Detection of REST Patterns and Antipatterns: A Heuristics-Based Approach

REST

(REpresentational State Transfer), relying on

resources

as its architectural unit, is currently a popular architectural choice for building Web-based applications. It is shown that

design patterns

—good solutions to recurring design problems—improve the design quality and facilitate maintenance and evolution of software systems.

Antipatterns

, on the other hand, are poor and counter-productive solutions. Therefore, the detection of

REST

(anti)patterns is essential for improving the maintenance and evolution of

RESTful

systems. Until now, however, no approach has been proposed. In this paper, we propose

SODA-R

(Service Oriented Detection for Antipatterns in

REST

), a heuristics-based approach to detect (anti)patterns in

RESTful

systems. We define detection heuristics for eight

REST

antipatterns and five patterns, and perform their detection on a set of 12 widely-used

REST

APIs

including BestBuy, Facebook, and DropBox. The results show that

SODA-R

can perform the detection of

REST

(anti)patterns with high accuracy. We also found that Twitter and DropBox are not well-designed,

i.e.

, contain more antipatterns. In contrast, Facebook and BestBuy are well-designed,

i.e.

, contain more patterns and less antipatterns.