Automated Test Scenario Selection Based on Levenshtein Distance

Specification based testing involves generating test cases from the specification, here, UML. The number of automatically generated test scenarios from UML activity diagrams is large and hence impossible to test completely. This paper presents a method for selection of test scenarios generated from activity diagrams using Levenshtein distance. An activity diagram is transformed into a directed graph representing the sequence of activities. A modified Depth First Algorithm(DFS) is applied to obtain test scenarios. Levenshtein distance is calculated between the scenarios thus generated. The objective is to select the less similar test cases and at the same time provide maximum coverage.

[1]  Patrícia Duarte de Lima Machado,et al.  Automated Test Case Selection Based on a Similarity Function , 2007, GI Jahrestagung.

[2]  Bertrand Meyer,et al.  Object distance and its application to adaptive random testing of object-oriented programs , 2006, RT '06.

[3]  Gregg Rothermel,et al.  Test Case Prioritization: A Family of Empirical Studies , 2002, IEEE Trans. Software Eng..

[4]  Juan C. Burguillo,et al.  Heuristic-Driven Test Case Selection from Formal Specifications. A Case Study , 2002, FME.

[5]  Alan Bundy,et al.  Constructing Induction Rules for Deductive Synthesis Proofs , 2006, CLASE.

[6]  Peter A. Lindsay,et al.  FME 2002:Formal Methods—Getting IT Right , 2002, Lecture Notes in Computer Science.

[7]  Mark Harman,et al.  Pareto efficient multi-objective test case selection , 2007, ISSTA '07.

[8]  Li Xuandong,et al.  Automatic test case generation for UML activity diagrams , 2006 .

[9]  Gregg Rothermel,et al.  A safe, efficient regression test selection technique , 1997, TSEM.

[10]  Yanping Chen,et al.  Specification-based regression test selection with risk analysis , 2002, CASCON.

[11]  Robert G. Merkel,et al.  Proceedings of the 1st international workshop on Random testing , 2006 .

[12]  Jean-Marc Jézéquel,et al.  ≪UML≫ 2002 — The Unified Modeling Language , 2002, Lecture Notes in Computer Science.

[13]  Tsong Yueh Chen,et al.  Adaptive Random Testing , 2004, ASIAN.

[14]  Juan C. Burguillo,et al.  Heuristic-driven Techniques for Test Case Selection , 2002, FMICS.

[15]  Wilkerson de L. Andrade,et al.  LTS-BT: a tool to generate and select functional test cases for embedded systems , 2008, SAC '08.

[16]  Laurie A. Williams,et al.  On the economics of requirements-based test case prioritization , 2005, ACM SIGSOFT Softw. Eng. Notes.

[17]  Gregg Rothermel,et al.  Prioritizing test cases for regression testing , 2000, ISSTA '00.

[18]  Sungwon Kang,et al.  Test Cases Generation from UML Activity Diagrams , 2007 .

[19]  Mingsong Chen,et al.  Coverage-driven automatic test generation for uml activity diagrams , 2008, GLSVLSI '08.

[20]  Hrushikesha Mohanty,et al.  Prioritization of Scenarios Based on UML Activity Diagrams , 2009, 2009 First International Conference on Computational Intelligence, Communication Systems and Networks.

[21]  Hrushikesha Mohanty,et al.  Automated Scenario Generation Based on UML Activity Diagrams , 2008, 2008 International Conference on Information Technology.

[22]  Eda Marchetti,et al.  The Cow_Suite Approach to Planning and Deriving Test Suites in UML Projects , 2002, UML.

[23]  Gregg Rothermel,et al.  Analyzing Regression Test Selection Techniques , 1996, IEEE Trans. Software Eng..

[24]  Gregg Rothermel,et al.  Test case prioritization , 2004 .

[25]  Vladimir I. Levenshtein,et al.  Binary codes capable of correcting deletions, insertions, and reversals , 1965 .