activity
20192023
most citedFlakyFix: Using Large Language Models for Predicting Flaky Test Fix Categories and Test Code Repair

19 citations · 57 across the 17 of their papers we have counts for

collaborators

21 papers

cs.LG2023

Gray-box Adversarial Attack of Deep Reinforcement Learning-based Trading Agents

Foozhan Ataiefard, Hadi Hemmati

In recent years, deep reinforcement learning (Deep RL) has been successfully implemented as a smart agent in many systems such as complex games, self-driving cars, and chat-bots. O…

cs.SE2023★ 9 cited

Domain Adaptation for Code Model-based Unit Test Case Generation

Jiho Shin, Sepehr Hashtroudi, Hadi Hemmati +1

Recently, deep learning-based test case generation approaches have been proposed to automate the generation of unit test cases. In this study, we leverage Transformer-based code mo…

cs.SE2023

A First Look at Fairness of Machine Learning Based Code Reviewer Recommendation

Mohammad Mahdi Mohajer, Alvine Boaye Belle, Nima Shiri harzevili +5

The fairness of machine learning (ML) approaches is critical to the reliability of modern artificial intelligence systems. Despite extensive study on this topic, the fairness of ML…

cs.SE2023★ 19 cited

FlakyFix: Using Large Language Models for Predicting Flaky Test Fix Categories and Test Code Repair

Sakina Fatima, Hadi Hemmati, Lionel Briand

Flaky tests are problematic because they non-deterministically pass or fail for the same software version under test, causing confusion and wasting development effort. While machin…

cs.SE2023★ 11 cited

A Systematic Literature Review of Explainable AI for Software Engineering

Ahmad Haji Mohammadkhani, Nitin Sai Bommi, Mariem Daboussi +3

Context: In recent years, leveraging machine learning (ML) techniques has become one of the main solutions to tackle many software engineering (SE) tasks, in research studies (ML4S…

cs.LG2022★ 5 cited

MDA: Availability-Aware Federated Learning Client Selection

Amin Eslami Abyane, Steve Drew, Hadi Hemmati

Recently, a new distributed learning scheme called Federated Learning (FL) has been introduced. FL is designed so that server never collects user-owned data meaning it is great at…

cs.LG2022★ 1 cited

Improving the Performance of DNN-based Software Services using Automated Layer Caching

Mohammadamin Abedi, Yanni Iouannou, Pooyan Jamshidi +1

Deep Neural Networks (DNNs) have become an essential component in many application domains including web-based services. A variety of these services require high throughput and (cl…

cs.SE2022★ 2 cited

Test2Vec: An Execution Trace Embedding for Test Case Prioritization

Emad Jabbar, Soheila Zangeneh, Hadi Hemmati +1

Most automated software testing tasks can benefit from the abstract representation of test cases. Traditionally, this is done by encoding test cases based on their code coverage. S…

cs.SE2022★ 1 cited

An Empirical Study on Bug Severity Estimation using Source Code Metrics and Static Analysis

Ehsan Mashhadi, Shaiful Chowdhury, Somayeh Modaberi +2

In the past couple of decades, significant research efforts have been devoted to the prediction of software bugs (i.e., defects). In general, these works leverage a diverse set of…

cs.LG2022★ 1 cited

Towards Understanding Quality Challenges of the Federated Learning for Neural Networks: A First Look from the Lens of Robustness

Amin Eslami Abyane, Derui Zhu, Roberto Souza +2

Federated learning (FL) is a distributed learning paradigm that preserves users' data privacy while leveraging the entire dataset of all participants. In FL, multiple models are tr…

cs.LG2021

Robustness Analysis of Deep Learning Frameworks on Mobile Platforms

Amin Eslami Abyane, Hadi Hemmati

With the recent increase in the computational power of modern mobile devices, machine learning-based heavy tasks such as face detection and speech recognition are now integral part…

cs.SE2021

Applying CodeBERT for Automated Program Repair of Java Simple Bugs

Ehsan Mashhadi, Hadi Hemmati

Software debugging, and program repair are among the most time-consuming and labor-intensive tasks in software engineering that would benefit a lot from automation. In this paper,…

cs.SE2021★ 1 cited

A Search-Based Testing Framework for Deep Neural Networks of Source Code Embedding

Maryam Vahdat Pour, Zhuo Li, Lei Ma +1

Over the past few years, deep neural networks (DNNs) have been continuously expanding their real-world applications for source code processing tasks across the software engineering…

cs.SE2021

GloBug: Using Global Data in Fault Localization

Nima Miryeganeh, Sepehr Hashtroudi, Hadi Hemmati

Fault Localization (FL) is an important first step in software debugging and is mostly manual in the current practice. Many methods have been proposed over years to automate the FL…

cs.SE2021★ 1 cited

A Pragmatic Approach for Hyper-Parameter Tuning in Search-based Test Case Generation

Shayan Zamani, Hadi Hemmati

Search-based test case generation, which is the application of meta-heuristic search for generating test cases, has been studied a lot in the literature, lately. Since, in theory,…

cs.LG2021

Deep State Inference: Toward Behavioral Model Inference of Black-box Software Systems

Foozhan Ataiefard, Mohammad Jafar Mashhadi, Hadi Hemmati +1

Many software engineering tasks, such as testing, and anomaly detection can benefit from the ability to infer a behavioral model of the software.Most existing inference approaches…

cs.LG2020

Hybrid Deep Neural Networks to Infer State Models of Black-Box Systems

Mohammad Jafar Mashhadi, Hadi Hemmati

Inferring behavior model of a running software system is quite useful for several automated software engineering tasks, such as program comprehension, anomaly detection, and testin…

cs.DB2019

An IR-based Approach Towards Automated Integration of Geo-spatial Datasets in Map-based Software Systems

Nima Miryeganeh, Mehdi Amoui, Hadi Hemmati

Data is arguably the most valuable asset of the modern world. In this era, the success of any data-intensive solution relies on the quality of data that drives it. Among vast amoun…

cs.SE2019

Revisiting Hyper-Parameter Tuning for Search-based Test Data Generation

Shayan Zamani, Hadi Hemmati

Search-based software testing (SBST) has been studied a lot in the literature, lately. Since, in theory, the performance of meta-heuristic search methods are highly dependent on th…

cs.SE2019★ 6 cited

Interactive Semi-automated Specification Mining for Debugging: An Experience Report

Mohammad Jafar Mashhadi, Taha R. Siddiqui, Hadi Hemmati +1

Context: Specification mining techniques are typically used to extract the specification of a software in the absence of (up-to-date) specification documents. This is useful for pr…

cs.SE2019

An Empirical Study on Practicality of Specification Mining Algorithms on a Real-world Application

Mohammad Jafar Mashhadi, Hadi Hemmati

Dynamic model inference techniques have been the center of many research projects recently. There are now multiple open source implementations of state-of-the-art algorithms, which…