@ARTICLE{Sakti14-TSE-JTExpert,
   AUTHOR       = {Abdelilah Sakti and Gilles Pesant and 
      Yann-Ga�l Gu�h�neuc},
   JOURNAL      = {Transactions on Software Engineering (TSE)},
   TITLE        = {Instance Generator and Problem Representation to Improve 
      Object Oriented Code Coverage},
   YEAR         = {2014},
   MONTH        = {October},
   NOTE         = {22 pages.},
   NUMBER       = {99},
   PAGES        = {1--22},
   VOLUME       = {40},
   EDITOR       = {Matthew B. Dwyer},
   KEYWORDS     = {Topic: <b>Test case generation</b>, Venue: <b>TSE</b>},
   PUBLISHER    = {IEEE CS Press},
   URL          = {http://www.ptidej.net/publications/documents/TSE14b.doc.pdf},
   ABSTRACT     = {Search-based approaches have been extensively applied to 
      solve the problem of software test-data generation. Yet, testdata 
      generation for object-oriented programming (OOP) is challenging due 
      to the features of OOP, e.g., abstraction, encapsulation, and 
      visibility that prevent direct access to some parts of the source 
      code. To address this problem we present a new automated search-based 
      software test-data generation approach that achieves high code 
      coverage for unit-class testing. We first describe how we structure 
      the test-data generation problem for unit-class testing to generate 
      relevant sequences of method calls. Through a static analysis, we 
      consider only methods or constructors changing the state of the 
      class-under-test or that may reach a test target. Then we introduce a 
      generator of instances of classes that is based on a family of 
      means-of-instantiation including subclasses and external factory 
      methods. It also uses a seeding strategy and a diversification 
      strategy to increase the likelihood to reach a test target. Using a 
      search heuristic to reach all test targets at the same time, we 
      implement our approach in a tool, JTExpert, that we evaluate on more 
      than a hundred Java classes from different open-source libraries. 
      JTExpert gives better results in terms of search time and code 
      coverage than the state of the art, EvoSuite, which uses traditional 
      techniques.}
}

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Yet, testdata generation for object-oriented programming (OOP) is challenging due to the features of OOP, e.g., abstraction, encapsulation, and visibility that prevent direct access to some parts of the source code. To address this problem we present a new automated search-based software test-data generation approach that achieves high code coverage for unit-class testing. We first describe how we structure the test-data generation problem for unit-class testing to generate relevant sequences of method calls. Through a static analysis, we consider only methods or constructors changing the state of the class-under-test or that may reach a test target. Then we introduce a generator of instances of classes that is based on a family of means-of-instantiation including subclasses and external factory methods. It also uses a seeding strategy and a diversification strategy to increase the likelihood to reach a test target. Using a search heuristic to reach all test targets at the same time, we implement our approach in a tool, JTExpert, that we evaluate on more than a hundred Java classes from different open-source libraries. JTExpert gives better results in terms of search time and code coverage than the state of the art, EvoSuite, which uses traditional techniques.","bibtex":"@ARTICLE{Sakti14-TSE-JTExpert,\r\n AUTHOR = {Abdelilah Sakti and Gilles Pesant and \r\n Yann-Ga�l Gu�h�neuc},\r\n JOURNAL = {Transactions on Software Engineering (TSE)},\r\n TITLE = {Instance Generator and Problem Representation to Improve \r\n Object Oriented Code Coverage},\r\n YEAR = {2014},\r\n MONTH = {October},\r\n NOTE = {22 pages.},\r\n NUMBER = {99},\r\n PAGES = {1--22},\r\n VOLUME = {40},\r\n EDITOR = {Matthew B. Dwyer},\r\n KEYWORDS = {Topic: <b>Test case generation</b>, Venue: <b>TSE</b>},\r\n PUBLISHER = {IEEE CS Press},\r\n URL = {http://www.ptidej.net/publications/documents/TSE14b.doc.pdf},\r\n ABSTRACT = {Search-based approaches have been extensively applied to \r\n solve the problem of software test-data generation. Yet, testdata \r\n generation for object-oriented programming (OOP) is challenging due \r\n to the features of OOP, e.g., abstraction, encapsulation, and \r\n visibility that prevent direct access to some parts of the source \r\n code. To address this problem we present a new automated search-based \r\n software test-data generation approach that achieves high code \r\n coverage for unit-class testing. We first describe how we structure \r\n the test-data generation problem for unit-class testing to generate \r\n relevant sequences of method calls. 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