75 citations · 110 across the 16 of their papers we have counts for
17 papers
Integrated Imputation-Classification for Supervised Learning with Missing Data
Yue Liu, Ben Liang, Ali Tizghadam +1
We study supervised classification problems with missing feature values. Existing approaches often decouple imputation from classification, producing imputations that may be plausi…
An Empirical Study on the Amount of Changes Required for Merge Request Acceptance
Samah Kansab, Mohammed Sayagh, Francis Bordeleau +1
Code review (CR) is essential to software development, helping ensure that new code is properly integrated. However, the CR process often involves significant effort, including cod…
Efficient Detection of Intermittent Job Failures Using Few-Shot Learning
Henri Aïdasso, Francis Bordeleau, Ali Tizghadam
One of the main challenges developers face in the use of continuous integration (CI) and deployment pipelines is the occurrence of intermittent job failures, which result from unex…
On The Impact of Merge Request Deviations on Code Review Practices
Samah Kansab, Francis Bordeleau, Ali Tizghadam
Code review is a key practice in software engineering, ensuring quality and collaboration. However, industrial Merge Request (MR) workflows often deviate from standardized review p…
Analyzing DevOps Practices Through Merge Request Data: A Case Study in Networking Software Company
Samah Kansab, Matthieu Hanania, Francis Bordeleau +1
DevOps integrates collaboration, automation, and continuous improvement, enhancing agility, reducing time to market, and ensuring consistent software releases. A key component of t…
Towards Build Optimization Using Digital Twins
Henri Aïdasso, Francis Bordeleau, Ali Tizghadam
Despite the indisputable benefits of Continuous Integration (CI) pipelines (or builds), CI still presents significant challenges regarding long durations, failures, and flakiness.…
On the Diagnosis of Flaky Job Failures: Understanding and Prioritizing Failure Categories
Henri Aïdasso, Francis Bordeleau, Ali Tizghadam
The continuous delivery of modern software requires the execution of many automated pipeline jobs. These jobs ensure the frequent release of new software versions while detecting c…
Intent Assurance using LLMs guided by Intent Drift
Kristina Dzeparoska, Ali Tizghadam, Alberto Leon-Garcia
Intent-Based Networking (IBN) presents a paradigm shift for network management, by promising to align intents and business objectives with network operations--in an automated manne…
LLM-based policy generation for intent-based management of applications
Kristina Dzeparoska, Jieyu Lin, Ali Tizghadam +1
Automated management requires decomposing high-level user requests, such as intents, to an abstraction that the system can understand and execute. This is challenging because even…
Improving Knowledge Distillation with Teacher's Explanation
Sayantan Chowdhury, Ben Liang, Ali Tizghadam +1
Knowledge distillation (KD) improves the performance of a low-complexity student model with the help of a more powerful teacher. The teacher in KD is a black-box model, imparting k…
Generative Adversarial Classification Network with Application to Network Traffic Classification
Rozhina Ghanavi, Ben Liang, Ali Tizghadam
Large datasets in machine learning often contain missing data, which necessitates the imputation of missing data values. In this work, we are motivated by network traffic classific…
Flow-Packet Hybrid Traffic Classification for Class-Aware Network Routing
Sayantan Chowdhury, Ben Liang, Ali Tizghadam +1
Network traffic classification using machine learning techniques has been widely studied. Most existing schemes classify entire traffic flows, but there are major limitations to th…
Queue-Learning: A Reinforcement Learning Approach for Providing Quality of Service
Majid Raeis, Ali Tizghadam, Alberto Leon-Garcia
End-to-end delay is a critical attribute of quality of service (QoS) in application domains such as cloud computing and computer networks. This metric is particularly important in…
Reinforcement Learning-based Admission Control in Delay-sensitive Service Systems
Majid Raeis, Ali Tizghadam, Alberto Leon-Garcia
Ensuring quality of service (QoS) guarantees in service systems is a challenging task, particularly when the system is composed of more fine-grained services, such as service funct…
Probabilistic Bounds on the End-to-End Delay of Service Function Chains using Deep MDN
Majid Raeis, Ali Tizghadam, Alberto Leon-Garcia
Ensuring the conformance of a service system's end-to-end delay to service level agreement (SLA) constraints is a challenging task that requires statistical measures beyond the ave…
Real-Time Prediction of Delay Distribution in Service Systems using Mixture Density Networks
Majid Raeis, Ali Tizghadam, Alberto Leon-Garcia
Motivated by interest in providing more efficient services in customer service systems, we use statistical learning methods and delay history information to predict the conditional…
Elascale: Autoscaling and Monitoring as a Service
Hamzeh Khazaei, Rajsimman Ravichandiran, Byungchul Park +3
Auto-scalability has become an evident feature for cloud software systems including but not limited to big data and IoT applications. Cloud application providers now are in full co…