57 citations · 116 across the 31 of their papers we have counts for
30 papers · 1 filter
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…
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…
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…
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…
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…
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…
Reflections on Surrogate-Assisted Search-Based Testing: A Taxonomy and Two Replication Studies based on Industrial ADAS and Simulink Models
Shiva Nejati, Lev Sorokin, Damir Safin +3
Surrogate-assisted search-based testing (SA-SBT) aims to reduce the computational time for testing compute-intensive systems. Surrogates enhance testing techniques by improving tes…
Probabilistic Safe WCET Estimation for Weakly Hard Real-Time Systems at Design Stages
Jaekwon Lee, Seung Yeob Shin, Lionel Briand +1
Weakly hard real-time systems can, to some degree, tolerate deadline misses, but their schedulability still needs to be analyzed to ensure their quality of service. Such analysis u…
Learning Non-robustness using Simulation-based Testing: a Network Traffic-shaping Case Study
Baharin Aliashrafi Jodat, Shiva Nejati, Mehrdad Sabetzadeh +1
An input to a system reveals a non-robust behaviour when, by making a small change in the input, the output of the system changes from acceptable (passing) to unacceptable (failing…
A Domain-Specific Language for Simulation-Based Testing of IoT Edge-to-Cloud Solutions
Jia Li, Shiva Nejati, Mehrdad Sabetzadeh +1
The Internet of things (IoT) is increasingly prevalent in domains such as emergency response, smart cities and autonomous vehicles. Simulation plays a key role in the testing of Io…
Guidelines for Artifacts to Support Industry-Relevant Research on Self-Adaptation
Danny Weyns, Ilias Gerostathopoulos, Barbora Buhnova +16
Artifacts support evaluating new research results and help comparing them with the state of the art in a field of interest. Over the past years, several artifacts have been introdu…
Learning Self-adaptations for IoT Networks: A Genetic Programming Approach
Jia Li, Shiva Nejati, Mehrdad Sabetzadeh
Internet of Things (IoT) is a pivotal technology in application domains that require connectivity and interoperability between large numbers of devices. IoT systems predominantly u…
Optimal Priority Assignment for Real-Time Systems: A Coevolution-Based Approach
Jaekwon Lee, Seung Yeob Shin, Shiva Nejati +1
In real-time systems, priorities assigned to real-time tasks determine the order of task executions, by relying on an underlying task scheduling policy. Assigning optimal priority…
Digital Twins Are Not Monozygotic -- Cross-Replicating ADAS Testing in Two Industry-Grade Automotive Simulators
Markus Borg, Raja Ben Abdessalem, Shiva Nejati +2
The increasing levels of software- and data-intensive driving automation call for an evolution of automotive software testing. As a recommended practice of the Verification and Val…
Combining Genetic Programming and Model Checking to Generate Environment Assumptions
Khouloud Gaaloul, Claudio Menghi, Shiva Nejati +2
Software verification may yield spurious failures when environment assumptions are not accounted for. Environment assumptions are the expectations that a system or a component make…