Ray, Pooyan Jamshidi:
CAMEO: A Causal Transfer Learning Approach for Performance Optimization of Configurable Computer Systems. SoCC 2023: 555-571 - [c65]Mehran Salmani, Saeid Ghafouri, Alireza Sanaee, Kamran Razavi, Max Mühlhäuser, Joseph Doyle, Pooyan Jamshidi, Mohsen Sharifi:
Reconciling High Accuracy, Cost-Efficiency, and Low Latency of Inference Serving Systems. EuroMLSys@EuroSys 2023: 78-86 - [i52]Md. Abir Hossen, Sonam Kharade, Bradley R. Schmerl, Javier Cámara, Jason M. O'Kane, Ellen C. Czaplinski, Katherine A. Dzurilla, David Garlan, Pooyan Jamshidi:
CaRE: Finding Root Causes of Configuration Issues in Highly-Configurable Robots. CoRR abs/2301.07690 (2023) - [i51]Fatemeh Ghofrani, Mehdi Yaghouti, Pooyan Jamshidi:
On the Role of Contrastive Representation Learning in Adversarial Robustness: An Empirical Study. CoRR abs/2302.02502 (2023) - [i50]Mehran Salmani, Saeid Ghafouri, Alireza Sanaee, Kamran Razavi, Max Mühlhäuser, Joseph Doyle, Pooyan Jamshidi, Mohsen Sharifi:
Reconciling High Accuracy, Cost-Efficiency, and Low Latency of Inference Serving Systems. CoRR abs/2304.10892 (2023) - [i49]Hamed Damirchi, Forest Agostinelli, Pooyan Jamshidi:
Independent Modular Networks. CoRR abs/2306.01316 (2023) - [i48]Md Shahriar Iqbal, Ziyuan Zhong, Iftakhar Ahmad, Baishakhi Ray, Pooyan Jamshidi:
CAMEO: A Causal Transfer Learning Approach for Performance Optimization of Configurable Computer Systems. CoRR abs/2306.07888 (2023) - [i47]Saeid Ghafouri, Kamran Razavi, Mehran Salmani, Alireza Sanaee, Tania Lorido-Botran, Lin Wang, Joseph Doyle, Pooyan Jamshidi:
IPA: Inference Pipeline Adaptation to Achieve High Accuracy and Cost-Efficiency. CoRR abs/2308.12871 (2023) - [i46]Vittorio Cortellessa, J. Andres Diaz-Pace, Daniele Di Pompeo, Sebastian Frank, Pooyan Jamshidi, Michele Tucci, André van Hoorn:
Introducing Interactions in Multi-Objective Optimization of Software Architectures. CoRR abs/2308.15084 (2023) - [i45]Ali Mokhtari, Saeid Ghafouri, Pooyan Jamshidi, Mohsen Amini Salehi:
HEET: A Heterogeneity Measure to Quantify the Difference across Distributed Computing Systems. CoRR abs/2312.03235 (2023) - 2022
- [j30]Danny Weyns, Ilias Gerostathopoulos, Barbora Buhnova, Nicolás Cardozo, Emilia Cioroaica, Ivana Dusparic, Lars Grunske, Pooyan Jamshidi, Christine Julien, Judith Michael, Gabriel A. Moreno, Shiva Nejati, Patrizio Pelliccione, Federico Quin, Genaína Nunes Rodrigues, Bradley R. Schmerl, Marco Vieira, Thomas Vogel, Rebekka Wohlrab:
Guidelines for Artifacts to Support Industry-Relevant Research on Self-Adaptation. ACM SIGSOFT Softw. Eng. Notes 47(4): 18-24 (2022) - [c64]Ali Mokhtari, Md. Abir Hossen, Pooyan Jamshidi, Mohsen Amini Salehi:
FELARE: Fair Scheduling of Machine Learning Tasks on Heterogeneous Edge Systems. CLOUD 2022: 459-468 - [c63]Md Shahriar Iqbal, Rahul Krishna, Mohammad Ali Javidian, Baishakhi Ray, Pooyan Jamshidi:
Unicorn: reasoning about configurable system performance through the lens of causality. EuroSys 2022: 199-217 - [c62]Miguel Velez, Pooyan Jamshidi, Norbert Siegmund, Sven Apel, Christian Kästner:
On Debugging the Performance of Configurable Software Systems: Developer Needs and Tailored Tool Support. ICSE 2022: 1571-1583 - [c61]André Bauer, Mark Leznik, Md Shahriar Iqbal, Daniel Seybold, Igor Trubin, Benjamin Erb, Jörg Domaschka, Pooyan Jamshidi:
SPEC Research - Introducing the Predictive Data Analytics Working Group: Poster Paper. ICPE (Companion) 2022: 13-14 - [c60]Mark Leznik, Md Shahriar Iqbal, Igor Trubin, Arne Lochner, Pooyan Jamshidi, André Bauer:
Change Point Detection for MongoDB Time Series Performance Regression. ICPE (Companion) 2022: 45-48 - [i44]Md Shahriar Iqbal, Rahul Krishna, Mohammad Ali Javidian, Baishakhi Ray, Pooyan Jamshidi:
Unicorn: Reasoning about Configurable System Performance through the lens of Causality. CoRR abs/2201.08413 (2022) - [i43]Rahul Goel, Modar Sulaiman, Kimia Noorbakhsh, Mahdi Sharifi, Rajesh Sharma, Pooyan Jamshidi, Kallol Roy:
Pre-Trained Language Transformers are Universal Image Classifiers. CoRR abs/2201.10182 (2022) - [i42]Miguel Velez, Pooyan Jamshidi, Norbert Siegmund, Sven Apel, Christian Kästner:
On Debugging the Performance of Configurable Software Systems: Developer Needs and Tailored Tool Support. CoRR abs/2203.10356 (2022) - [i41]Ali Mokhtari, Pooyan Jamshidi, Mohsen Amini Salehi:
FELARE: Fair Scheduling of Machine Learning Applications on Heterogeneous Edge Systems. CoRR abs/2206.00065 (2022) - [i40]Danny Weyns, Ilias Gerostathopoulos, Barbora Buhnova, Nicolás Cardozo, Emilia Cioroaica, Ivana Dusparic, Lars Grunske, Pooyan Jamshidi, Christine Julien, Judith Michael, Gabriel A. Moreno, Shiva Nejati, Patrizio Pelliccione, Federico Quin, Genaína Nunes Rodrigues, Bradley R. Schmerl, Marco Vieira, Thomas Vogel, Rebekka Wohlrab:
Guidelines for Artifacts to Support Industry-Relevant Research on Self-Adaptation. CoRR abs/2206.12492 (2022) - [i39]Mohammadamin Abedi, Yanni Iouannou, Pooyan Jamshidi, Hadi Hemmati:
Improving the Performance of DNN-based Software Services using Automated Layer Caching. CoRR abs/2209.08625 (2022) - 2021
- [j29]Nabor Chagas Mendonça, Pooyan Jamshidi, David Garlan, Claus Pahl:
Developing Self-Adaptive Microservice Systems: Challenges and Directions. IEEE Softw. 38(2): 70-79 (2021) - [j28]Rahul Krishna, Vivek Nair, Pooyan Jamshidi, Tim Menzies:
Whence to Learn? Transferring Knowledge in Configurable Systems Using BEETLE. IEEE Trans. Software Eng. 47(12): 2956-2972 (2021) - [c59]Md. Musfiqur Rahman, Ayman Rasheed, Md. Mosaddek Khan, Mohammad Ali Javidian, Pooyan Jamshidi, Md. Mamun-Or-Rashid:
Accelerating Recursive Partition-Based Causal Structure Learning. AAMAS 2021: 1028-1036 - [c58]Mohammad Ali Javidian, Marco Valtorta, Pooyan Jamshidi:
An Order-Independent Algorithm for Learning Chain Graphs. FLAIRS 2021 - [c57]Miguel Velez, Pooyan Jamshidi, Norbert Siegmund, Sven Apel, Christian Kästner:
White-Box Analysis over Machine Learning: Modeling Performance of Configurable Systems. ICSE 2021: 1072-1084 - [i38]Ahmad Banijamali, Pasi Kuvaja, Markku Oivo, Pooyan Jamshidi:
Kuksa*: Self-Adaptive Microservices in Automotive Systems. CoRR abs/2101.03524 (2021) - [i37]Miguel Velez, Pooyan Jamshidi, Norbert Siegmund, Sven Apel, Christian Kästner:
White-Box Analysis over Machine Learning: Modeling Performance of Configurable Systems. CoRR abs/2101.05362 (2021) - [i36]Md. Musfiqur Rahman, Ayman Rasheed, Md. Mosaddek Khan, Mohammad Ali Javidian, Pooyan Jamshidi, Md. Mamun-Or-Rashid:
Accelerating Recursive Partition-Based Causal Structure Learning. CoRR abs/2102.11545 (2021) - [i35]Mohammad Ali Javidian, Om Pandey, Pooyan Jamshidi:
Scalable Causal Transfer Learning. CoRR abs/2103.00139 (2021) - [i34]Kimia Noorbakhsh, Modar Sulaiman, Mahdi Sharifi, Kallol Roy, Pooyan Jamshidi:
Pretrained Language Models are Symbolic Mathematics Solvers too! CoRR abs/2110.03501 (2021) - 2020
- [j27]Miguel Velez, Pooyan Jamshidi, Florian Sattler, Norbert Siegmund, Sven Apel, Christian Kästner:
ConfigCrusher: towards white-box performance analysis for configurable systems. Autom. Softw. Eng. 27(3): 265-300 (2020) - [j26]Mohammad Ali Javidian, Marco Valtorta, Pooyan Jamshidi:
AMP Chain Graphs: Minimal Separators and Structure Learning Algorithms. J. Artif. Intell. Res. 69: 419-470 (2020) - [j25]Antonio Brogi, Antonio Bucchiarone, Rafael Capilla, Pooyan Jamshidi, Maurizio Leotta, Zoltán Ádám Mann, Marina Mongiello, Francesco Nocera:
Ensemble-Based Software Engineering for Modern Computing Platforms. ACM SIGSOFT Softw. Eng. Notes 45(1): 28-30 (2020) - [c56]Catia Trubiani, Aldeida Aleti, Sarah Goodwin, Pooyan Jamshidi, André van Hoorn, Samuel Gratzl:
VisArch: Visualisation of Performance-based Architectural Refactorings. ECSA 2020: 182-190 - [c55]Ahmad Banijamali, Pasi Kuvaja, Markku Oivo, Pooyan Jamshidi:
Kuksa*: Self-adaptive Microservices in Automotive Systems. PROFES 2020: 367-384 - [c54]Claus Pahl, Pooyan Jamshidi, Olaf Zimmermann:
Microservices and Containers. SE 2020: 115-116 - [c53]Mohammad Ali Javidian, Marco Valtorta, Pooyan Jamshidi:
Learning LWF Chain Graphs: A Markov Blanket Discovery Approach. UAI 2020: 1069-1078 - [i33]Ying Meng, Jianhai Su, Jason M. O'Kane, Pooyan Jamshidi:
Ensembles of Many Diverse Weak Defenses can be Strong: Defending Deep Neural Networks Against Adversarial Attacks. CoRR abs/2001.00308 (2020) - [i32]Md Shahriar Iqbal, Jianhai Su, Lars Kotthoff, Pooyan Jamshidi:
FlexiBO: Cost-Aware Multi-Objective Optimization of Deep Neural Networks. CoRR abs/2001.06588 (2020) - [i31]Mohammad Ali Javidian, Marco Valtorta, Pooyan Jamshidi:
AMP Chain Graphs: Minimal Separators and Structure Learning Algorithms. CoRR abs/2002.10870 (2020) - [i30]Mahdi Fahmideh, Pooyan Jamshidi, Fereidoon Shams:
A Procedure for Extracting Software Development Process Patterns. CoRR abs/2004.09380 (2020) - [i29]Mahdi Fahmideh, Mohsen Sharifi, Pooyan Jamshidi, Fereidoon Shams, Hassan Haghighi:
Process Patterns for Service Oriented Development. CoRR abs/2004.09381 (2020) - [i28]Mahdi Fahmideh, Fereidoon Shams, Pooyan Jamshidi:
Toward a Methodological Knowledge for Service-Oriented Development Based on OPEN Meta Model. CoRR abs/2004.10135 (2020) - [i27]Mahdi Fahmideh, Mohsen Sharifi, Pooyan Jamshidi:
Enhancing the OPEN Process Framework with Service-Oriented Method Fragments. CoRR abs/2004.10136 (2020) - [i26]Yang Ren, Gregory Gay, Christian Kästner, Pooyan Jamshidi:
Understanding the Nature of System-Related Issues in Machine Learning Frameworks: An Exploratory Study. CoRR abs/2005.06091 (2020) - [i25]Mohammad Ali Javidian, Marco Valtorta, Pooyan Jamshidi:
Learning LWF Chain Graphs: an Order Independent Algorithm. CoRR abs/2005.14037 (2020) - [i24]Mohammad Ali Javidian, Marco Valtorta, Pooyan Jamshidi:
Learning LWF Chain Graphs: A Markov Blanket Discovery Approach. CoRR abs/2006.00970 (2020) - [i23]Rahul Krishna, Md Shahriar Iqbal, Mohammad Ali Javidian, Baishakhi Ray, Pooyan Jamshidi:
CADET: A Systematic Method For Debugging Misconfigurations using Counterfactual Reasoning. CoRR abs/2010.06061 (2020)
2010 – 2019
- 2019
- [j24]Marcello M. Bersani, Francesco Marconi, Damian A. Tamburri, Andrea Nodari, Pooyan Jamshidi:
Verifying big data topologies by-design : a semi-automated approach. J. Big Data 6: 40 (2019) - [j23]Jonathan Aldrich, David Garlan, Christian Kästner, Claire Le Goues, Anahita Mohseni-Kabir, Ivan Ruchkin, Selva Samuel, Bradley R. Schmerl, Christopher Steven Timperley, Manuela Veloso, Ian Voysey, Joydeep Biswas, Arjun Guha, Jarrett Holtz, Javier Cámara, Pooyan Jamshidi:
Model-Based Adaptation for Robotics Software. IEEE Softw. 36(2): 83-90 (2019) - [j22]Catia Trubiani, Pooyan Jamshidi, Jürgen Cito, Weiyi Shang, Zhen Ming Jiang, Markus Borg:
Performance Issues? Hey DevOps, Mind the Uncertainty. IEEE Softw. 36(2): 110-117 (2019) - [j21]Claus Pahl, Antonio Brogi, Jacopo Soldani, Pooyan Jamshidi:
Cloud Container Technologies: A State-of-the-Art Review. IEEE Trans. Cloud Comput. 7(3): 677-692 (2019) - [c52]Mohammad Ali Javidian, Pooyan Jamshidi, Rasoul Ramezanian:
Avoiding Social Disappointment in Elections. AAMAS 2019: 2039-2041 - [c51]Markos Viggiato, Johnatan Oliveira, Eduardo Figueiredo, Pooyan Jamshidi, Christian Kästner:
Understanding similarities and differences in software development practices across domains. ICGSE 2019: 74-84 - [c50]Pooyan Jamshidi, Javier Cámara, Bradley R. Schmerl, Christian Kästner, David Garlan:
Machine learning meets quantitative planning: enabling self-adaptation in autonomous robots. SEAMS@ICSE 2019: 39-50 - [c49]Markos Viggiato, Johnatan Oliveira, Eduardo Figueiredo, Pooyan Jamshidi, Christian Kästner:
How Do Code Changes Evolve in Different Platforms? A Mining-Based Investigation. ICSME 2019: 218-222 - [c48]Md Shahriar Iqbal, Lars Kotthoff, Pooyan Jamshidi:
Transfer Learning for Performance Modeling of Deep Neural Network Systems. OpML 2019: 43-46 - [c47]Ahmad Banijamali, Pooyan Jamshidi, Pasi Kuvaja, Markku Oivo:
Kuksa: A Cloud-Native Architecture for Enabling Continuous Delivery in the Automotive Domain. PROFES 2019: 455-472 - [c46]Mohammad Ali Javidian, Marco Valtorta, Pooyan Jamshidi:
Order-Independent Structure Learning of Multivariate Regression Chain Graphs. SUM 2019: 324-338 - [c45]Cor-Paul Bezemer, Simon Eismann, Vincenzo Ferme, Johannes Grohmann, Robert Heinrich, Pooyan Jamshidi, Weiyi Shang, André van Hoorn, Mónica Villavicencio, Jürgen Walter, Felix Willnecker:
How is Performance Addressed in DevOps? ICPE 2019: 45-50 - [e1]Francesco Nocera, Antonio Bucchiarone, Marina Mongiello, Rafael Capilla, Maurizio Leotta, Zoltán Ádám Mann, Pooyan Jamshidi, Antonio Brogi:
Proceedings of the 2nd ACM SIGSOFT International Workshop on Ensemble-Based Software Engineering for Modern Computing Platforms, EnSEmble@ESEC/SIGSOFT FSE 2019, Tallinn, Estonia, August 26, 2019. ACM 2019, ISBN 978-1-4503-6853-7 [contents] - [i22]Mohammad Ali Javidian, Pooyan Jamshidi, Marco Valtorta:
Transfer Learning for Performance Modeling of Configurable Systems: A Causal Analysis. CoRR abs/1902.10119 (2019) - [i21]Pooyan Jamshidi, Javier Cámara, Bradley R. Schmerl, Christian Kästner, David Garlan:
Machine Learning Meets Quantitative Planning: Enabling Self-Adaptation in Autonomous Robots. CoRR abs/1903.03920 (2019) - [i20]Md Shahriar Iqbal, Lars Kotthoff, Pooyan Jamshidi:
Transfer Learning for Performance Modeling of Deep Neural Network Systems. CoRR abs/1904.02838 (2019) - [i19]Miguel Velez, Pooyan Jamshidi, Florian Sattler, Norbert Siegmund, Sven Apel, Christian Kästner:
ConfigCrusher: White-Box Performance Analysis for Configurable Systems. CoRR abs/1905.02066 (2019) - [i18]Aaron M. Roth, Nicholay Topin, Pooyan Jamshidi, Manuela Veloso:
Conservative Q-Improvement: Reinforcement Learning for an Interpretable Decision-Tree Policy. CoRR abs/1907.01180 (2019) - [i17]Mohammad Ali Javidian, Marco Valtorta, Pooyan Jamshidi:
Order-Independent Structure Learning of Multivariate Regression Chain Graphs. CoRR abs/1910.01067 (2019) - [i16]Nabor C. Mendonça, Pooyan Jamshidi, David Garlan, Claus Pahl:
Developing Self-Adaptive Microservice Systems: Challenges and Directions. CoRR abs/1910.07660 (2019) - [i15]Ahmad Banijamali, Pooyan Jamshidi, Pasi Kuvaja, Markku Oivo:
Kuksa: A Cloud-Native Architecture for Enabling Continuous Delivery in the Automotive Domain. CoRR abs/1910.10190 (2019) - [i14]Markos Viggiato, Johnatan Oliveira, Eduardo Figueiredo, Pooyan Jamshidi, Christian Kästner:
How Do Code Changes Evolve in Different Platforms? A Mining-based Investigation. CoRR abs/1910.11433 (2019) - [i13]Rahul Krishna, Vivek Nair, Pooyan Jamshidi, Tim Menzies:
Whence to Learn? Transferring Knowledge in Configurable Systems using BEETLE. CoRR abs/1911.01817 (2019) - 2018
- [j20]Aldeida Aleti, Catia Trubiani, André van Hoorn, Pooyan Jamshidi:
An efficient method for uncertainty propagation in robust software performance estimation. J. Syst. Softw. 138: 222-235 (2018) - [j19]Pooyan Jamshidi, Claus Pahl, Nabor C. Mendonça, James Lewis, Stefan Tilkov:
Microservices: The Journey So Far and Challenges Ahead. IEEE Softw. 35(3): 24-35 (2018) - [j18]Armin Balalaie, Abbas Heydarnoori, Pooyan Jamshidi, Damian A. Tamburri, Theo Lynn:
Microservices migration patterns. Softw. Pract. Exp. 48(11): 2019-2042 (2018) - [j17]Frank Fowley, Claus Pahl, Pooyan Jamshidi, Daren Fang, Xiaodong Liu:
A Classification and Comparison Framework for Cloud Service Brokerage Architectures. IEEE Trans. Cloud Comput. 6(2): 358-371 (2018) - [j16]Claus Pahl, Pooyan Jamshidi, Olaf Zimmermann:
Architectural Principles for Cloud Software. ACM Trans. Internet Techn. 18(2): 17:1-17:23 (2018) - [c44]Allan Mori, Gustavo Vale, Markos Viggiato, Johnatan Oliveira, Eduardo Figueiredo, Elder Cirilo, Pooyan Jamshidi, Christian Kästner:
Evaluating domain-specific metric thresholds: an empirical study. TechDebt@ICSE 2018: 41-50 - [c43]Pooyan Jamshidi, Miguel Velez, Christian Kästner, Norbert Siegmund:
Learning to sample: exploiting similarities across environments to learn performance models for configurable systems. ESEC/SIGSOFT FSE 2018: 71-82 - [i12]Aldeida Aleti, Catia Trubiani, André van Hoorn, Pooyan Jamshidi:
An Efficient Method for Uncertainty Propagation in Robust Software Performance Estimation. CoRR abs/1801.04644 (2018) - [i11]Vivek Nair, Rahul Krishna, Tim Menzies, Pooyan Jamshidi:
Transfer Learning with Bellwethers to find Good Configurations. CoRR abs/1803.03900 (2018) - [i10]Cor-Paul Bezemer, Simon Eismann, Vincenzo Ferme, Johannes Grohmann, Robert Heinrich, Pooyan Jamshidi, Weiyi Shang, André van Hoorn, Mónica Villavicencio, Jürgen Walter, Felix Willnecker:
How is Performance Addressed in DevOps? A Survey on Industrial Practices. CoRR abs/1808.06915 (2018) - 2017
- [j15]Claus Pahl, Pooyan Jamshidi, Danny Weyns:
Cloud architecture continuity: Change models and change rules for sustainable cloud software architectures. J. Softw. Evol. Process. 29(2) (2017) - [j14]Pooyan Jamshidi, Claus Pahl, Nabor C. Mendonça:
Pattern-based multi-cloud architecture migration. Softw. Pract. Exp. 47(9): 1159-1184 (2017) - [j13]Antonio Filieri, Martina Maggio, Konstantinos Angelopoulos, Nicolás D'Ippolito, Ilias Gerostathopoulos, Andreas Berndt Hempel, Henry Hoffmann, Pooyan Jamshidi, Evangelia Kalyvianaki, Cristian Klein, Filip Krikava, Sasa Misailovic, Alessandro Vittorio Papadopoulos, Suprio Ray, Amir Molzam Sharifloo, Stepan Shevtsov, Mateusz Ujma, Thomas Vogel:
Control Strategies for Self-Adaptive Software Systems. ACM Trans. Auton. Adapt. Syst. 11(4): 24:1-24:31 (2017) - [c42]Hamid Arabnejad, Claus Pahl, Pooyan Jamshidi, Giovani Estrada:
A Comparison of Reinforcement Learning Techniques for Fuzzy Cloud Auto-Scaling. CCGrid 2017: 64-73 - [c41]Carlos M. Aderaldo, Nabor C. Mendonça, Claus Pahl, Pooyan Jamshidi:
Benchmark Requirements for Microservices Architecture Research. ECASE@ICSE 2017: 8-13 - [c40]Pooyan Jamshidi, Miguel Velez, Christian Kästner, Norbert Siegmund, Prasad Kawthekar:
Transfer Learning for Improving Model Predictions in Highly Configurable Software. SEAMS@ICSE 2017: 31-41 - [c39]Pooyan Jamshidi, Norbert Siegmund, Miguel Velez, Christian Kästner, Akshay Patel, Yuvraj Agarwal:
Transfer learning for performance modeling of configurable systems: an exploratory analysis. ASE 2017: 497-508 - [i9]Pooyan Jamshidi, Miguel Velez, Christian Kästner, Norbert Siegmund, Prasad Kawthekar:
Transfer Learning for Improving Model Predictions in Highly Configurable Software. CoRR abs/1704.00234 (2017) - [i8]Hamid Arabnejad, Claus Pahl, Pooyan Jamshidi, Giovani Estrada:
A Comparison of Reinforcement Learning Techniques for Fuzzy Cloud Auto-Scaling. CoRR abs/1705.07114 (2017) - [i7]Pooyan Jamshidi, Norbert Siegmund, Miguel Velez, Christian Kästner, Akshay Patel, Yuvraj Agarwal:
Transfer Learning for Performance Modeling of Configurable Systems: An Exploratory Analysis. CoRR abs/1709.02280 (2017) - [i6]André van Hoorn, Pooyan Jamshidi, Philipp Leitner, Ingo Weber:
Report from GI-Dagstuhl Seminar 16394: Software Performance Engineering in the DevOps World. CoRR abs/1709.08951 (2017) - 2016
- [j12]Pooyan Jamshidi, Claus Pahl, Nabor C. Mendonça:
Managing Uncertainty in Autonomic Cloud Elasticity Controllers. IEEE Cloud Comput. 3(3): 50-60 (2016) - [j11]Daren Fang, Xiaodong Liu, Imed Romdhani, Pooyan Jamshidi, Claus Pahl:
An agility-oriented and fuzziness-embedded semantic model for collaborative cloud service search, retrieval and recommendation. Future Gener. Comput. Syst. 56: 11-26 (2016) - [j10]Soodeh Farokhi, Pooyan Jamshidi, Ewnetu Bayuh Lakew, Ivona Brandic, Erik Elmroth:
A hybrid cloud controller for vertical memory elasticity: A control-theoretic approach. Future Gener. Comput. Syst. 65: 57-72 (2016) - [j9]Alireza Khoshkbarforoushha, Pooyan Jamshidi, Mahdi Fahmideh Gholami, Lizhe Wang, Rajiv Ranjan:
Metrics for BPEL Process Reusability Analysis in a Workflow System. IEEE Syst. J. 10(1): 36-45 (2016) - [j8]Armin Balalaie, Abbas Heydarnoori, Pooyan Jamshidi:
Microservices Architecture Enables DevOps: Migration to a Cloud-Native Architecture. IEEE Softw. 33(3): 42-52 (2016) - [c38]Claus Pahl, Pooyan Jamshidi:
Microservices: A Systematic Mapping Study. CLOSER (1) 2016: 137-146 - [c37]Hamid Arabnejad, Pooyan Jamshidi, Giovani Estrada, Nabil El Ioini, Claus Pahl:
An Auto-Scaling Cloud Controller Using Fuzzy Q-Learning - Implementation in OpenStack. ESOCC 2016: 152-167 - [c36]Elisabetta Di Nitto, Pooyan Jamshidi, Michele Guerriero, Ilias Spais, Damian A. Tamburri:
A software architecture framework for quality-aware DevOps. QUDOS@ISSTA 2016: 12-17 - [c35]Pooyan Jamshidi, Giuliano Casale:
An Uncertainty-Aware Approach to Optimal Configuration of Stream Processing Systems. MASCOTS 2016: 39-48 - [c34]Pooyan Jamshidi, Amir Molzam Sharifloo, Claus Pahl, Hamid Arabnejad, Andreas Metzger, Giovani Estrada:
Fuzzy Self-Learning Controllers for Elasticity Management in Dynamic Cloud Architectures. QoSA 2016: 70-79 - [c33]