Paper  abstract   bibtex   

@ARTICLE{Brabra19-IST-SemanticDetectionCloudAPI,
   AUTHOR       = {Hayet Brabra and Achraf Mtibaa and Fabio Petrillo and 
      Philippe Merle and Layth Sliman and Naouel Moha and Walid Gaaloul and 
      Yann-Ga�l Gu�h�neuc and Boualem Benatallah and Fa�ez Gargouri},
   JOURNAL      = {Information and Software Technology (IST)},
   TITLE        = {On the Semantic Detection of Cloud API (Anti)Patterns},
   YEAR         = {2019},
   MONTH        = {March},
   NOTE         = {17 pages.},
   NUMBER       = {3},
   PAGES        = {65--82},
   VOLUME       = {107},
   EDITOR       = {Claes Wohlin},
   KEYWORDS     = {Topic: <b>Design patterns</b>, 
      Topic: <b>Code and design smells</b>, Venue: <b>IST</b>},
   PUBLISHER    = {Elsevier},
   URL          = {http://www.ptidej.net/publications/documents/IST18.doc.pdf},
   ABSTRACT     = {\textit{Context.} Open standards are urgently needed for 
      enabling software interoperability in Cloud Computing. Open Cloud 
      Computing Interface (OCCI) provides a set of best design principles 
      to create interoperable REST management APIs. Although OCCI is the 
      only standard addressing the management of any kind of cloud 
      resources, it does not support a range of best principles related to 
      REST design. This often worsens REST API quality by decreasing their 
      understandability and reusability. \textit{Objective.} We aim at 
      assisting cloud developers to enhance their REST management APIs by 
      providing a compliance evaluation of OCCI and REST best principles 
      and a recommendation support to comply with these principles. 
      \textit{Method.} First, we leverage patterns and anti-patterns to 
      drive respectively the good and poor practices of OCCI and REST best 
      principles. Then, we propose a semantic-based approach for defining 
      and detecting REST and OCCI (anti)patterns and providing a set of 
      correction recommendations to comply with both REST and OCCI best 
      principles. We validated this approach by applying it on cloud REST 
      APIs and evaluating its accuracy, usefulness and extensibility. 
      \textit{Results.} We found that our approach accurately detects OCCI 
      and REST(anti)patterns and provides useful recommendations. According 
      to the compliance results, we reveal that there is no widespread 
      adoption of OCCI principles in existing APIs. In contrast, these APIs 
      have reached an acceptable level of maturity regarding REST 
      principles. \textit{Conclusion.} Our approach provides an effective 
      and extensible technique for defining and detecting OCCI and REST 
      (anti)patterns in Cloud REST APIs. Cloud software developers can 
      benefit from our approach and defined principles to accurately 
      evaluate their APIs from OCCI and REST perspectives. This contributes 
      in designing interoperable, understandable, and reusable Cloud 
      management APIs. Thank to the compliance analysis and the 
      recommendation support, we also contribute to improving these APIs, 
      which make them more straightforward.}
}