34 citations · 74 across the 35 of their papers we have counts for
39 papers
Synthesizing Behavioural Models of CPS Using Automata Learning and Statistical Machine Learning
Negin Ayoughi, Baharin A. Jodat, Armina Faghihi +3
Inferring behavioural models from system executions is essential for supporting formal verification and analysis of complex, heterogeneous cyber-physical systems (CPS). Automata le…
Question Answering for Diagram-Rich Technical Meeting Videos
Zhuoran Xu, Jia Li, Dayuan Tan +5
Software engineering increasingly relies on asynchronous communication artifacts, including recorded meetings where stakeholders discuss concerns, rationale, and decisions. These m…
LLM-Based Discovery of Latent Requirements from Stakeholder Conversations: Preliminary Results from Industry
Mithila Sivakumar, Martin Lochner, Shiva Nejati +1
Stakeholder interviews are an important source of information for requirements elicitation, yet many relevant requirements remain implicit in such conversations. Stakeholders frequ…
Agentic Persona Generation with Critique-Refinement: An Industrial Evaluation
Mohammad Hossein Amini, David Dewar, Shiva Nejati +1
Personas are widely used in software engineering to support requirements elicitation, design, and validation, but their manual creation is costly, time-consuming, and hard to scale…
Genetic Programming for Self-Adaptive Auto-Scaling of Microservices
Jia Li, Mehrdad Sabetzadeh, Shiva Nejati
Microservice architecture is widely adopted in modern systems, where auto-scaling is critical for satisfying service-level objectives (SLOs). However, determining optimal scaling f…
Question Answering for Multi-Release Systems: A Case Study at Ciena
Parham Khamsepour, Mark Cole, Ish Ashraf +3
Companies regularly have to contend with multi-release systems, where several versions of the same software are in operation simultaneously. Question answering over documents from…
DSL or Code? Evaluating the Quality of LLM-Generated Algebraic Specifications: A Case Study in Optimization at Kinaxis
Negin Ayoughi, David Dewar, Shiva Nejati +1
Model-driven engineering (MDE) provides abstraction and analytical rigour, but industrial adoption in many domains has been limited by the cost of developing and maintaining models…
The Impact of Critique on LLM-Based Model Generation from Natural Language: The Case of Activity Diagrams
Parham Khamsepour, Mark Cole, Ish Ashraf +4
Large Language Models (LLMs) show strong potential for automating model generation from natural-language descriptions. A common approach begins with an initial model generation, fo…
Automated Test Validators for Flaky Cyber-Physical System Simulators: Approach and Evaluation
Baharin A. Jodat, Khouloud Gaaloul, Mehrdad Sabetzadeh +1
Simulation-based testing of cyber-physical systems (CPS) is costly due to the time-consuming execution of CPS simulators. In addition, CPS simulators may be flaky, leading to incon…
From Law to Gherkin: A Human-Centred Quasi-Experiment on the Quality of LLM-Generated Behavioural Specifications from Food-Safety Regulations
Shabnam Hassani, Mehrdad Sabetzadeh, Daniel Amyot
Context: Laws and regulations increasingly shape software design, development, and quality assurance in regulated domains. Because legal provisions are written in technology-neutra…
Effort-Optimized, Accuracy-Driven Labelling and Validation of Test Inputs for DL Systems: A Mixed-Integer Linear Programming Approach
Mohammad Hossein Amini, Mehrdad Sabetzadeh, Shiva Nejati
Software systems increasingly include AI components based on deep learning (DL). Reliable testing of such systems requires near-perfect test-input validity and label accuracy, with…
An Empirical Study on LLM-based Classification of Requirements-related Provisions in Food-safety Regulations
Shabnam Hassani, Mehrdad Sabetzadeh, Daniel Amyot
As Industry 4.0 transforms the food industry, the role of software in achieving compliance with food-safety regulations is becoming increasingly critical. Food-safety regulations,…
Simulink Mutation Testing using CodeBERT
Jingfan Zhang, Delaram Ghobari, Mehrdad Sabetzadeh +1
We present BERTiMuS, an approach that uses CodeBERT to generate mutants for Simulink models. BERTiMuS converts Simulink models into textual representations, masks tokens from the d…
Test Input Validation for Vision-based DL Systems: An Active Learning Approach
Delaram Ghobari, Mohammad Hossein Amini, Dai Quoc Tran +3
Testing deep learning (DL) systems requires extensive and diverse, yet valid, test inputs. While synthetic test input generation methods, such as metamorphic testing, are widely us…
Developing a Llama-Based Chatbot for CI/CD Question Answering: A Case Study at Ericsson
Daksh Chaudhary, Sri Lakshmi Vadlamani, Dimple Thomas +2
This paper presents our experience developing a Llama-based chatbot for question answering about continuous integration and continuous delivery (CI/CD) at Ericsson, a multinational…
Requirements-driven Slicing of Simulink Models Using LLMs
Dipeeka Luitel, Shiva Nejati, Mehrdad Sabetzadeh
Model slicing is a useful technique for identifying a subset of a larger model that is relevant to fulfilling a given requirement. Notable applications of slicing include reducing…
Enhancing Automata Learning with Statistical Machine Learning: A Network Security Case Study
Negin Ayoughi, Shiva Nejati, Mehrdad Sabetzadeh +1
Intrusion detection systems are crucial for network security. Verification of these systems is complicated by various factors, including the heterogeneity of network platforms and…
Rethinking Legal Compliance Automation: Opportunities with Large Language Models
Shabnam Hassani, Mehrdad Sabetzadeh, Daniel Amyot +1
As software-intensive systems face growing pressure to comply with laws and regulations, providing automated support for compliance analysis has become paramount. Despite advances…
A Lean Simulation Framework for Stress Testing IoT Cloud Systems
Jia Li, Behrad Moeini, Shiva Nejati +2
The Internet of Things connects a plethora of smart devices globally across various applications like smart cities, autonomous vehicles and health monitoring. Simulation plays a ke…
Self-adaptive, Requirements-driven Autoscaling of Microservices
João Paulo Karol Santos Nunes, Shiva Nejati, Mehrdad Sabetzadeh +1
Microservices architecture offers various benefits, including granularity, flexibility, and scalability. A crucial feature of this architecture is the ability to autoscale microser…
Practical Guidelines for the Selection and Evaluation of Natural Language Processing Techniques in Requirements Engineering
Mehrdad Sabetzadeh, Chetan Arora
Natural Language Processing (NLP) is now a cornerstone of requirements automation. One compelling factor behind the growing adoption of NLP in Requirements Engineering (RE) is the…
Test Generation Strategies for Building Failure Models and Explaining Spurious Failures
Baharin Aliashrafi Jodat, Abhishek Chandar, Shiva Nejati +1
Test inputs fail not only when the system under test is faulty but also when the inputs are invalid or unrealistic. Failures resulting from invalid or unrealistic test inputs are s…
Improving Requirements Completeness: Automated Assistance through Large Language Models
Dipeeka Luitel, Shabnam Hassani, Mehrdad Sabetzadeh
Natural language (NL) is arguably the most prevalent medium for expressing systems and software requirements. Detecting incompleteness in NL requirements is a major challenge. One…
Using Genetic Programming to Build Self-Adaptivity into Software-Defined Networks
Jia Li, Shiva Nejati, Mehrdad Sabetzadeh
Self-adaptation solutions need to periodically monitor, reason about, and adapt a running system. The adaptation step involves generating an adaptation strategy and applying it to…