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Computer Engineering

Departmental Technical Reports (CS)

Test data generator

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Full-Text Articles in Engineering

Integrating Random Testing With Constraints For Improved Efficiency And Diversity, Yoonsik Cheon, Antonio Cortes, Martine Ceberio, Gary T. Leavens Feb 2008

Integrating Random Testing With Constraints For Improved Efficiency And Diversity, Yoonsik Cheon, Antonio Cortes, Martine Ceberio, Gary T. Leavens

Departmental Technical Reports (CS)

Random testing can be fully automated, eliminates subjectiveness in constructing test cases, and increases the diversity of test data. However, randomly generated tests may not satisfy program's assumptions (e.g., method preconditions). While constraint solving can satisfy such assumptions, it does not necessarily generate diverse tests and is hard to apply to large programs. We blend these techniques by extending random testing with constraint solving, improving the efficiency of generating valid test data while preserving diversity. For domains such as objects, we generate input values randomly; however, for values of finite domains such as integers, we represent test data generation as …


A Fitness Function To Find Feasible Sequences Of Method Calls For Evolutionary Testing Of Object-Oriented Programs, Myoung Yee Kim, Yoonsik Cheon Nov 2007

A Fitness Function To Find Feasible Sequences Of Method Calls For Evolutionary Testing Of Object-Oriented Programs, Myoung Yee Kim, Yoonsik Cheon

Departmental Technical Reports (CS)

In evolutionary testing of an object-oriented program, the search objective is to find a sequence of method calls that can successfully produce a test object of an interesting state. This is challenging because not all call sequences are feasible; each call of a sequence has to meet the assumption of the called method. The effectiveness of an evolutionary testing thus depends in part on the quality of the so-called fitness function that determines the degree of the fitness of a candidate solution. In this paper, we propose a new fitness function based on assertions such as method preconditions to find …


A Quick Tutorial On Jet, Yoonsik Cheon Jun 2007

A Quick Tutorial On Jet, Yoonsik Cheon

Departmental Technical Reports (CS)

JET is an automated unit testing tool for Java classes annotated with JML specifications; JML is a formal interface specification language for Java to document the behavior of Java classes and interfaces. JET tests each method of the class under test separately. For each method, it generates a collection of test data, executes them, and decides test results (i.e., pass/fail) by using JML specifications as test oracles, thereby fully automating unit testing of Java classes. This document gives a quick tutorial introduction to JET.


Random Test Data Generation For Java Classes Annotated With Jml Specifications, Yoonsik Cheon, Carlos E. Rubio-Medrano Mar 2007

Random Test Data Generation For Java Classes Annotated With Jml Specifications, Yoonsik Cheon, Carlos E. Rubio-Medrano

Departmental Technical Reports (CS)

The hidden states of objects create a barrier to designing and generating test data automatically. For example, the state of an object has to be established indirectly through a sequence of method invocations. For a non-trivial class, however, it is extremely unlikely that a randomly-chosen sequence of method invocations can construct an object successfully, as each invocation has to satisfy the state invariants. Nonetheless, automated random testing can reduce the cost of testing dramatically and has potential for finding errors that are difficult to find in other ways because it eliminates the subjectiveness in constructing test data. We propose a …


Automated Random Testing To Detect Specification-Code Inconsistencies, Yoonsik Cheon Jan 2007

Automated Random Testing To Detect Specification-Code Inconsistencies, Yoonsik Cheon

Departmental Technical Reports (CS)

An interface specification language such as JML provides a means to document precisely the behavior of program modules such as Java classes, and it is being adopted by industry. However, few practical tools exist for programmers to assure the correctness of their interface specifications. Nonetheless, the correctness of an interface specification is a prerequisite for the use of the specification, both as a precise API documentation and as a foundation for formal verification of and reasoning about the implementation. We propose automated random testing as a practical tool to assure the correctness of interface specifications. The key idea of our …


A Fitness Function For Modular Evolutionary Testing Of Object-Oriented Programs, Yoonsik Cheon, Kim Myoung Oct 2005

A Fitness Function For Modular Evolutionary Testing Of Object-Oriented Programs, Yoonsik Cheon, Kim Myoung

Departmental Technical Reports (CS)

We show that encapsulation of states in object-oriented programs hinders the search for test data using evolutionary testing. In a well-designed object-oriented program the encapsulated or hidden state is accessible only through exported or public methods. As client code is oblivious to the internal state of a server object, no guidance is available to test the client code using evolutionary testing. In particular, it is difficult to determine the fitness or goodness of test data, as it may depend on the hidden internal state. However, evolutionary testing is a promising new approach whose effectiveness has been shown by several researchers. …