Hi, I'm Safdar Aqeel (Ph.D.)

I am an enthusiastic computer scientist and practitioner with excellent academic records and 8+ years of experience working on multiple R&D projects that span the area of software modeling, testing, search algorithms, and machine learning at various known research institutes. I am a results-driven, customer-focused, articulate and analytical software engineer/architect who is skilled in software design & development, IT architecture, and cloud infrastructure.

Currently I am working as an IT Architect at DNB, which is the largest bank of Norway. As an Architect, my job is to design software solutions to address different needs of customers and meet the legal requirements impose on financial institutes in addition to assessing the feasibility of new technologies (e.g., Kafka, Kubernetes, cloud services) and improving the current software solutions

I received my Ph.D. degree in Software Engineering from University of Oslo, Norway in April 2021. During my Ph.D., I worked as a Research Fellow at Simula Research Laboratory, Norway where I worked with Dr. Tao Yue and Dr. Shaukat Ali in the field of Product Line Engineering of Cyber-Physical Systems. I attained my Bachelor and Master degrees in Computer Science from the National University of Computer and Emerging Sciences (FAST-NU), Islamabad campus, Pakistan in 2013 and 2015 respectively. I also worked as a Research Fellow at Software Quality Engineering and Testing (QUEST) Laboratory, Pakistan with Dr. Muhammad Zohaib Iqbal and Dr. Muhammad Uzair Khan in the field of Model-Driven Engineering and Software Testing. My research interests include Product Line Engineering, Search-Based Software Engineering, Model-Based Engineering, Empirical Software Engineering, and Machine Learning

Journals

• Evaluating UML Modeling Tools based on Modeler's Productivity - A Replicated Study, Safdar Aqeel Safdar, Muhammad Zohaib Iqbal, Muhammad Uzair Khan, submitted to an international journal, 2021

• Recommending Faulty Configurations for Interacting Systems Under Test Using Multi-Objective Search, Safdar Aqeel Safdar, Tao Yue, Shaukat Ali, Accepted in the ACM Transactions on Software Engineering and Methodology (TOSEM), 2021

• Quality Indicators in Search-based Software Engineering: An Empirical Evaluation, Shaukat Ali, Polo Arcaini, Dipesh Pradhan, Safdar Aqeel Safdar, Tao Yue, Published in the ACM Transactions on Software Engineering and Methodology (TOSEM), 2020

• A Framework for Automated Multi-Stage and Multi-Step Product Configuration of Cyber-Physical Systems, Safdar Aqeel Safdar, Hong Lu, Tao Yue, Shaukat Ali, Kunming Nie, Published in the International Journal of Software and Systems Modeling (SoSym), 2020

• Using multi-objective search and machine learning to infer rules constraining product, Safdar Aqeel Safdar, Hong Lu, Tao Yue, Shaukat Ali, Published in the International Journal of Automated Software Engineering (ASE), 2019

Conferences

• Mining Cross Product Line Rules with Multi-Objective Search and Machine Learning, Safdar Aqeel Safdar, Hong Lu, Tao Yue, Shaukat Ali, published in Genetic and Evolutionary Computation Conference (GECCO), 2017.

• Evaluating Variability Modeling Techniques for Supporting Cyber-Physical System Product Line Engineering, Safdar Aqeel Safdar, Tao Yue, Shaukat Ali, Hong Lu published in System Analysis and Modeling Conference (SAM), 2016.

• An Empirical Evaluation of UML Modeling Tool- An Experiment, Safdar Aqeel Safdar, Muhammad Zohaib Iqbal, Muhammad Uzair Khan published in European Conference on Modeling Foundations and Applications (ECMFA), 2015

Thesis

• Improving Post-Deployment Configuration of Cyber-Physical Systems Using Machine Learning and Multi- Objective Search (Ph.D. Thesis), Safdar Aqeel Safdar, University of Oslo, Norway 2021

• A Comparative Study of UML Modeling Tools (MS Thesis), Safdar Aqeel Safdar, National University of Computer and Emerging Sciences (FAST-NU) 2015

• Post-Deployment Configuration Recommendation: In this project, we proposed a multi-objective search-based technique that recommends the configurations for a system of systems to ensure the correct behavior of the system using software constraints. The proposed approach is published in a journal paper in the ACM Transactions on Software Engineering and Methodology (TOSEM).

• Facilitating the Automated Configuration of CPS Product Lines: In this project, we proposed a conceptual framework to support the automated configuration of CPS product lines, which involves variability modeling, constraint specifications, and different automated functionalities of a configuration tool. The proposed framework is published in a journal paper in the International Journal of Software and Systems Modeling (SoSym).

• Mining Cross Product Line Rules: In this project, we proposed a technique, which combines machine learning and multi-objective search algorithms to mine the rules specifying the abnormal behavior of system. The results are published in a conference paper at GECCO-2017 and a journal paper in the International Journal of Systems and Software (JSS).

• Variability Modeling for Cyber-Physical Systems (CPSs): In this project, we proposed a set of variation points and modeling requirements to capture the variabilities of CPS product lines. Further, we evaluated four existing variability modeling techniques based on proposed framework. Results of this project are published in a conference publication at SAM-2016.

• Evaluation of UML Modeling Tools: In this project, we evaluated the capabilities of UML modeling tools in terms of modeler’s productivity using controlled experiments. Evaluation results of initial experiment are published in a conference publication at ECMFA-2015 and results of replication are in process of publication at an international journal.

During my Ph.D. I worked in the field of Software Prodcut Line Engineering. More specifically, my Ph.D. focused on improving the post-deployment configuration of Cyber-Physical System Product Lines with the help of Machine Learning and Multi-Objective Search

During my masters at FAST-NU, I studied a variey of computer science and software engineering courses. Addionally, I conducted research in the filed of Model-driven Software Engineering and Emprical Software Engineering. In my master thesis, I evaluate the usability of different UML modeling tools and the productivity of Modelers using human-based controlled experiments.

During my Bachelor at FAST-NU, I studied a variey of courses covering wide range of topics such as software analysis &design, coding, testing, data structure, algorithm analysis, project management, data mining, and other business aspects such as marketing, management, and entrepreneurship. Moreover, I also studied several courses on mathematics including calculus, linear algebra, numerical analysis, and statistics & probability.

Currently, I am working at DNB Bank as IT Architect. My job as IT Architect includes identifying and mitigating the technical debet in the current software systems, designing new banking sofware solutions, and assessing and recommending the new technologies to meet the customer needs and other legal requirements in an efficient manner

I worked as a Ph.D. Research Fellow from July 2015 up till April 2021 at Simula Research Laboratory, Oslo, Norway. During this tenure, I worked in the field of Product Line Engineering of Cyber-Physical System (CPS). More specifically, I focused on variability modeling, mining configuration patterns in form of configuration rules, post-deployment configuration recommendation and automation of configuration. I also participated in research activities such as paper reviews, discussions, and reviews for international conferences and journals.

I worked as Research Fellow from June 2013 to June 2015 at QUEST lab, Islamabad, Pakistan. During this tenure, I worked on industrial problems with the collaboration of other senior researchers. I planned and conducted controlled experiments and wrote a number of research papers. I also participated in research activities such as paper reviews, experiments, discussions, and peer reviews.