Detecting Design Level Anti-patterns; Structure and Semantics in UML Class Diagrams

  title={Detecting Design Level Anti-patterns; Structure and Semantics in UML Class Diagrams},
  author={Eman K. Elsayed and Enas E. El-Sharawy},
  journal={J. Comput.},
Nowadays generation of reliable patterns is a challenge in the software engineering field, so determination of the anti-patterns becomes an effective and objective concept to evaluate any design. This paper proposes a general method to detect anti-patterns; structure and semantics in case of UML(Unified modeling language) class diagram. The proposed method is classified as a hybrid between mathematical and meta-model approaches. Its four phases merge between OWL(Web Ontology Language… 
An Automatic Generation of Domain Ontologies Based on an MDA Approach to Support Big Data Analytics
This chapter proposes a new methodology for the automatic generation of domain ontologies to support big data analytics by transforming UML class diagrams to domain ontology in PSM level through ODM, which is an OMG standard for ontology modeling.
This research pursuit to present database in the formal method and acquire demonstrated and automatic Event-B code that guided by the Student enrolment case study, using the validation in UML-B and verification approach with the RODIN platform tool.
Combining UML and ontology: An exploratory survey
Verification and Validation of UML/OCL Object Componenets Models
This document breaches copyright and will be removed from access immediately and investigate the claim.


Detection, Simulation and Elimination of Semantic Anti-patterns in Ontology-Driven Conceptual Models
The paper presents a tool that is able to automatically identify anti-patterns in user’s models, provide visualization for its consequences, and generate corrections to these models by the automatic inclusion of OCL constraints.
An approach to design pattern and anti-pattern detection in mof-based modeling languages
This thesis proposes a new unified approach to detecting both kinds of patterns for MOF-based modeling languages, an increasingly important standard that is used to define many popular modeling languages today, including UML, BPMN and SysML.
A Metric-Based Approach for Anti-pattern Detection in UML Designs
This work proposes an approach that identifies anti-patterns in UML designs through the use of existing and newly defined quality metrics and examines structural and behavioral information through the class and sequence diagrams.
UML Specification and Correction of Object-Oriented Anti-patterns
  • M. T. Llano, R. Pooley
  • Computer Science
    2009 Fourth International Conference on Software Engineering Advances
  • 2009
This work defines a UML-based specification of anti-patterns and establishes design transformations for their correction and expects to open up the possibility to automate the detection and correction of these kinds of software defects.
Detecting patterns and antipatterns in software using Prolog rules
This article proposes detection methods for a set of patterns and antipatterns, using a logic-based approach and defines with help of Prolog predicates both structural and behavioural aspects of patternsand antipatters.
SMURF: A SVM-based Incremental Anti-pattern Detection Approach
SMURF, a novel approach to detect anti-patterns, based on a machine learning technique - support vector machines - and taking into account practitioners' feedback is introduced, showing that the accuracy of SMURF is greater than that of DETEX and BDTEX when detecting anti- patterns occurrences.
Anti-pattern Mutations and Fault-proneness
This paper presents results from an empirical study aimed at understanding the evolution of anti-patterns in 27 releases of three open-source software systems: ArgoUML, Mylyn, and Rhino, and identifies some mutations that are more risky in terms of fault-proneness.
Software project management anti-patterns
A Systematic Approach to Atomicity Decomposition in Event-B
A systematic definition of the atomicity decomposition approach is outlined, the tool that supports it is developed and the contribution that the tool makes is evaluated.
Learning and inferencing in user ontology for personalized Semantic Web search