There are several problem areas that must be addressed when ap-plying randomization to unit testing. As yet no general, fully au-tomated solution that works for all units has been proposed. We therefore have developed RUTE-J, a Java package intended to help programmers do randomized unit testing in Java. In this paper, we describe RUTE-J and illustrate how it supports the development of per-unit solutions for the problems of randomized unit testing. We report on an experiment in which we applied RUTE-J to the standard Java TreeMap class, measuring the efficiency and effec-tiveness of the technique. We also illustrate the use of randomized testing in experimentation, by adapting RUTE-J so that it gener-ates randomized minimal covering test s...
Random testing can eliminate subjectiveness in constructing test data and increase the diversity of ...
Abstract. Concolic testing is a method for test input generation where a given program is executed b...
We are concerned with the problem of detecting bugs in machine learning applications. In the absence...
This paper presents Jartege, a tool which allows random generation of unit tests for Java classes sp...
RANDOOP FOR JAVA is a tool that generates unit tests for Java code using feedback-directed random te...
Abstract—Adaptive Random Testing (ART) is a testing technique which is based on an observation that ...
Random testing represents a simple and tractable way for software assessment. This paper presents th...
Testing is an important approach to uncover errors in software systems; but, effective testing can b...
Data from projects worldwide show that many software projects fail and most are completed late or ov...
International audienceRandom testing represents a simple and tractable way for software assessment. ...
Thorough software testing involves the generation of testinput data that meets adequacy criteria, wh...
Java PathFinder (JPF) and PRISM are the most popular model checkers for Java code and systems that e...
International audienceStatistical testing aims at generating random test data that respect selected ...
peer reviewedAfter four successful JUnit tool competitions, we report on the achievements of a new J...
Jumble is a byte code level mutation testing tool for Java which inter-operates with JUnit. It has b...
Random testing can eliminate subjectiveness in constructing test data and increase the diversity of ...
Abstract. Concolic testing is a method for test input generation where a given program is executed b...
We are concerned with the problem of detecting bugs in machine learning applications. In the absence...
This paper presents Jartege, a tool which allows random generation of unit tests for Java classes sp...
RANDOOP FOR JAVA is a tool that generates unit tests for Java code using feedback-directed random te...
Abstract—Adaptive Random Testing (ART) is a testing technique which is based on an observation that ...
Random testing represents a simple and tractable way for software assessment. This paper presents th...
Testing is an important approach to uncover errors in software systems; but, effective testing can b...
Data from projects worldwide show that many software projects fail and most are completed late or ov...
International audienceRandom testing represents a simple and tractable way for software assessment. ...
Thorough software testing involves the generation of testinput data that meets adequacy criteria, wh...
Java PathFinder (JPF) and PRISM are the most popular model checkers for Java code and systems that e...
International audienceStatistical testing aims at generating random test data that respect selected ...
peer reviewedAfter four successful JUnit tool competitions, we report on the achievements of a new J...
Jumble is a byte code level mutation testing tool for Java which inter-operates with JUnit. It has b...
Random testing can eliminate subjectiveness in constructing test data and increase the diversity of ...
Abstract. Concolic testing is a method for test input generation where a given program is executed b...
We are concerned with the problem of detecting bugs in machine learning applications. In the absence...