Paper  abstract   bibtex   

@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.}
}