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2020 – today
- 2024
[c6]Ashwin Prasad Shivarpatna Venkatesh
, Samkutty Sabu, Amir M. Mir, Sofia Reis, Eric Bodden:
The Emergence of Large Language Models in Static Analysis: A First Look through Micro-Benchmarks. FORGE 2024: 35-39- [c5]Ashwin Prasad Shivarpatna Venkatesh, Samkutty Sabu, Jiawei Wang, Amir M. Mir, Li Li, Eric Bodden:
TypeEvalPy: A Micro-benchmarking Framework for Python Type Inference Tools. ICSE Companion 2024: 49-53 - [c4]Amir M. Mir, Mehdi Keshani, Sebastian Proksch:
On the Effectiveness of Machine Learning-based Call Graph Pruning: An Empirical Study. MSR 2024: 457-468 - [i9]Amir M. Mir, Mehdi Keshani, Sebastian Proksch:
On the Effectiveness of Machine Learning-based Call Graph Pruning: An Empirical Study. CoRR abs/2402.07294 (2024) - [i8]Ashwin Prasad Shivarpatna Venkatesh, Samkutty Sabu, Amir M. Mir, Sofia Reis, Eric Bodden:
The Emergence of Large Language Models in Static Analysis: A First Look through Micro-Benchmarks. CoRR abs/2402.17679 (2024) - [i7]Ashwin Prasad Shivarpatna Venkatesh, Rose Sunil, Samkutty Sabu, Amir M. Mir, Sofia Reis, Eric Bodden:
An Empirical Study of Large Language Models for Type and Call Graph Analysis. CoRR abs/2410.00603 (2024) - 2023
- [c3]Amir M. Mir, Mehdi Keshani, Sebastian Proksch:
On the Effect of Transitivity and Granularity on Vulnerability Propagation in the Maven Ecosystem. SANER 2023: 201-211 - [i6]Amir M. Mir, Mehdi Keshani, Sebastian Proksch:
On the Effect of Transitivity and Granularity on Vulnerability Propagation in the Maven Ecosystem. CoRR abs/2301.07972 (2023) - [i5]Ashwin Prasad Shivarpatna Venkatesh, Samkutty Sabu, Jiawei Wang, Amir M. Mir, Li Li, Eric Bodden:
TypeEvalPy: A Micro-benchmarking Framework for Python Type Inference Tools. CoRR abs/2312.16882 (2023) - 2022
- [c2]Amir M. Mir, Evaldas Latoskinas, Sebastian Proksch, Georgios Gousios:
Type4Py: Practical Deep Similarity Learning-Based Type Inference for Python. ICSE 2022: 2241-2252 - 2021
- [c1]Amir M. Mir, Evaldas Latoskinas, Georgios Gousios:
ManyTypes4Py: A Benchmark Python Dataset for Machine Learning-based Type Inference. MSR 2021: 585-589 - [i4]Amir M. Mir, Evaldas Latoskinas, Sebastian Proksch, Georgios Gousios:
Type4Py: Deep Similarity Learning-Based Type Inference for Python. CoRR abs/2101.04470 (2021) - [i3]Amir M. Mir, Evaldas Latoskinas, Georgios Gousios:
ManyTypes4Py: A Benchmark Python Dataset for Machine Learning-based Type Inference. CoRR abs/2104.04706 (2021) - 2020
- [j3]Jalal A. Nasiri, Amir M. Mir:
An enhanced KNN-based twin support vector machine with stable learning rules. Neural Comput. Appl. 32(16): 12949-12969 (2020) - [i2]Amir M. Mir, Mahdi Rahbar, Jalal A. Nasiri:
LIBTwinSVM: A Library for Twin Support Vector Machines. CoRR abs/2001.10073 (2020)
2010 – 2019
- 2019
- [j2]Amir M. Mir, Jalal A. Nasiri:
LightTwinSVM: A Simple and Fast Implementation of Standard Twin Support Vector Machine Classifier. J. Open Source Softw. 4(35): 1252 (2019) - [i1]Amir M. Mir, Jalal A. Nasiri:
An enhanced KNN-based twin support vector machine with stable learning rules. CoRR abs/1906.09443 (2019) - 2018
- [j1]Amir M. Mir, Jalal A. Nasiri:
KNN-based least squares twin support vector machine for pattern classification. Appl. Intell. 48(12): 4551-4564 (2018)
Coauthor Index
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