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2020 – today
- 2024
[j8]Mahshid Helali Moghadam, Markus Borg, Mehrdad Saadatmand, Seyed Jalaleddin Mousavirad
, Markus Bohlin, Björn Lisper:
Machine learning testing in an ADAS case study using simulation-integrated bio-inspired search-based testing. J. Softw. Evol. Process. 36(5) (2024)- [c22]Alireza Dehlaghi-Ghadim, Niclas Ericsson, Lars-Göran Magnusson, Mats Eriksson, Mahshid Helali Moghadam, Ali Balador, Hans Hansson:
Using Decision Support to Fortify Industrial Control System Against Cyberattacks. ETFA 2024: 1-4 - [c21]Arman Sheikhani, Ervin Agic, Mahshid Helali Moghadam, Juan Carlos Andresen, Anders Vesterberg:
Lithium-Ion Battery SOH Forecasting: From Deep Learning Augmented by Explainability to Lightweight Machine Learning Models. ETFA 2024: 1-4 - [c20]Seyed Jalaleddin Mousavirad, Diego Oliva, Gerald Schaefer, Mahshid Helali Moghadam, Mohammed El-Abd:
A Novel Two-Level Clustering-Based Differential Evolution Algorithm for Training Neural Networks. EvoApplications@EvoStar 2024: 259-272 - [i12]Mahshid Helali Moghadam, Mateusz Rzymowski, Lukasz Kulas:
Enabling Smart Retrofitting and Performance Anomaly Detection for a Sensorized Vessel: A Maritime Industry Experience. CoRR abs/2401.00112 (2024) - 2023
- [j7]Alireza Dehlaghi-Ghadim, Mahshid Helali Moghadam, Ali Balador, Hans Hansson:
Anomaly Detection Dataset for Industrial Control Systems. IEEE Access 11: 107982-107996 (2023) - [j6]Alireza Dehlaghi-Ghadim, Ali Balador, Mahshid Helali Moghadam, Hans Hansson, Mauro Conti:
ICSSIM - A framework for building industrial control systems security testbeds. Comput. Ind. 148: 103906 (2023) - [j5]Seyed Jalaleddin Mousavirad, Gerald Schaefer, Huiyu Zhou, Mahshid Helali Moghadam:
How effective are current population-based metaheuristic algorithms for variance-based multi-level image thresholding? Knowl. Based Syst. 272: 110587 (2023) - [j4]Markus Borg, Jens Henriksson, Kasper Socha, Olof Lennartsson, Elias Sonnsjö Lönegren, Thanh Bui, Piotr Tomaszewski, Sankar Raman Sathyamoorthy, Sebastian Brink, Mahshid Helali Moghadam:
Ergo, SMIRK is safe: a safety case for a machine learning component in a pedestrian automatic emergency brake system. Softw. Qual. J. 31(2): 335-403 (2023) - [i11]Muhammad Abbas, Ali Hamayouni, Mahshid Helali Moghadam, Mehrdad Saadatmand, Per Erik Strandberg:
Making Sense of Failure Logs in an Industrial DevOps Environment. CoRR abs/2301.03450 (2023) - [i10]Alireza Dehlaghi-Ghadim, Mahshid Helali Moghadam, Ali Balador, Hans Hansson:
Anomaly Detection Dataset for Industrial Control Systems. CoRR abs/2305.09678 (2023) - 2022
- [b1]Mahshid Helali Moghadam:
Intelligence-Driven Software Performance Assurance. Mälardalen University, Sweden, 2022 - [j3]Mahshid Helali Moghadam, Mehrdad Saadatmand, Markus Borg, Markus Bohlin, Björn Lisper:
An autonomous performance testing framework using self-adaptive fuzzy reinforcement learning. Softw. Qual. J. 30(1): 127-159 (2022) - [c19]Seyed Jalaleddin Mousavirad, Mahshid Helali Moghadam, Mehrdad Saadatmand, Ripon K. Chakrabortty, Gerald Schaefer, Diego Oliva:
RWS-L-SHADE: An Effective L-SHADE Algorithm Incorporation Roulette Wheel Selection Strategy for Numerical Optimisation. EvoApplications 2022: 255-268 - [i9]Mahshid Helali Moghadam, Markus Borg, Mehrdad Saadatmand, Seyed Jalaleddin Mousavirad, Markus Bohlin, Björn Lisper:
Machine Learning Testing in an ADAS Case Study Using Simulation-Integrated Bio-Inspired Search-Based Testing. CoRR abs/2203.12026 (2022) - [i8]Markus Borg, Jens Henriksson, Kasper Socha, Olof Lennartsson, Elias Sonnsjö Lönegren, Thanh Bui, Piotr Tomaszewski, Sankar Raman Sathyamoorthy, Sebastian Brink, Mahshid Helali Moghadam:
Ergo, SMIRK is Safe: A Safety Case for a Machine Learning Component in a Pedestrian Automatic Emergency Brake System. CoRR abs/2204.07874 (2022) - 2021
- [j2]Marjan Sirjani, Luciana Provenzano, Sara Abbaspour Asadollah, Mahshid Helali Moghadam, Mehrdad Saadatmand:
Towards a Verification-Driven Iterative Development of Software for Safety-Critical Cyber-Physical Systems. J. Internet Serv. Appl. 12(1): 2 (2021) - [c18]Hamid Ebadi, Mahshid Helali Moghadam, Markus Borg, Gregory Gay, Afonso Fontes, Kasper Socha:
Efficient and Effective Generation of Test Cases for Pedestrian Detection - Search-based Software Testing of Baidu Apollo in SVL. AITest 2021: 103-110 - [c17]Ali Sedaghatbaf, Mahshid Helali Moghadam, Mehrdad Saadatmand:
Automated Performance Testing Based on Active Deep Learning. AST@ICSE 2021: 11-19 - [c16]Mahshid Helali Moghadam, Golrokh Hamidi, Markus Borg, Mehrdad Saadatmand, Markus Bohlin, Björn Lisper, Pasqualina Potena:
Performance Testing Using a Smart Reinforcement Learning-Driven Test Agent. CEC 2021: 2385-2394 - [c15]Seyed Jalaleddin Mousavirad, Gerald Schaefer, Mahshid Helali Moghadam, Mehrdad Saadatmand, Mahdi Pedram:
A population-based automatic clustering algorithm for image segmentation. GECCO Companion 2021: 1931-1936 - [c14]Seyed Vahid Moravvej, Seyed Jalaleddin Mousavirad, Mahshid Helali Moghadam, Mehrdad Saadatmand:
An LSTM-Based Plagiarism Detection via Attention Mechanism and a Population-Based Approach for Pre-training Parameters with Imbalanced Classes. ICONIP (3) 2021: 690-701 - [c13]Mahshid Helali Moghadam, Markus Borg, Seyed Jalaleddin Mousavirad:
Deeper at the SBST 2021 Tool Competition: ADAS Testing Using Multi-Objective Search. SBST@ICSE 2021: 40-41 - [c12]Seyed Jalaleddin Mousavirad, Gerald Schaefer, Iakov Korovin, Mahshid Helali Moghadam, Mehrdad Saadatmand, Mahdi Pedram:
An Enhanced Differential Evolution Algorithm Using a Novel Clustering-based Mutation Operator. SMC 2021: 176-181 - [c11]Seyed Jalaleddin Mousavirad, Gerald Schaefer, Iakov Korovin, Diego Oliva, Mahshid Helali Moghadam, Mehrdad Saadatmand:
HMS-OS: Improving the Human Mental Search Optimisation Algorithm by Grouping in both Search and Objective Space. SSCI 2021: 1-7 - [i7]Ali Sedaghatbaf, Mahshid Helali Moghadam, Mehrdad Saadatmand:
Automated Performance Testing Based on Active Deep Learning. CoRR abs/2104.02102 (2021) - [i6]Mahshid Helali Moghadam, Golrokh Hamidi, Markus Borg, Mehrdad Saadatmand, Markus Bohlin, Björn Lisper, Pasqualina Potena:
Performance Testing Using a Smart Reinforcement Learning-Driven Test Agent. CoRR abs/2104.12893 (2021) - [i5]Hamid Ebabi, Mahshid Helali Moghadam, Markus Borg, Gregory Gay, Afonso Fontes, Kasper Socha:
Efficient and Effective Generation of Test Cases for Pedestrian Detection - Search-based Software Testing of Baidu Apollo in SVL. CoRR abs/2109.07960 (2021) - [i4]Seyed Jalaleddin Mousavirad, Gerald Schaefer, Iakov Korovin, Mahshid Helali Moghadam, Mehrdad Saadatmand, Mahdi Pedram:
An Enhanced Differential Evolution Algorithm Using a Novel Clustering-based Mutation Operator. CoRR abs/2109.09351 (2021) - [i3]Seyed Vahid Moravvej, Seyed Jalaleddin Mousavirad, Mahshid Helali Moghadam, Mehrdad Saadatmand:
An LSTM-based Plagiarism Detection via Attention Mechanism and a Population-based Approach for Pre-Training Parameters with imbalanced Classes. CoRR abs/2110.08771 (2021) - [i2]Seyed Jalaleddin Mousavirad, Gerald Schaefer, Iakov Korovin, Diego Oliva, Mahshid Helali Moghadam, Mehrdad Saadatmand:
HMS-OS: Improving the Human Mental Search Optimisation Algorithm by Grouping in both Search and Objective Space. CoRR abs/2111.10188 (2021) - 2020
- [c10]Mahshid Helali Moghadam, Mehrdad Saadatmand, Markus Borg, Markus Bohlin, Björn Lisper:
Poster: Performance Testing Driven by Reinforcement Learning. ICST 2020: 402-405 - [c9]Marjan Sirjani, Luciana Provenzano, Sara Abbaspour Asadollah, Mahshid Helali Moghadam:
From Requirements to Verifiable Executable Models Using Rebeca. SEFM 2020: 67-86
2010 – 2019
- 2019
- [c8]Mahshid Helali Moghadam, Mehrdad Saadatmand, Markus Borg, Markus Bohlin, Björn Lisper:
Machine Learning to Guide Performance Testing: An Autonomous Test Framework. ICST Workshops 2019: 164-167 - [c7]Mahshid Helali Moghadam:
Machine learning-assisted performance testing. ESEC/SIGSOFT FSE 2019: 1187-1189 - [i1]Mahshid Helali Moghadam, Mehrdad Saadatmand, Markus Borg, Markus Bohlin, Björn Lisper:
An Autonomous Performance Testing Framework using Self-Adaptive Fuzzy Reinforcement Learning. CoRR abs/1908.06900 (2019) - 2018
- [j1]Mahshid Helali Moghadam, Seyed Morteza Babamir:
Makespan reduction for dynamic workloads in cluster-based data grids using reinforcement-learning based scheduling. J. Comput. Sci. 24: 402-412 (2018) - [c6]Mahshid Helali Moghadam, Mehrdad Saadatmand, Markus Borg, Markus Bohlin, Björn Lisper:
Learning-based response time analysis in real-time embedded systems: a simulation-based approach. SQUADE@ICSE 2018: 21-24 - [c5]Mahshid Helali Moghadam, Mehrdad Saadatmand, Markus Borg, Markus Bohlin, Björn Lisper:
Adaptive runtime response time control in PLC-based real-time systems using reinforcement learning. SEAMS@ICSE 2018: 217-223 - [c4]Mahshid Helali Moghadam, Mehrdad Saadatmand, Markus Borg, Markus Bohlin, Björn Lisper:
Learning-Based Self-Adaptive Assurance of Timing Properties in a Real-Time Embedded System. ICST Workshops 2018: 77-80 - 2017
- [c3]Olumuyiwa Ibidunmoye, Mahshid Helali Moghadam, Ewnetu Bayuh Lakew, Erik Elmroth:
Adaptive Service Performance Control using Cooperative Fuzzy Reinforcement Learning in Virtualized Environments. UCC 2017: 19-28 - 2016
- [c2]Foroogh Sedighi, Mahshid Helali Moghadam:
Integration of heterogeneous data sources in smart grid based on summary schema model. IIT 2016: 1-6 - [c1]Mahshid Helali Moghadam, Seyed Morteza Babamir, Meghdad Mirabi:
A Multi-Objective Optimization Model for Data-Intensive Workflow Scheduling in Data Grids. LCN Workshops 2016: 25-33
Coauthor Index
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