Open Access   Article Go Back

Generating Optimized Test Case from UML Diagram Using Meta-Heuristic Algorithm

Preeti 1 , Rohit Goyal2

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-6 , Page no. 1177-1183, Jun-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i6.11771183

Online published on Jun 30, 2019

Copyright © Preeti, Rohit Goyal . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: Preeti, Rohit Goyal, “Generating Optimized Test Case from UML Diagram Using Meta-Heuristic Algorithm,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.1177-1183, 2019.

MLA Style Citation: Preeti, Rohit Goyal "Generating Optimized Test Case from UML Diagram Using Meta-Heuristic Algorithm." International Journal of Computer Sciences and Engineering 7.6 (2019): 1177-1183.

APA Style Citation: Preeti, Rohit Goyal, (2019). Generating Optimized Test Case from UML Diagram Using Meta-Heuristic Algorithm. International Journal of Computer Sciences and Engineering, 7(6), 1177-1183.

BibTex Style Citation:
@article{Goyal_2019,
author = {Preeti, Rohit Goyal},
title = {Generating Optimized Test Case from UML Diagram Using Meta-Heuristic Algorithm},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {6 2019},
volume = {7},
Issue = {6},
month = {6},
year = {2019},
issn = {2347-2693},
pages = {1177-1183},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4703},
doi = {https://doi.org/10.26438/ijcse/v7i6.11771183}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i6.11771183}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4703
TI - Generating Optimized Test Case from UML Diagram Using Meta-Heuristic Algorithm
T2 - International Journal of Computer Sciences and Engineering
AU - Preeti, Rohit Goyal
PY - 2019
DA - 2019/06/30
PB - IJCSE, Indore, INDIA
SP - 1177-1183
IS - 6
VL - 7
SN - 2347-2693
ER -

VIEWS PDF XML
318 200 downloads 145 downloads
  
  
           

Abstract

Properly tested software is better in quality then the software tested using a poor approach or not tested. Increasing size and complexity of software makes manual testing process a time, cost and resource consuming task. Automating the testing process can improve software development process. The unified modeling language (UML) is the most widely used language to describe the analysis and designs of object-oriented software. Test cases can be derived from UML models more efficiently. In our work, we propose a novel approach for automatic test case generation from the combination of UML state chart, sequence and activity diagrams. In our approach, we first draw the UML state chart, sequence and activity diagrams. Then convert these diagrams to graphs and generate a combined graph. This graph is then used to generate test paths. We have integrated meta-heuristic algorithm i.e. Genetic Algorithm (GA) for this purpose and found fruitful results.

Key-Words / Index Term

UMLDiagram, Sequence Diagram, Activity Diagram, Test case generation, Genetic Algorithm

References

[1] Yoo-Min Choi and Dong-Jin Lim. Automatic feasible transition path generation from UML state chart diagrams using grouping genetic algorithms. 94:38–58, 2018.
[2] Rathee N. & Chhillar,” A Survey on Test Case Generation Techniques Using UML Diagrams”, Journal of Software, vol. 12, 8 August 2017.
[3] Khurana N., R.S Chillar,”Test Case Generation and Optimization using UML Models and Genetic Algorithm”, 3rd International Conference on Recent Trends in Computing 2015, Sciencedirect, PP.996-1004.
[4] Akshat Sharma, Rishon Patani, Ashish Aggarwal,”Software Testing Using Genetic Algorithms”, International Journal of Computer Science & Engineering Survey vol.7,No.2, April 2016, PP-21-33.
[5] Itti Hooda, R.S Chillar,”Test Case Optimization and Redundancy Using GA and Neural Networks”, International Journal of Electrical and Computer Engineering vol.8, No.6, December 2018, PP-5449-5456.
[6] Abdelkamel Hettab, Elhillali Kerkouche, Allaoua Chaoui,”A Graph Transformation Approach for Automatic Test Cases Generation from UML activity Diagram”,C3S2E 2015,ACM,2015.
[7] Fernando AugustoDiniz, Glaucia Braga e Silva,”EastTest: An approach for Automaric Test Cases Generation from UML Activity diagram.”, Springer,2018
[8] Meiliana, Irwandhi Septian, Ricky Setiawan Alianto, Daniel, Ford Lumban Gaol,”Automated Test Case Genartaion from UML Activity Diagram and Sequence Diagram using Depth First Search Algorithm”, 2nd International Conference on Computer Science and Computational Intelligence 2017,ICCSCI,ScienceDirect,october2017,PP-629-637.
[9] Monalisa Sharma, Debashish Kundu, Rajib Mall,”Automatic Test Case Generation from UML Sequence Diagrams” the proceeding of IEEE Conference on Software Maintainance,2007,IEEE. PP-996-1004.
[10] Ranjita Kumari Swain, Vikas Panthi, Prafulla Kumar Beher,”Generation of test cases using Activity Diagram” ,ISSN(PRINT):2231-5292, Vol.3,Issue-2,2013
[11] Saso Karakatic, Tina Schweighofer,”A Novel Approach to Generating Test Cases with Genetic Programming”,Springer,2015,PP-260-271.
[12] Ajay Kumar Jena, Santosh Kumar Swain, Durga Prasad Mohapatra,” Test Case Creation from UML Sequence Diagram: A Soft Computing Approach”, Springer, Proceedings of ICCD 2014, Volume 1
[13] Arvinder Kaur, Vidhi Vig,” Automatic test case generation through collaboration diagram: a case study”, Springer, 2017.
[14] S. Dubey, R. Jhaggar, R. Verma, D. Gaur, “Encryption and Decryption of Data by Genetic Algorithm”, International Journal of Scientific Research in Computer Science and Engineering, Vol. 5 No. 3, pp. 42-46, June 2017.
[15] G.R. Shahmohammadi and Kh.Mohammadi, “Key Management in Hierarchical Sensor Networks Using Improved Evolutionary Algorithm”, International Journal of Scientific Research in Network Security and Communication, Vol. 4, No. 2, pp. 5-14, April 2016.