An Empirical Study to investigate the Effectiveness of Different Variants of SMOTE for Improving Web Service Anti-Patterns Prediction
| Autor: | Sahithi Tummalapalli, Santanu Kumar Rath, Lalita Bhanu Murthy, Lov Kumar |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Service (systems architecture)
Source code business.industry Computer science media_common.quotation_subject Information technology 020206 networking & telecommunications 020207 software engineering 02 engineering and technology computer.software_genre Software Empirical research 0202 electrical engineering electronic engineering information engineering Quality (business) Software system Web service Software engineering business computer media_common |
| Zdroj: | ISEC |
| Popis: | In today’s world, IT professionals must ensure that all enterprise applications are running smoothly and are communicating with each other. Service-Oriented Architecture(SOA) provides the organization with a framework that makes the management of information technology systems affordable and manageable. Service-Based Systems(SBS) need to adapt themselves over time to fit in the new client prerequisites. These outcomes in the weakening of the software systems quality and plan and may cause the emergence of poor solutions called Anti-patterns. An anti-pattern is a repeated application of code or design that leads to a bad outcome. The research uncovered that the presence of anti-patterns thwarts the software systems advancement and maintenance. The early prediction of these anti-pattern using extracted features from source code helps to reduce the software system’s maintenance and enhance the quality of the software. This present work’s ideology is to investigate the viability of different data sampling technique variants empirically and the machine learning technique, Naive Bayes, in the anti-patterns prediction in web services. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|