Tag: metrics

Unveiling Hybrid Cyclomatic Complexity: A Comprehensive Analysis and Evaluation as an Integral Feature in Automatic Defect Prediction Models (2025)

arXiv.org Authors L. Cernau, L. Dioşan, Camelia Serban Abstract The complex software systems developed nowadays require assessing their quality and proneness to errors. Reducing code complexity is a never-ending problem, especially in today’s fast pace of software systems development. Therefore, the industry needs to find a method to determine the qualities of a software…

Textural analysis and artificial intelligence as decision support tools in the diagnosis of multiple sclerosis – a systematic review (2025)

Frontiers in Neuroscience Authors Filip Orzan, Ș. Iancu, L. Dioşan, Z. Bálint Abstract Introduction Magnetic resonance imaging (MRI) is conventionally used for the detection and diagnosis of multiple sclerosis (MS), often complemented by lumbar puncture—a highly invasive method—to validate the diagnosis. Additionally, MRI is periodically repeated to monitor disease progression and treatment efficacy. Recent…

Challenges in Software Metrics Adoption: Insights from Cluj-Napoca’s Development Community (2025)

International Conference on Evaluation of Novel Approaches to Software Engineering Authors L. Cernau, L. Dioşan, Camelia Serban Abstract Established research directions yield concrete outcomes on the benefits of using software metrics in software development processes, such as notable correlations between software metric values and various quality attributes of software systems or defect prediction. A…

A pedagogical approach in interleaving software quality concerns at an artificial intelligence course (2022)

EASEAI@ESEC/SIGSOFT FSE Authors L. Cernau, L. Dioşan, C. Serban Abstract The software engineering industry is an everchanging domain requiring professionals to have a good knowledge base and adaptability skills.Artificial Intelligence (AI) has achieved substantial success in enhancing program analysis techniques and applications, including bug prediction. It is a promising direction by applying advanced Machine…

A Hybrid Complexity Metric in Automatic Software Defects Prediction (2022)

International Conference on Software and Data Technologies Authors L. Cernau, L. Dioşan, C. Serban Abstract Nowadays, software systems evolve in vast and complex applications. In such a complex system, a minor change in one part may have unexpected degradation of the software system design, leading to an unending chain of bugs and defects. Therefore,…

On the use of evolutionary algorithms for test case prioritization in regression testing considering requirements dependencies (2021)

AISTA@ISSTA Authors A. Vescan, Camelia Chisalita-Cretu, C. Serban, L. Dioşan Abstract Nowadays, software systems encounter repeated modifications in order to satisfy any requirement regarding a business change. To assure that these changes do not affect systems' proper functioning, those parts affected by the changes need to be retested, minimizing the negative impact of performed…

A Validation Framework for ARP Similarity Measure (2021)

International Conference on Machine Learning and Applications Authors Sergiu Limboi, Mara Deac-Petrusel Abstract In the last years, a wide range of new similarity measures has been designed and applied to different contexts. Currently, there’s a deep lack in the validation and evaluation steps for novel similarities. In general, new measures are validated mostly through…