Research

Research

My research area is software engineering. Within this broad research area, I focus on measuring software quality by performing empirical evaluation with regard to SE practices, methods, and tools which could help obtain better software quality. These include employing artificial intelligence techniques to software engineering, particularly machine learning algorithms that deals with issues of how to develop software systems that improve their performance through experience. 

At present I have a major interest in the following research:

• Improving data quality with outlier detection methods/ feature engineering methods/ data profiling methods

• Research related to improve the quality of research data for predictive modeling including investigating techniques, practices and tools for handling imbalance data.

• Understanding the impact of artificial intelligence techniques on software repositories that contain software engineering data, such as source code, execution traces, historical code changes, mailing lists, and bug reports. By applying the machine learning on software repositories, researchers can gain an empirically based understanding of software development practices, and practitioners can better manage, maintain, and evolve complex software projects. Some of the potential research topics are: log engineering, bug detection and vulnerability detection.

• Applying systematic approach in conducting review of literature. For example,  using the systematic literature review (SLR) or systematic mapping studies (SMS) to understand the existing state of evidence in research.

Potential Topics for Final Year Projects

• Bug Prediction Model: Develop a machine learning or deep learning model that predicts potential bugs in software projects based on historical data from bug tracking systems, version control, and code reviews.

• Fault Prediction System with Interactive Visualization of Object-Oriented Metrics: Create a fault prediction system that provides interactive visualizations of object-oriented metrics, allowing developers to explore and analyze the relationships between different metrics and their impact on fault prediction.

• Fault Prediction System with Explainable AI: Develop a fault prediction system that provides explanations for its predictions by highlighting the object-oriented metrics contributing the most to the prediction outcome, thereby enhancing transparency and trustworthiness of the predictions. 

• Automated Code Review System with Fault Prediction Based on Object-Oriented Metrics: Integrate fault prediction based on object-oriented metrics into an automated code review system, allowing developers to receive proactive feedback on potential faults and code quality issues during the code review process.

• Code Recommender System: Build a recommender system that suggests code snippets, libraries, or best practices to developers based on context, project requirements, and similarities to existing code within the repository.

• Code Smell Detection System: Design a system that automatically detects code smells (e.g., duplicated code, long methods, high cyclomatic complexity) in software projects, providing recommendations for refactoring.

• Code Complexity Visualization: Develop a visualization system that visualizes code complexity metrics (e.g., cyclomatic complexity, nesting depth) within the software repository, helping developers identify areas of code that may require refactoring or optimization.

• Code Evolution Visualization: Create a visualization system that illustrates the evolution of source code over time, highlighting key changes, refactorings, and trends to help developers understand the progression of the software project.

 Journal Publication

1. Shah, S.N.S.Z., Rosli, M.M., "Clustering algorithms for analysing electronic medical record: A mapping study ", IAES International Journal of Artificial Intelligence, 2023, 12(4), pp. 1784–1792 

2. J. Edward, M. M. Rosli and A. Seman, "A New Multi-Class Rebalancing Framework for Imbalance Medical Data," in IEEE Access, vol. 11, pp. 92857-92874, 2023, doi: 10.1109/ACCESS.2023.3309732.

3. MM Rosli, M Annamalai, NAM Kasim, C Yung-An, HM Nawawi, "Cross-checked screening application for reliable categorisation of familial hypercholesterolaemia: design and development of the prototype'', IAES International Journal of Artificial Intelligence 12 (2), 704.

4. F Li, M Xu, MM Rosli, "Application of Multi-Modal Neural Networks in Verifying the Authenticity of News Text and Images" , Traitement du Signal 40 (6), 2397

5. Rosli, M.M., Yusop, N.S.M. "Evaluating the Effectiveness of Data Quality Framework in Software Engineering." International Journal of Electrical and Computer Engineering, 2022, 12(6), pp. 6409-6421.

6. Yusuf, A.M.I.A., Rosli, M.M., Yusop, N.S.M." A Screening System for COVID-19 Severity using Machine Learning." International Journal of Advanced Computer Science and Applications, 2022, 13(7), pp. 368-374.

7. Sasha Farhana Shamsul Anwar, Marshima Mohd Rosli, Nur Atiqah Sia Abdullah "Classification of Fault Prediction: A Mapping Study." Pertanika Journal of Science & Technology 30, no.  (2022).

8. Sani, Muhammad Izzuddin Mohd, Nur Atiqah Sia Abdullah, and Marshima Mohd Rosli. "Review on hypertension diagnosis using expert system and wearable devices." International Journal of Electrical and Computer Engineering 12, no. 3 (2022): 3166.

9. Zakariya, Nur Zarna Elya, and Marshima Mohd Rosli. "Physical activity prediction using fitness data: Challenges and issues." Bulletin of Electrical Engineering and Informatics 10, no. 1 (2021): 419-426.

10. Rosli, Marshima Mohd, Jafhate Edward, Marcella Onn, Yung-An Chua, Noor Alicezah Mohd Kasim, and Hapizah Nawawi. "Classifying Familial Hypercholesterolaemia: A Tree-based Machine Learning Approach." International Journal of Advanced Computer Science and Applications 12, no. 9 (2021)

11. Rosli, Marshima Mohd, Nor Shahida Mohamad Yusop, and Aini Sofea Fazuly. "Design of meal intake prediction for gestational diabetes mellitus using genetic algorithm." IAES International Journal of Artificial Intelligence 9, no. 4 (2020): 591.

12. Jamaludin, Muhammad Hamizan, Yap Bee Wah, Hapizah Mohd Nawawi, Chua Yung-An, Marshima Mohd Rosli, and Muthukkaruppan Annamalai. "Classification of Familial Hypercholesterolaemia Using Ordinal Logistic Regression." Pertanika Journal of Science & Technology 28, no. 4 (2020).

13. Nor, N. M., S. S. M. Fauzi, R. Ahmad, and M. M. Rosli. "Modelling lower-level technical dependencies to improve coordination in software engineering projects: A conceptualization." International Journal 9, no. 3 (2020).

14. Adamu, Jibril, Raseeda Hamzah, and Marshima Mohd Rosli. "Security issues and framework of electronic medical record: A review." Bulletin of Electrical Engineering and Informatics 9, no. 2 (2020): 565-572.

15. Rodzman, Shaiful Bakhtiar, Nordin Abu Bakar, Yun-Huoy Choo, Syed Ahmad Aljunid, Normaly Kamal Ismail, Nurazzah Abd Rahman, and Marshima Mohd Rosli. "I-ONAr: A rule-based machine learning approach for intelligent assessment in an online learning environment." Indonesian Journal of Electrical Engineering and Computer Science 17, no. 2 (2020): 1021-1028

16. Rosli, Shuhada Mohd, Marshima Mohd Rosli, and Rosmawati Nordin. "A mapping study on blood glucose recommender system for patients with gestational diabetes mellitus." Bulletin of Electrical Engineering and Informatics 8, no. 4 (2019): 1489-1495

17. Hussin, W. M. H. W., Marshima Mohd Rosli, and Rosmawati Nordin. "Review of traffic control techniques for emergency vehicles." Indonesian Journal of Electrical Engineering and Computer Science (IJEECS) 13, no. 3 (2019): 1243-1251

18. Rosli, Marshima Mohd, Ewan Tempero, and Andrew Luxton-Reilly. "Evaluating the quality of datasets in software engineering." Advanced Science Letters 24, no. 10 (2018): 7232-7239.

19. Halim, Muhammad Zabir Abdul, and Marshima Mohd Rosli. "A Modular and Extensible Framework for Human Resource System." Indonesian Journal of Electrical Engineering and Computer Science 12, no. 2 (2018): 641-647.

20. Annamalai, M., Rosli, M.M., "Software engineering: A pathway to enterprise-strength ontology engineering", International Journal of Digital Content Technology and its Applications, 2012, 6(22), pp. 98–107 

21. Abidin, S.Z.Z., Omar, N., Rahman, H.F.A., Rosli, M.M. ," Investigating the impacts of digital elements in Web information for socio-informatics",  WSEAS Transactions on Communications, 2010, 9(9), pp. 605–614 

 Conference Publication

1. Yahaya, N., Yusop, N.S.M., Rosli, M.M. "The relationship between testers' personalities and their opinions on the importance and difficulties of writing usability defect reports" (2023) AIP Conference Proceedings, 2608, art. no. 020014.

2. Edward, J., Rosli, M.M., Chua, Y.-A., Kasim, N.A.M., Nawawi, H. "Classification Prediction of Familial Hypercholesterolemia using Ensemble-based Classifier with Feature Selection and Rebalancing Technique ", International Conference on ICT Convergence, 2022, 2022-October, pp. 278–283 

3. Edward, Jafhate, and Marshima Mohd Rosli. "A Systematic Mapping Study on Ensemble-Based Classifier." In 2021 IEEE International Conference on Computing (ICOCO), pp. 43-48. IEEE, 2021.

4. Murad, Maisarah Adibah, Nur Atiqah Sia Abdullah, and Marshima Mohd Rosli. "Software Cost Estimation for Mobile Application Development-A Comparative Study of COCOMO Models." In 2021 IEEE 11th International Conference on System Engineering and Technology (ICSET), pp. 106-111. IEEE, 2021.

5. Syafiq, Syamsul, Marshima Mohd Rosli, Maslina Daud, Abdul Fuad Abdul Rahman, Mohd Nasrul Taufiq Salleh, and Farhan Arif Mohamad. "Smart Energy Monitoring System for Residential in Malaysia." In Proceedings of the 3rd International Conference on Big Data and Internet of Things, pp. 18-22. 2019.

6. Syafiq, Syamsul, Abdul Fuad Abdul Rahman, Mohd Nasrul Taufiq Salleh, Farhan Arif Mohamad, Maslina Daud, and Marshima Mohd Rosli. "Comparison on Scorecard and Dashboard in Smart Water Monitoring Application." In Proceedings of the 23rd Conference of Open Innovations Association FRUCT, pp. 549-555. 2018.

7. Rosli, Marshima Mohd, Ewan Tempero, and Andrew Luxton-Reilly. "What is in our datasets? Describing a structure of datasets." In Proceedings of the Australasian Computer Science Week Multiconference, pp. 1-10. 2016.

8. Rosli, Marshima Mohd, Ewan Tempero, and Andrew Luxton-Reilly. "Can we trust our results? a mapping study on data quality." In 2013 20th Asia-Pacific Software Engineering Conference (APSEC), vol. 1, pp. 116-123. IEEE, 2013.

9. M. Annamalai and M. M. Rosli, "Software engineering approach to enterprise-strength ontology engineering," 2011 Malaysian Conference in Software Engineering, 2011, pp. 130-135, doi: 10.1109/MySEC.2011.6140656.

10. M. M. Rosli, N. H. I. Teo, N. S. M. Yusop and N. S. Mohammad, "The design of a software fault prone application using evolutionary algorithm," 2011 IEEE Conference on Open Systems, 2011, pp. 338-343, doi: 10.1109/ICOS.2011.6079246.

11. Rosli, Marshima M., Noor Hasimah Ibrahim Teo, Nor Shahida M. Yusop, and N. Shahriman Mohamad. "Fault prediction model for web application using genetic algorithm." In International conference on computer and software Modeling (IPCSIT), vol. 14, pp. 71-77. 2011.

12. Rahman, H.F.A., Omar, N., Abidin, S.Z.Z., Mahmud, Z., Rosli, M.M.,"Visualizing patterns of online media preference based on young adults lifestyle", Recent Researches in Computer Science - Proceedings of the 15th WSEAS International Conference on Computers, Part of the 15th WSEAS CSCC Multiconference, 2011, pp. 319–323 

13. Rosli, Marshima Mohd, Noor Hasimah Ibrahim Teo, and Nurul Nisa'Khairol Azmi. "Undergraduate student preference activities and sources to learn programming." In 2010 2nd International Congress on Engineering Education, pp. 47-51. IEEE, 2010.

14. Abidin, S.Z.Z., Omar, N., Rahman, H.F.A., Rosli, M.M., "Socio-informatics: Identifying influential factors in digital elements", International Conference on Computers - Proceedings, 2010, 1, pp. 397–402 

Book Chapter

Mohd Rosli, M., Abdullah, N.A.S., Ruzaini, A. (2019). ReciPicker: Recipe recommendation using hybrid filtering for reducing food waste, Frontiers in Artificial Intelligence and Applications, 318, pp. 444-455. 

Research Grant (Principal Investigator)

1. Development of a fully automated classification system of cervical vertebral maturation staging using deep convolutional neural network (PRGS-MOHE, 2023–2025)

2. Data-driven selection model for optimizing active learning method using recommender approach (FRGS-MOHE, 2023–2025)

3. Modelling covid 19 of malaysia patients for effective triage and treatment (MYRA-UiTM, 2020-2023)

4. Data interpretation metamodel for evaluating the quality of data sets (REI-UiTM, 2019-2022)

5. Analytics dataset metamodel for data interpretation with external elements (FRGS-MOHE, 2019-2021)

6. A new noise detection and elimination algorithm for software defect prediction (DANA-UiTM, 2012-2014)

Poster and Extended Abstracts

1. A Alkhateeb, C Yung-An, M Mohd Rosli, H Mohd Nawawi, "Agreement between the various familial hypercholesterolaemia diagnostic criteria in Malaysian population", Atherosclerosis, 331 (2021)

2. A Alkhateeb, C Yung An, NA Mohd Kasim, M Mohd Rosli, H Mohd Nawawi, "Lower lipoprotein (a) serum levels among an Asian native community compared to the European population", Atherosclerosis, 331 (2021)

3. M Mohd Rosli, M Annamalai, YA Chua, NA Mohd Kasim, AS Ramli, H Mohd Nawawi , "FH CatScreen: computer-based familial hypercholesterolemia (FH) screening and categorisation application based on various FH diagnostic criteria", Atherosclerosis, 315, (2020), pp. e174-e175