Are RESTful APIs Well-designed? Detection of Their Linguistic (Anti)Patterns

Are RESTful APIs Well-designed? Detection of Their Linguistic (Anti)Patterns. Palma, F., Gonzalez-Huerta, J., Moha, N., Gu�h�neuc, Y., & Tremblay, G. In Barros, A., Grigori, D., & Narendra, N., editors, Proceedings of the 13th International Conference on Service Oriented Computing (ICSOC), pages 171–187, November, 2015. Springer. 16 pages.

Paper abstract bibtex

Identifier lexicon has a direct impact on software understandability and reusability and, thus, on the quality of the final software product. Understandability and reusability are two important characteristics of software quality. REST (REpresentational State Transfer) style is becoming a de facto standard adopted by many software organisations. The use of proper lexicon in RESTful APIs might make them easier to understand and reuse by client developers, and thus, would ease their adoption. Linguistic antipatterns represent poor practices in the naming, documentation, and choice of identifiers in the APIs as opposed to linguistic patterns that represent best practices. We present the DOLAR approach (Detection Of Linguistic Antipatterns in REST), which applies syntactic and semantic analyses for the detection of linguistic (anti)patterns in RESTful APIs. We provide detailed definitions of ten (anti)patterns and define and apply their detection algorithms on 15 widely-used RESTful APIs, including Facebook, Twitter, and YouTube. The results show that DOLAR can indeed detect linguistic (anti)patterns with high accuracy and that they do occur in major RESTful APIs.

@INPROCEEDINGS{Palma15-ICSOC-RESTLinguisticAPs,
   AUTHOR       = {Francis Palma and Javier Gonzalez-Huerta and Naouel Moha and 
      Yann-Ga�l Gu�h�neuc and Guy Tremblay},
   BOOKTITLE    = {Proceedings of the 13<sup>th</sup> International Conference on Service Oriented Computing (ICSOC)},
   TITLE        = {Are RESTful APIs Well-designed? Detection of Their 
      Linguistic (Anti)Patterns},
   YEAR         = {2015},
   OPTADDRESS   = {},
   OPTCROSSREF  = {},
   EDITOR       = {Alistair Barros and Daniela Grigori and N.C. Narendra},
   MONTH        = {November},
   NOTE         = {16 pages.},
   OPTNUMBER    = {},
   OPTORGANIZATION = {},
   PAGES        = {171--187},
   PUBLISHER    = {Springer},
   OPTSERIES    = {},
   OPTVOLUME    = {},
   KEYWORDS     = {Topic: <b>Code and design smells</b>, 
      Venue: <c>ICSOC</c>},
   URL          = {http://www.ptidej.net/publications/documents/ICSOC15.doc.pdf},
   PDF          = {http://www.ptidej.net/publications/documents/ICSOC15.ppt.pdf},
   ABSTRACT     = {Identifier lexicon has a direct impact on software 
      understandability and reusability and, thus, on the quality of the 
      final software product. Understandability and reusability are two 
      important characteristics of software quality. REST (REpresentational 
      State Transfer) style is becoming a de facto standard adopted by many 
      software organisations. The use of proper lexicon in RESTful APIs 
      might make them easier to understand and reuse by client developers, 
      and thus, would ease their adoption. Linguistic antipatterns 
      represent poor practices in the naming, documentation, and choice of 
      identifiers in the APIs as opposed to linguistic patterns that 
      represent best practices. We present the DOLAR approach (Detection Of 
      Linguistic Antipatterns in REST), which applies syntactic and 
      semantic analyses for the detection of linguistic (anti)patterns in 
      RESTful APIs. We provide detailed definitions of ten (anti)patterns 
      and define and apply their detection algorithms on 15 widely-used 
      RESTful APIs, including Facebook, Twitter, and YouTube. The results 
      show that DOLAR can indeed detect linguistic (anti)patterns with high 
      accuracy and that they do occur in major RESTful APIs.}
}

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