A Code Analysis Base Regression Test Selection Technique for D Programming Language

Author(s):  
Nitesh Chouhan ◽  
Maitreyee Dutta ◽  
Mayank Singh
Author(s):  
MATS SKOGLUND ◽  
PER RUNESON

One regression test selection technique proposed for object-oriented programs is the Class firewall regression test selection technique. The selection technique selects test cases for regression test, which test changed classes and classes depending on changed classes. However, in empirical studies of the application of the technique, we observed that another technique found the same defects, selected fewer tests and required a simpler, less costly, analysis. The technique, which we refer to as the Change-based regression test selection technique, is basically the Class firewall technique, but with the class firewall removed. In this paper we formulate a hypothesis stating that these empirical observations are not incidental, but an inherent property of the Class firewall technique. We prove that the hypothesis holds for Java in a stable testing environment, and conclude that the effectiveness of the Class firewall regression testing technique can be improved without sacrificing the defect detection capability of the technique, by removing the class firewall.


2009 ◽  
Vol 2009 ◽  
pp. 1-10 ◽  
Author(s):  
Nashat Mansour ◽  
Wael Statieh

We present a regression test selection technique for C# programs. C# is fairly new and is often used within the Microsoft .Net framework to give programmers a solid base to develop a variety of applications. Regression testing is done after modifying a program. Regression test selection refers to selecting a suitable subset of test cases from the original test suite in order to be rerun. It aims to provide confidence that the modifications are correct and did not affect other unmodified parts of the program. The regression test selection technique presented in this paper accounts for C#.Net specific features. Our technique is based on three phases; the first phase builds an Affected Class Diagram consisting of classes that are affected by the change in the source code. The second phase builds a C# Interclass Graph (CIG) from the affected class diagram based on C# specific features. In this phase, we reduce the number of selected test cases. The third phase involves further reduction and a new metric for assigning weights to test cases for prioritizing the selected test cases. We have empirically validated the proposed technique by using case studies. The empirical results show the usefulness of the proposed regression testing technique for C#.Net programs.


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