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Evaluating Critical Success Factors in AI-Driven Drug Discovery Using AHP: A Strategic Framework for Optimization
Amir Mohamed Talib;Areen Metib Al-Hgaish;Rodziah Binti Atan;Abdulaziz Alshammari;Fahad Omar Alomary;Razali Yaakob;Abdulaziz Alsahli;Mohd Hafeez Osman
Artificial Intelligence (AI) is reshaping drug discovery by accelerating the identification of therapeutic candidates and reducing development timelines and costs. However, its effectiveness depends on addressing key success factors that influence AI integration. This study presents a novel framework using the Analytic Hierarchy Process (AHP) to systematically evaluate and rank these factors, addr...Show More
Interpretable Deep Learning for Efficient Code Smell Prioritization in Software Development
Maaeda M. Rashid;Mohd Hafeez Osman;Khaironi Yatim Sharif;Hazura Zulzalil
Code smells indicate potential design flaws in software systems that can impair maintainability and increase technical debt. While existing approaches have advanced code smell priortization, they often lack effective prioritization mechanisms and interpretability, hindering developers’ ability to make informed refactoring decisions. This paper presents a novel approach combining CodeBERT embedding...Show More
Identification of Emergent Properties Occurrences Factors in System-of-Systems
Lehka Subramanium;Sa'adah Hassan;Hazura Zulzalil;Mohd. Hafeez Osman
2023 IEEE International Conference on Computing (ICOCO)
Year: 2023 | Conference Paper |
Systems-of-systems (SoS) is a term used to describe independent systems that collaborate to accomplish a task they are unable to complete separately. One of the challenges of developing SoS is to manage the emergent properties that arise from the interaction of independent systems. The emergent properties can be desirable or undesirable. It is important to comprehend the undesirable emergent prope...Show More
Applications of Data Analytics and Machine Learning for Digital Twin-based Precision Biodiversity: A Review
Nurfadhlina Mohd Sharef;Nurul Amelina Nasharuddin;Raihani Mohamed;Nabila Wardah Zamani;Mohd Hafeez Osman;Razali Yaakob
2022 International Conference on Advanced Creative Networks and Intelligent Systems (ICACNIS)
Year: 2022 | Conference Paper |
Cited by: Papers (2)
Biodiversity projections and model evaluation are essential to inform future formulation of biodiversity policy. These could be supported by data analytics and machine learning approaches, as well as precision technologies. However, existing works are segregated by the selection of species under-study and depending on the location. This paper reviews the existing approaches for precision biodivers...Show More
Run-Time Safety Monitoring Framework for AI-Based Systems: Automated Driving Cases
2019 26th Asia-Pacific Software Engineering Conference (APSEC)
Year: 2019 | Conference Paper |
Cited by: Papers (6)
Intelligent systems based on artificial intelligence techniques are increasing and are recently being accepted in the automotive domain. In the competition of automobile makers to provide fully automated vehicles, it is perceived that artificial intelligence will profoundly influence the automotive electric and electronic architecture in the future. However, while such systems provide highly advan...Show More
Learning a Classifier for Prediction of Maintainability Based on Static Analysis Tools
Markus Schnappinger;Mohd Hafeez Osman;Alexander Pretschner;Arnaud Fietzke
2019 IEEE/ACM 27th International Conference on Program Comprehension (ICPC)
Year: 2019 | Conference Paper |
Cited by: Papers (11)
Static Code Analysis Tools are a popular aid to monitor and control the quality of software systems. Still, these tools only provide a large number of measurements that have to be interpreted by the developers in order to obtain insights about the actual quality of the software. In cooperation with professional quality analysts, we manually inspected source code from three different projects and e...Show More
Anomaly Detection for Advanced Driver Assistance Systems Using Online Feature Selection
Christoph Segler;Stefan Kugele;Philipp Obergfell;Mohd Hafeez Osman;Sina Shafaci;Eric Sax;Alois Knoll
Context: As we move towards higher levels of automation in autonomous driving, we see an increase in functionality that either assists or takes over in both normal and emergency scenarios. These new functionalities can be intentionally switched off by the user, but can also be deactivated unintentionally by (i) accident, (ii) a software malfunction, (iii) a hardware defect, or (iv) an intrusion. A...Show More
Evaluation of Feature Selection for Anomaly Detection in Automotive E/E Architectures
Christoph Segler;Stefan Kugele;Philipp Obergfell;Mohd Hafeez Osman;Sina Shafaei;Eric Sax;Alois Knoll
2019 IEEE/ACM 41st International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)
Year: 2019 | Conference Paper |
Cited by: Papers (4)
As we move towards higher levels of automation in autonomous driving, we see an increase in functionality that either assists or takes over in both normal and emergency scenarios. These new functionalities can be switched off by the user for personalisation. We aim to recognise mistimed and/or unintended deactivation of vehicle functions, in particular, driver assistance functions (ADAS), at run-t...Show More
An Automated Approach for Classifying Reverse-Engineered and Forward-Engineered UML Class Diagrams
2018 44th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)
Year: 2018 | Conference Paper |
Cited by: Papers (12)
UML Class diagrams are commonly used to describe the designs of systems. Such designs can be used to guide the construction of software. In practice, we have identified two main types of using UML: (i) FwCD refers to diagrams are hand-made as part of the forward-looking development process; (ii) RECD refers to those diagrams that are reverse engineered from the source code; Recently, empirical stu...Show More
Ambiguous Software Requirement Specification Detection: An Automated Approach
2018 IEEE/ACM 5th International Workshop on Requirements Engineering and Testing (RET)
Year: 2018 | Conference Paper |
Software requirement specification (SRS) document is the most crucial document in software development process. All subsequent steps in software development are influenced by this document. However, issues in requirement, such as ambiguity or incomplete specification may lead to misinterpretation of requirements which consequently, influence the testing activities and higher the risk of time and c...Show More
Systematic Approach Based on Best Practices to Develop Requirements Engineering (RE) Guideline in an Organization
Azlena Haron;Shamsul Sahibuddin;Haizan Yusoff;Mohd Haffez Osman
2017 Palestinian International Conference on Information and Communication Technology (PICICT)
Year: 2017 | Conference Paper |
Cited by: Papers (1)
Best practices in developing Requirements Engineering are not new. They are easily comprehended by experts familiar to Requirements Engineering. However, for IT Personnel that are new to this field, understanding the process may pose major challenges. Thus, a Requirements Engineering Best Practices Work Flow was developed as a tool to assist in the development of Requirements Engineering. The work...Show More
Interactive Scalable Abstraction of Reverse Engineered UML Class Diagrams
2014 21st Asia-Pacific Software Engineering Conference
Year: 2014 | Conference Paper |
A large fraction of the time consumed in software development and maintenance is spent on understanding the software, which indicates it is a critical activity. Software documentation, including software architecture design documentation, is an important aid in software comprehension. However, keeping documentation up to date with evolving source code is often challenging and absence of up date or...Show More
Condensing reverse engineered class diagrams through class name based abstraction
Mohd Hafeez Osman;Michel R.V. Chaudron;Peter van der Putten;Truong Ho-Quang
2014 4th World Congress on Information and Communication Technologies (WICT 2014)
Year: 2014 | Conference Paper |
Cited by: Papers (4)
In this paper, we report on a machine learning approach to condensing class diagrams. The goal of the algorithm is to learn to identify what classes are most relevant to include in the diagram, as opposed to full reverse engineering of all classes. This paper focuses on building a classifier that is based on the names of classes in addition to design metrics, and we compare to earlier work that is...Show More
An Analysis of Machine Learning Algorithms for Condensing Reverse Engineered Class Diagrams
2013 IEEE International Conference on Software Maintenance
Year: 2013 | Conference Paper |
Cited by: Papers (36)
There is a range of techniques available to reverse engineer software designs from source code. However, these approaches generate highly detailed representations. The condensing of reverse engineered representations into more high-level design information would enhance the understandability of reverse engineered diagrams. This paper describes an automated approach for condensing reverse engineere...Show More
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