This software delivery includes source code and documentations of the automated verification and validation tool developed under the PETTT BY15-080SP project.
Replication Package of "Exploiting Vision-Language Models in GUI Reuse", a paper published in the 22nd International Conference on Systems and Software Reuse (ICSR), Ottawa, Canada, April 27 2025.
The authors are: Victoria Niu, Walaa Alshammari, Naga Mamata Iluru, Padmaja Vaishnavi Teeleti, Nan Niu, Tanmay Bhowmik, and Jianzhang Zhang.
Replication Package of Environmental Variations of Software Features: A Logical Test Cases' Perspective authored by Md Rayhan Amin,Tanmay Bhowmik, Nan Niu, and Juha Savolainen
The development of complex and dependable systems like autonomous vehicles relies increasingly on the use of systems modeling language (SysML). In fact, SysML has become a de facto standard for systems engineering. With model-driven engineering, a SysML model serves as a reference for the early defect detection of the system under design: the earlier the errors are detected, the less is the cost of handling the errors. Mutation testing is a fault-based technique that has recently seen its applications to SysML behavioral models (e.g., state machine diagrams). Specifically, a system's state-transition design can be fed to a model checker where mutants are automatically generated and then killed against the desired design specifications (e.g., safety properties). In this paper, we present a novel approach based on process mining to improve the effectiveness and efficiency of the SysML mutation testing based on model checking. In our approach, the mutation operators are applied directly to the state machine diagram. These mutants are then fed as traces into a process mining tool and checked according to the event logs. Our initial results indicates that the process mining approach kills more mutants faster than the model checking method.
This document contains the list of Hidden Requirements and Disagreement between stakeholders between teams G1,G2,V1 and V2 and their validity check by stakeholders
Aurek Chattopadhyay, Reagan Maddox, Glen Horton, Nan Niu, Ganesh Malla, Tanmay Bhowmik, Jianzhang Zhang, and Juha Savolainen, Completeness of Natural Language Requirements: A Comparative Study of User Stories and Feature Descriptions (submitted to REFSQ 2023: https://2023.refsq.org)
Artifacts of the paper entitled:
Prompting Creative Requirements via Traceable and Adversarial Examples in Deep Learning
Authors: Hemanth Gudaparthi, Nan Niu, Boyang Wang, Tanmay Bhowmik, Hui Liu, Jianzhang Zhang, Juha Savolainen, Glen Horton, Sean Crowe, Thomas Scherz and Lisa Haitz
To appear in the Proceedings of the 31st IEEE International Requirements Engineering Conference (RE 2023 https://conf.researchr.org/home/RE-2023)
Artifacts of the paper entitled:
A Study of Natural-Language and Vision-Language GUI Retrieval
Authors: Walaa Alshammari, Yitong Yang, Yinglin Wang, Nan Niu, Tanmay Bhowmik, Padmaja Vaishnavi Teeleti, and Naga Mamata Iluru
The content is:
A-relevance-judging-results.xlsx has five sheets recording the four judges' assessment and their inter-rater agreement levels;
B-GUI-retrieval-answer-set.xlsx specifies the relevance relations between 40 GUI images and 27 NL queries;
C-retrieval-results.xlsx contains top-10 NL-based results in one sheet, and top-5 NL-based and VL-based results in the other four sheets; and
D-human-subject-study-material.pdf documents the five GUI reuse tasks approved by an institutional review board.
D-