Profile
Office: FNAS 0.10
Email: pakiki@ndu.edu.lb
Phone: +961 9 218950 (ext. 2084)
Hello!

I am a computer scientist and a researcher focusing mostly on Software Engineering and Human-Computer Interaction.

I am an associate professor in the Department of Computer Science at Notre Dame University – Louaize.

I hold a Ph.D. in Computing from The Open University in the United Kingdom, where I worked on devising a platform for supporting the development of adaptive model-driven user interfaces. I have a diverse education and set of skills, which I applied in both academia and industry.

For more information check out my curriculum vitae.

Recent Research Themes

Full List of Research Themes >>

End-User Development for IoT and Robotics
2016 2020

Profile
End-user development challenges include configuring internet-of-things (IoT) devices and services to work together and programming robots for different purposes. Millions of school kids nowadays are taught programming concepts using end-user development environments. Can’t we use a similar environment to empower end-users to develop software for IoT and robotics? Visual Simple Transformations (ViSiT) empowers end-users to wire IoT devices and services. For example, end-users can use puzzle pieces to implement a transformation that allows a Microsoft Xbox controller to communicate with a Lego Mindstorms robot. EUD-MARS provides end-users with a simple approach for developing model-driven adaptive robotics software using a visual programming language.

Tracking Changes and Measuring Contributions in Cooperative Systems Modeling
2019 2020

Profile
Models are often used to represent various types of systems. This is especially true for software systems, where cooperating teams create models using a modeling language (e.g., UML). In cooperative modeling scenarios, it is useful to identify contributions and changes performed by individuals and teams. CHECKSUM monitors the cooperative work done on models and maintains an immutable changelog. CHECKSUM uses its changelog to measure contributions based on points, time, and quality, and to enable the auditing of a model’s change-history. GEneric Meta-Model (GEMM) enables CHECKSUM to support an extensible variety of model types by unifying the models’ underlying representation.

Model-Driven Contextual Help for Adaptive User Interfaces
2017 2018

Profile
Contextual Help for Adaptive INterfaces (CHAIN) is an approach for developing model-driven contextual help that maintains its usefulness across UI adaptations. This trait is achieved by interpreting the help models at runtime and overlaying instructions on the running adapted UI. A language called Contextual Help for Adaptive INterfaces eXtensible Markup Language (CHAINXML) and a visual notation were developed for expressing and depicting help models. A technique was also devised for presenting CHAIN help models over legacy applications, whether or not their source-code is available. A supporting tool was developed as an extension to Cedar Studio.
End-user development challenges include configuring internet-of-things (IoT) devices and services to work together and programming robots for different purposes. Millions of school kids nowadays are taught programming concepts using end-user development environments. Can’t we use a similar environment to empower end-users to develop software for IoT and robotics? Visual Simple Transformations (ViSiT) empowers end-users to wire IoT devices and services. For example, end-users can use puzzle pieces to implement a transformation that allows a Microsoft Xbox controller to communicate with a Lego Mindstorms robot. EUD-MARS provides end-users with a simple approach for developing model-driven adaptive robotics software using a visual programming language.
Models are often used to represent various types of systems. This is especially true for software systems, where cooperating teams create models using a modeling language (e.g., UML). In cooperative modeling scenarios, it is useful to identify contributions and changes performed by individuals and teams. CHECKSUM monitors the cooperative work done on models and maintains an immutable changelog. CHECKSUM uses its changelog to measure contributions based on points, time, and quality, and to enable the auditing of a model’s change-history. GEneric Meta-Model (GEMM) enables CHECKSUM to support an extensible variety of model types by unifying the models’ underlying representation.
Contextual Help for Adaptive INterfaces (CHAIN) is an approach for developing model-driven contextual help that maintains its usefulness across UI adaptations. This trait is achieved by interpreting the help models at runtime and overlaying instructions on the running adapted UI. A language called Contextual Help for Adaptive INterfaces eXtensible Markup Language (CHAINXML) and a visual notation were developed for expressing and depicting help models. A technique was also devised for presenting CHAIN help models over legacy applications, whether or not their source-code is available. A supporting tool was developed as an extension to Cedar Studio.

Analyzing Source Code to Improve Software Quality
2018

Profile
Source code can be analyzed to understand how software developers apply certain principles. The results of such analysis show whether software developers are using certain principles or programming language features. As a starting point in this research, I developed a software called CARE#. The latter can analyze the source code of C# software programs to determine how software developers are using and misusing implicit and explicit typing. CARE# can also automatically refactor the source code to improve the developers’ typing choices in terms of consistency and readability.

Adaptive Model-Driven User Interfaces
2011 2016

Profile
Cedar is a platform targeting the development of adaptive user interfaces for enterprise applications, using a model-driven approach. Cedar’s primary aim is user interface simplification, which comprises role-based feature-set minimization and layout optimization. Enterprise software applications include many scenarios, where end-users with different roles require variable versions of the same user interface. Catering to this variability, by providing multiple user interface versions, would enhance usability. This research contributed: a reference-architecture (Cedar Architecture), an adaptation technique (RBUIS), and a supporting IDE (Cedar Studio).

Forecasting ERP Implementation Outcome
2010

Profile
With the constant evolution of technology and increase in business process complexity, ERP systems had to drastically evolve to accommodate the needs of modern businesses. This drives the implementation of such systems to become very complex hence creating a high risk of implementation failure. This work mainly aims to establish a systematic framework that helps in reducing the risk of ERP implementation failures to protect businesses from possible financial losses.
Source code can be analyzed to understand how software developers apply certain principles. The results of such analysis show whether software developers are using certain principles or programming language features. As a starting point in this research, I developed a software called CARE#. The latter can analyze the source code of C# software programs to determine how software developers are using and misusing implicit and explicit typing. CARE# can also automatically refactor the source code to improve the developers’ typing choices in terms of consistency and readability.
Cedar is a platform targeting the development of adaptive user interfaces for enterprise applications, using a model-driven approach. Cedar’s primary aim is user interface simplification, which comprises role-based feature-set minimization and layout optimization. Enterprise software applications include many scenarios, where end-users with different roles require variable versions of the same user interface. Catering to this variability, by providing multiple user interface versions, would enhance usability. This research contributed: a reference-architecture (Cedar Architecture), an adaptation technique (RBUIS), and a supporting IDE (Cedar Studio).
With the constant evolution of technology and increase in business process complexity, ERP systems had to drastically evolve to accommodate the needs of modern businesses. This drives the implementation of such systems to become very complex hence creating a high risk of implementation failure. This work mainly aims to establish a systematic framework that helps in reducing the risk of ERP implementation failures to protect businesses from possible financial losses.
Recent Research Videos

Full List of Research Videos >>

Tracking Changes and Measuring Contributions in Cooperative Systems Modeling

End-User Development for IoT

Engineering Adaptive UIs for Enterprise Applications

Recent Publications

Full List of Publications >>

2021

PDF
CHECKSUM: tracking changes and measuring contributions in cooperative systems modeling
Pierre A. Akiki and Hoda W. Maalouf
Software and Systems Modeling, Springer

2020

PDF
EUD-MARS: End-user development of model-driven adaptive robotics software systems
Pierre A. Akiki, Paul A. Akiki, Arosha K. Bandara, and Yijun Yu
Science of Computer Programming, Elsevier, 200: 102534

2019

PDF
To var or not to var: How do C# Developers Use and Misuse Implicit and Explicit Typing?
Pierre A. Akiki
Software Quality Journal, Springer, 27(3), 1175-1207

2018

PDF
CHAIN: Developing Model-Driven Contextual Help for Adaptive User Interfaces
Pierre A. Akiki
Journal of Systems and Software, Elsevier, 135, pp. 165-190

2017

PDF
Visual Simple Transformations: Empowering End-Users to Wire Internet of Things Objects
Pierre A. Akiki, Arosha K. Bandara, and Yijun Yu
ACM Transactions on Computer-Human Interaction, ACM, 24(2), pp. 10:1-10:43

2016

PDF
Engineering Adaptive Model-Driven User Interfaces
Pierre A. Akiki, Arosha K. Bandara, and Yijun Yu
IEEE Transactions on Software Engineering, IEEE, 42(12), pp. 1118–1147

2014

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Adaptive Model-Driven User Interface Development Systems
Pierre A. Akiki, Arosha K. Bandara, and Yijun Yu
ACM Computing Surveys, ACM, 47(1), pp. 64:1–64:33
PDF
Integrating Adaptive User Interface Capabilities in Enterprise Applications
Pierre A. Akiki, Arosha K. Bandara, and Yijun Yu
36th International Conference on Software Engineering, Hyderabad, India, ACM/IEEE, pp. 712–723
PDF
Engineering Adaptive Model-Driven User Interfaces for Enterprise Applications
Pierre A. Akiki
The Open University, Milton Keynes, United Kingdom
PhD in Computing

2013

PDF
RBUIS: Simplifying Enterprise Application User Interfaces through Engineering Role-Based Adaptive Behavior
Pierre A. Akiki, Arosha K. Bandara, and Yijun Yu
5th ACM SIGCHI Symposium on Engineering Interactive Computing Systems, London, United Kingdom, ACM, pp. 3–12
Best Paper Award
PDF
Cedar Studio: An IDE Supporting Adaptive Model-Driven User Interfaces for Enterprise Applications
Pierre A. Akiki, Arosha K. Bandara, and Yijun Yu
5th ACM SIGCHI Symposium on Engineering Interactive Computing Systems, London, United Kingdom, ACM, pp. 139–144
PDF
Crowdsourcing User Interface Adaptations for Minimizing the Bloat in Enterprise Applications
Pierre A. Akiki, Arosha K. Bandara, and Yijun Yu
5th ACM SIGCHI Symposium on Engineering Interactive Computing Systems, London, United Kingdom, ACM, pp. 121–126
PDF
Engineering Adaptive User Interfaces for Enterprise Applications
Pierre A. Akiki
5th ACM SIGCHI Symposium on Engineering Interactive Computing Systems, London, United Kingdom, ACM, pp. 151–154
PDF
Preserving Designer Input on Concrete User Interfaces Using Constraints While Maintaining Adaptive Behavior
Pierre A. Akiki, Arosha K. Bandara, and Yijun Yu
2nd Workshop on Context-Aware Adaptation of Service Front-Ends, London, United Kingdom, CEUR-WS.org, pp. 9–16