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

Detection of REST Patterns and Antipatterns: A Heuristics-based Approach. Palma, F., Dubois, J., Moha, N., & Gu�h�neuc, Y. In Franch, X., Ghose, A., & Lewis, G., editors, Proceedings of the 12th International Conference on Service Oriented Computing (ICSOC), pages 230–244, November, 2014. Springer. 15 pages.

Paper abstract bibtex

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, DropBox, and Alchemy are not well-designed, i.e., contain more antipatterns. In contrast, Facebook, BestBuy, and YouTube are well-designed, i.e., contain more patterns and less antipatterns.

@INPROCEEDINGS{Palma14-ICSOC-SOAAntiPatternsWebServices,
   AUTHOR       = {Francis Palma and Johann Dubois and Naouel Moha and 
      Yann-Ga�l Gu�h�neuc},
   BOOKTITLE    = {Proceedings of the 12<sup>th</sup> International Conference on Service Oriented Computing (ICSOC)},
   TITLE        = {Detection of REST Patterns and Antipatterns: A 
      Heuristics-based Approach},
   YEAR         = {2014},
   OPTADDRESS   = {},
   OPTCROSSREF  = {},
   EDITOR       = {Xavier Franch and Aditya Ghose and Grace Lewis},
   MONTH        = {November},
   NOTE         = {15 pages.},
   OPTNUMBER    = {},
   OPTORGANIZATION = {},
   PAGES        = {230&ndash;244},
   PUBLISHER    = {Springer},
   OPTSERIES    = {},
   OPTVOLUME    = {},
   KEYWORDS     = {Topic: <b>Code and design smells</b>, 
      Rubrique : <b>mauvaises pratiques</b>, Conference: ICSOC},
   URL          = {http://www.ptidej.net/publications/documents/ICSOC14.doc.pdf},
   PDF          = {http://www.ptidej.net/publications/documents/ICSOC14.ppt.pdf},
   ABSTRACT     = {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&mdash;good solutions to recurring design 
      problems&mdash;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, DropBox, and Alchemy are not well-designed, 
      i.e., contain more antipatterns. In contrast, Facebook, BestBuy, and 
      YouTube are well-designed, i.e., contain more patterns and less 
      antipatterns.}
}

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