Software Quality Engineering and Testing (QUEST) Center
The Software Quality Engineering and Testing Center (QUEST) focuses on engineering of reliable and dependable software systems. Quality Engineering and Testing of software systems is an active research area and is receiving a lot of attention worldwide. However, catastrophic software failures are still reported frequently. There is an ever-increasing need to develop better quality software by using systematic engineering techniques. For this purpose, the center will investigate the use of model-driven approaches for developing high quality software.
Almost all professionals in software industry agree on the need to thoroughly test the developed software. However, the actual testing process is severely hindered by lack of automation. Software testing is a time consuming process that requires specific expertise and automation to be cost-effective, which are often not available in industry.
The QUEST center aims to bridge this gap by developing novel strategies and tools for quality engineering and automated testing that are scalable in industrial context. The real impact of software engineering is visible only when the practices/techniques are transferred to the practitioners/industry. Therefore, the center focuses on performing applied research by solving real industrial problems. For this purpose we work closely with local and international industrial and research partners. The key research and academic goals of the lab include:
- To propose and evaluate new methodologies for engineering quality software systems.
- To develop new and innovative testing strategies for cost effective testing.
- To improve the quality engineering practices of local organizations by providing automated quality engineering tools and techniques.
- To conduct high quality research in collaboration with international research organizations.
- To allow students and researchers in Pakistan to work with top international research institutes and researchers in the field of quality engineering.
Engineering dependable and reliable systems is a difficult challenge, which requires cross-disciplinary collaboration involving both the academia and the industry. The Quest lab is actively involved in research collaborations with researchers from renowned research organizations such as Simula Labs, Norway and the Inter-disciplinary Center for Security and Trust (SnT).
- Integrated Toolset for automated model-based testing – MBT-Toolset (National ICT R&D Funded) Collaboration: Simula Labs, Norway.
- Automated model based constraint solver. Collaboration: SnT, Luxumbourg
- Automated Re-factoring of UML Models. Collaboration: Cisco Systems Inc.
- Automated testing of model transformations
- Model based development of dependable mobile applications
Impact Factor International Journal publications from QUEST in 2013/2014
- Muhammad Zohaib Iqbal, Shaukat Ali, Tao Yue, Lionel Briand, Applying UML/MARTE on Industrial Projects: Challenges, Experiences, and Guidelines, Accepted for publication in Software and Systems Modeling Journal (SoSyM), 2014
- Shaukat Ali, Muhammad Zohaib Iqbal, Andrea Arcuri, Lionel Briand, Generating Test Data from OCL Constraints with Search Techniques, in IEEE Transactions on Software Engineering, 39(10): 1376-1402, 2013.
- Muhammad Zohaib Iqbal, Andrea Arcuri, Lionel Briand, "Environment Modeling and Simulation for Automated Testing of Soft Real-Time Embedded Software", in Software and Systems Modeling Journal (SoSyM), 2013.
Software Engineering Research Center (SERC)
The objectives of this centre are to carry out research and development in software engineering and allied application areas. The centre promotes theoretical research in the software engineering area, resolve problems faced by the software industry, and helps establish software engineering practices in the industry. Through SERC, the University seeks to help and support the local software industry in establishing and improving their processes and practices through continuous feedback and training. SERC aims to achieve these objectives by collecting the industry data to understand productivity, cost, and quality parameters. This will hopefully also help in developing more suitable process and lifecycle models for different types of projects being undertaken by our local industry in the offshore and distributed environment. Software Architecture, Software Project Management, Software Quality and Process Improvement are main areas of research.
Sample Projects Completed
- Software Maintenance Prediction: An Architecture Perspective.
- Coverage Analysis for GUI Testing.
- Intelligent Requirement Prioritization using Fuzzy Logic.
- Proposing Architecture for Grid Monitoring Tools.
- Tracing Architecture Decisions to Requirements.
- Proposing Software Project Management Methodology.
- Integrated service-oriented architecture (SOA) environment.
- Software Architecture for 2D Mobile Game Development.
- Sense Me (A virtual interface).
- Authenticated identification system.
- Framework and Software Architecture for Information Assurance and Regulatory Compliance (“FAIR”)
- A Generic Model for Testing Agent based Applications
- Software Effort Estimation using Evolutionary Computation Techniques
- Widget-Based Application Composition Framework
Management Advancement Research Center - MARC
The Management Advancement Research Centre (MARC) was established at FAST_NUCES Islamabad to conduct leading edge research in management sciences with the aim to enhance knowledge and find solutions for industry challenges. Various Special Interest Groups (SIGs) work under MARC, all committed to taking up projects which contribute to the body of knowledge, yet at the same time provide a bridge between academia and practice.
The Leadership and Management SIG has carried out various projects on leadership, cross-cultural HRM and performance management over the past few years. International projects and partnerships include work with the Cross-Cultural Management Network (CCMN) under which the main past project covered trust and leadership across cultures, while the current project is based on leadership behaviors, trust and job embeddedness across cultures. Another landmark project of the SIG includes collection of data on GLOBE's cultural dimension in Pakistan and comparison of Pakistan with 61 GLOBE countries in collaboration with the GLOBE team and the Thunderbird University. The lead researcher has also been involved in various projects on performance management to improve industry practices, and has a special interest in using data to improve HR practices.
The Project Management and the Organizational Behavior SIGs are recent additions to expand the scope of MARC. The team's expertise include behavioral decision making in project management, justice, creativity, organizational politics, workplace stressors and psychological stressors. The SIG researchers have various publications in the above mentioned areas and are interested in working with industry to improve organizational practices. Extensive research has been carried out on Islamic Finance under the Islamic Finance SIG. The lead researcher has published two books on Islamic Finance and has published numerous articles on the subject. The SIG is interested in working closely with the Islamic banks and the Islamic finance industry to refine practices.
Extensive research has been carried out on Islamic Finance under the Islamic Finance SIG. The lead researcher has published two books on Islamic Finance and has published numerous articles on the subject. The SIG is interested in working closely with the Islamic banks and the Islamic finance industry to refine practices.
ReVeaL (Recognition, Vision and Learning) Research Group
ReVeaL is a research group that focuses on applied research in Visual Recognition, Computer Vision and Machine Learning for solving real-world large-scale complex problems.
In ReVeaL the goal is to conceive, design and develop recognition systems that can recognize and understand the content of an image (or video) and then make informed decisions or recommendations. Building such systems not only demands solutions for complex recognition and inference problems but also requires answers to challenging computational questions.
Research areas include:
- Computer Vision
- Visual Recognition
- Deep Learning
- Applied Image Processing and Machine Learning
Members of the group:
Following faculty members are part of this group:
- Dr. Sibt ul Hussain (Post Doc. and Doctorate in Visual Recognition and Machine Learning).
- Dr. Usman Farrokh (Doctorate in Visual Recognition and Video Processing).
- Dr. Fareed Ahmad (Doctorate in Applied Image Processing).
Artificial Intelligence & Machine Leaning [AIM]
The primary motivation for the creation of this group is to encourage the development and understanding of Artificial Intelligence (AI) and its applications in our students and faculty members. It promotes inter-disciplinary exchanges between AI and other fields such as information processing, energy management etc. Its principal focus is to maintain a sustainable research base aimed for graduate and post-graduate students within relevant research areas.
This research group emphasizes on the areas of Computational Intelligence, Machine Learning and Data Mining. We explore the applications of the algorithms and techniques from these areas, in real life scenarios. The group has ongoing research work that investigates the creation of automated and independent learning within machines. Some areas where our research work is applied include Game AI, Social Computing, Knowledge Management, as well as other classical areas of research such as function optimization in dynamic or time variant environments.
Members of the group:
- Dr. Hammad Majeed, Assistant Prof.
- Dr. Waseem Shahzad, Associate Prof.
- Dr. Hassan Mujtaba, Assistant Prof.
- Dr. Omer Beg, Assistant Prof.
- Mr. Ali Nasir, Assistant Prof.
- Ms. Saba Rasheed Malik, Assistant Prof.
EPIC (Embedded Systems & Pervasive Computing) Lab
Electrical Engineering Department hosts the Embedded Systems & Pervasive Computing (EPIC) Lab that as the name suggests, encompasses research and development activities in the broad areas of Embedded Systems, Internet of Things (IOT), Cloud Computing and integration of software and hardware systems. It is headed by Dr. Ataul Aziz Ikram, Associate Professor, Department of Electrical Engineering. Currently, a Higher Education Commission (HEC) funded National Research Program for Universities (NRPU) project is being executed by Dr. Ataul Aziz Ikram, Principal Investigator. The title of the project is “Implementation of a multi-device multi technology cloud, performance evaluation and customization for commercial applications”. The project is in collaboration with the University of Gujrat, Hafiz Hayat Campus, and the Co-Principal Investigator, Dr. Zia- Ul Qayyum, who is also the Vice Chancellor there.
HALP (Huawei Authorized Learning Partner)
To bridge the gap between academia and industry, the University has joined hands with Huawei Technologies to establish a training center at its Islamabad campus. It is now a “Huawei Authorized Learning Partner (HALP)” and is able to deliver Huawei Certified Network Associate training program. The three programs currently offered include HCNA Unified Communications and HCNA Storage and HCNA Routers and Switches. Six batches that constituted Industry Professionals and University Alumni have successfully completed HCNA training from HALP.
HAINA (Huawei Authorized Information and Network Academy)
Huawei Authorized Information and Network Academy (HAINA) is a not-for-profit partnership program that authorizes universities and colleges to deliver Huawei Certification courses to their students. Huawei and Islamabad campus signed HAINA agreement recently and two batches have already completed their Training Program. The University believes that practical knowledge will create opportunities and will support effective and sustainable growth. Through the HAINA program, Huawei and NUCES contributes support to the local ICT education, shares knowledge, creates more opportunities, and builds a better ICT talent eco-system.