Context: API growth is accelerating. RESTful APIs are gaining traction and are backed by major players. Extending the APIs commonly introduce antipatterns, which are bad solutions to problems. Objective: The purpose of this review is to identify and analyze the current, state-of-the-art approaches in detecting antipatterns in RESTful APIs. Method: Six research questions are clearly defined. Search strings are used in digital libraries to identify studies in the field of antipatterns in RESTful APIs. The studies must come from reputable sources. Studies are subjected to inclusion-exclusion and quality assessment. Results: Eight studies were selected. Each study has one main approach. Three classes were created to identify the types of approaches. All approaches require expert domain knowledge to apply and vary in the difficulty of application. The accuracy of the approaches is above 80\%. Four types of antipatterns were identified and the approaches detect one or multiple types of antipatterns. Conclusion: Various techniques were discovered, each selected study presented a single technique. Classifications for the techniques and antipatterns were made. The research field is young with future work planned.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:lnu-114232 |
| Date | January 2022 |
| Creators | Neagu, Andrei |
| Publisher | Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM) |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
Page generated in 0.0017 seconds