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Journal : journal of information technology and computer science

Identifying Thresholds for Similarity-Based Class Cohesion (SCC) Metrics Pradana, Fajar; Priyambadha, Bayu; Rusdianto, Denny Sagita
Journal of Information Technology and Computer Science Vol. 1 No. 2: November 2016
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (757.414 KB) | DOI: 10.25126/jitecs.20161213

Abstract

Abstract. The object-oriented design (OOD) concept can be used to implement a quality measurement program is based on the possibility of inter-relationship between attributes and methods in the class diagram and interaction between objects on a communication diagram. The process of calculating the value of cohesion on the design of object-oriented software using Similarity-Based Class Cohesion metrics can be done by identifying the relationship between the three types of possible interaction between those methods, method-attribute, and interaction attribute-attribute. But the existence of such measurements theory is rarely used in the software development industry. This is due to there is no threshold value that is used as the limit of good or bad design. This study aims to determine the threshold of cohesion metric based on the class diagram. The result showed that the threshold of SCC metric is 0.45. 0.45 is the value that has the highest level of agreement with the design expert
Challenges in Developing Sequence Diagrams (UML) Kurniawan, Tri Astoto; Lê, Lam-Son; Priyambadha, Bayu
Journal of Information Technology and Computer Science Vol. 5 No. 2: August 2020
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1682.638 KB) | DOI: 10.25126/jitecs.202052216

Abstract

During the object-oriented software design phase, the designers have to describe the dynamic aspect of the system under development through the most common interaction diagram variant in UML 2.0, i.e. sequence diagrams. Some novice designers, including undergraduate and postgraduate students, suffer from making inappropriate models due to insufficiently detailed guidance required to develop such sequence diagrams. This paper classifies some potential mistakes which are likely performed by such novice designers, and discusses the corresponding corrections. We summarized such mistakes based on our long experiences in teaching software modeling classes as well as software analysis and design classes. There were classified twenty-one potential mistakes with respect to the syntactical and semantical correctness of the developed models. It is concluded that novice designers have to be aware and take into account the identified mistakes in such a way they can produce correct sequence diagrams.
Detection of God Class Smells in PHP Systems Using Object-Oriented Metrics Toofani, Naveed; Priyambadha, Bayu; Arwan, Achmad
Journal of Information Technology and Computer Science Vol. 11 No. 2: August 2026
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jitecs.2026112892

Abstract

Software maintainability becomes difficult when object-oriented systems contain God Class code smells, where a single class handles excessive responsibilities and controls large portions of system behavior. Most existing God Class detection approaches use metric thresholds developed for statically typed languages such as Java, which may not accurately represent the architectural characteristics of dynamically typed PHP systems. This problem can reduce software maintainability, increase system complexity, and complicate future development and testing activities. This study applies a quantitative empirical research approach to evaluate metric-based God Class detection in PHP systems. Twelve open-source PHP projects containing 7,866 classes were collected from GitHub and analyzed using the PDepend static analysis tool. The extracted object-oriented metrics included Weighted Methods per Class (WMC), Number of Public Methods (NPM), Depth of Inheritance Tree (DIT), and Lines of Code (LOC). A class was classified as a God Class when at least three out of four threshold values were exceeded. The detection results were validated using statistical analysis, K-Means clustering, machine learning consistency validation, PHPMD comparison, and expert manual validation. The results identified 421 God Classes and showed that WMC, NPM, and LOC are strong indicators of God Class behavior in PHP systems, while DIT has lower influence due to framework-based inheritance structures. The study demonstrates that metric-based detection can effectively identify maintainability problems in PHP applications and provides a foundation for future PHP-specific threshold development.