DocumentCode :
1830370
Title :
Scenario Based Functional Regression Testing Using Petri Net Models
Author :
Ahmad, Farhan ; Qaisar, Zahid Hussain
Author_Institution :
Fac. of Inf. Technol., Univ. of Central Punjab, Lahore, Pakistan
Volume :
2
fYear :
2013
fDate :
4-7 Dec. 2013
Firstpage :
572
Lastpage :
577
Abstract :
Software testing lies in the validation which ensures that the implementation satisfies the client´s requirements. There are several techniques on software testing some are implementation based while others are model based. We have proposed the Petri net model based testing technique for testing the software. Although UML is the de-facto standard for the software development however most of the UML diagrams supports static behavior while Petri nets supports dynamic behavior i.e. we can represent concurrent behavior of objects in case of object oriented paradigm. In our case we have also selected object oriented paradigm as it is well established paradigm and provides ease in development and it is more realistic. We have proposed a regression based testing technique using Petri nets. Regression testing technique is applied on the Delta version i.e. changed version of the software. Our technique has efficient mechanism of reducing the test suite for the delta version on the basis of analysis of the baseline version. Petri net models are used in this paper for analyzing the baseline and delta version.
Keywords :
Petri nets; object-oriented methods; program testing; program verification; Delta version; Petri net models; baseline version analysis; object-oriented paradigm; scenario-based functional regression testing; software development; software testing; software validation; test suite reduction; Analytical models; Computational modeling; Object oriented modeling; Petri nets; Software; Testing; Unified modeling language; Petri nets; change analysis; change identification; formal methods; model based testing; software testing; test suite; test suite reduction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Applications (ICMLA), 2013 12th International Conference on
Conference_Location :
Miami, FL
Type :
conf
DOI :
10.1109/ICMLA.2013.179
Filename :
6786173
Link To Document :
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