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All Journal Journal of Software Engineering, Information and Communication Technology The Indonesian Journal of Computer Science
Kabarungi, Moreen
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Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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An Empirical Analysis of Code Smell in Eclipse Framework Ecosystem Kawuma, Simon; Mabberi, Enock; Sabiiti, David; Kabarungi, Moreen; Kalungi, Dickson; Nabaasa, Evarist
Journal of Software Engineering, Information and Communication Technology (SEICT) Vol 6, No 1: June 2025
Publisher : Universitas Pendidikan Indonesia (UPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/seict.v6i1.76200

Abstract

Eclipse Framework developers claim that public APIs are supported whereas internal APIs are unsupported. However, there is no guarantee that these interfaces are well-tested because several code smells are reported by interface users. Applications that use code-smelly interfaces risk failing if the code-smell are not fixed.  Previous research revealed that not all code smells can be resolved and fixed within a short period. Thus, interface users have to fix the code smells themselves or abandon that particular interface. To avoid waiting indefinitely for solutions from interface developers or getting involved in code smell fixing, users should use code-smell-free interfaces. However, interface users may not be aware of the existence   of code smell-free interfaces in the Eclipse framework. In this research   study, we used SonarQube tool to carry out an empirical investigation on 28 major Eclipse releases to establish the existence of code-smell- free interfaces. We provide a data set of 218K and 321K code-smell-free public APIs and internal APIs classes respectively. Also, we discovered that on average, 36.1% and 57.2% of the total interfaces in a given Eclipse release are code smell-free public APIs and internal APIs respectively in all the studied Eclipse releases. Furthermore, we have discovered that the number of code smells linearly increases as the Eclipse framework evolves. The average number of code smell and technical Debt is 147K and 2,744 days in all the studied Eclipse releases.  Results from this study can be used by both interface providers and users as a starting point to know tested interfaces and also estimate efforts needed to fix code smells in Eclipse Frameworks.
Developing a Campus Blended Learning Framework to Improve Adoption in Higher Educational Institutions in Southwestern Uganda Kabarungi, Moreen; Ntwari Richard; Annabella Habinka Ejiri; Kawuma Simon
The Indonesian Journal of Computer Science Vol. 14 No. 5 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i5.5026

Abstract

Despite the potential benefits of blended learning in higher education, adoption rates in Ugandan universities remain critically low at 29.1%, with significant barriers including inadequate infrastructure, limited institutional support, and mental health challenges affecting both educators and students. This study aimed to develop a Campus Blended Learning Framework (CBLF) to improve blended learning adoption in higher educational institutions in southwestern Uganda. A Design Science Research methodology was employed, incorporating both quantitative and qualitative approaches. Data were collected from three universities: Mbarara University of Science and Technology (MUST), Bishop Stuart University (BSU), and Kabale University (KAB). A total of 1,495 participants (1,051 students and 444 staff members) were surveyed using structured questionnaires based on the Complex Adaptive Blended Learning Framework (CABLF). Ten experts participated in qualitative interviews to evaluate the framework's usability and acceptability. The study identified six critical components for effective blended learning adoption: pedagogy, infrastructure, content, assessment, support, and mental health. Mental health emerged as a significant factor influencing all other components. The proposed CBLF integrates these elements while addressing the unique contextual challenges of developing countries. The Campus Blended Learning Framework provides a comprehensive approach to addressing low adoption rates of blended learning in southwestern Uganda's higher educational institutions. The framework's emphasis on mental health support and contextual adaptation makes it particularly suitable for developing country contexts.
Design and Implementation of mHealth-Based Early Warning Systems for Heart Disease: A Scoping Review Ntwari, Richard; Wesonga, Bob; Vallence Ngabo Maniragaba; Engwau, Tonny; Kabarungi, Moreen
The Indonesian Journal of Computer Science Vol. 14 No. 6 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i6.5051

Abstract

Cardiovascular diseases (CVDs) remain the leading cause of mortality globally, with sub-Saharan Africa including Uganda experiencing a growing burden due to limited access to early detection and specialist care. In response, mobile health (mHealth) technologies have emerged as promising tools to support early cardiac risk detection and intervention, especially in low-resource settings. Following Arksey and O’Malley’s scoping review framework with enhancements a systematic search was conducted across five databases from January 2000 to April 2025. Studies were screened and selected based on predefined inclusion criteria, and data were charted across design elements, outcomes, and implementation contexts. Thematic analysis was applied to synthesize findings.Twenty-seven studies met the inclusion criteria. mHealth-based EWS frequently incorporate wearable sensors, mobile apps, and AI-driven analytics for real-time monitoring and risk prediction. While user-centered design enhances acceptability, clinical efficacy evidence is mixed and scalability remains under-explored. AI/ML integration shows promise in improving prediction and personalization, but challenges persist around interoperability and health system integration.mHealth-based early warning systems hold significant potential to address cardiovascular care gaps in resource-limited settings. To maximize impact, future interventions should prioritize clinical validation, adaptive AI integration, and sustainable scale-up models tailored to local infrastructure and user needs. These insights are critical for guiding policymakers, developers, and researchers toward more effective digital health strategies for CVD prevention.
Co-Authors Annabella Habinka Ejiri Engwau, Tonny Kalungi, Dickson Kawuma Simon Kawuma, Simon Mabberi, Enock Nabaasa, Evarist Ntwari Richard Ntwari, Richard Sabiiti, David Vallence Ngabo Maniragaba Wesonga, Bob