Selecting Software Test Data Using Data Flow Information
IEEE Transactions on Software Engineering
Data Diversity: An Approach to Software Fault Tolerance
IEEE Transactions on Computers - Fault-Tolerant Computing
Partition Testing Does Not Inspire Confidence (Program Testing)
IEEE Transactions on Software Engineering
Automated Software Test Data Generation
IEEE Transactions on Software Engineering
Analyzing Partition Testing Strategies
IEEE Transactions on Software Engineering
PIE: A Dynamic Failure-Based Technique
IEEE Transactions on Software Engineering
Encyclopedia of software engineering
Encyclopedia of software engineering
Computer
Black-box testing: techniques for functional testing of software and systems
Black-box testing: techniques for functional testing of software and systems
Journal of Computational Physics
A semantic model of program faults
ISSTA '96 Proceedings of the 1996 ACM SIGSOFT international symposium on Software testing and analysis
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
ADTEST: A Test Data Generation Suite for Ada Software Systems
IEEE Transactions on Software Engineering
Automated program flaw finding using simulated annealing
Proceedings of the 1998 ACM SIGSOFT international symposium on Software testing and analysis
Model-based testing in practice
Proceedings of the 21st international conference on Software engineering
Automatic test data generation for path testing using GAs
Information Sciences: an International Journal
On Comparisons of Random, Partition, and Proportional Partition Testing
IEEE Transactions on Software Engineering
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Art of Software Testing
Continuity in software systems
ISSTA '02 Proceedings of the 2002 ACM SIGSOFT international symposium on Software testing and analysis
Computational intelligence as an emerging paradigm of software engineering
SEKE '02 Proceedings of the 14th international conference on Software engineering and knowledge engineering
Artificial Immune Systems: A New Computational Intelligence Paradigm
Artificial Immune Systems: A New Computational Intelligence Paradigm
Generating Software Test Data by Evolution
IEEE Transactions on Software Engineering
ECSQ '02 Proceedings of the 7th International Conference on Software Quality
Fast Antirandom (FAR) Test Generation
HASE '98 The 3rd IEEE International Symposium on High-Assurance Systems Engineering
Adaptive Random Testing Through Dynamic Partitioning
QSIC '04 Proceedings of the Quality Software, Fourth International Conference
Is mutation an appropriate tool for testing experiments?
Proceedings of the 27th international conference on Software engineering
Search-based software test data generation: a survey: Research Articles
Software Testing, Verification & Reliability
Lattice-based adaptive random testing
Proceedings of the 20th IEEE/ACM international Conference on Automated software engineering
Planning Algorithms
The Current State and Future of Search Based Software Engineering
FOSE '07 2007 Future of Software Engineering
Automatic mutation test input data generation via ant colony
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Applying particle swarm optimization to software testing
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Improving random test sets using the diversity oriented test data generation
Proceedings of the 2nd international workshop on Random testing: co-located with the 22nd IEEE/ACM International Conference on Automated Software Engineering (ASE 2007)
Automatic Generation of Floating-Point Test Data
IEEE Transactions on Software Engineering
A System to Generate Test Data and Symbolically Execute Programs
IEEE Transactions on Software Engineering
On the Automated Generation of Program Test Data
IEEE Transactions on Software Engineering
A Data Flow Oriented Program Testing Strategy
IEEE Transactions on Software Engineering
Symbolic Testing and the DISSECT Symbolic Evaluation System
IEEE Transactions on Software Engineering
Automatic test data generation using particle systems
Proceedings of the 2008 ACM symposium on Applied computing
Search based software testing of object-oriented containers
Information Sciences: an International Journal
Searching for Cognitively Diverse Tests: Towards Universal Test Diversity Metrics
ICSTW '08 Proceedings of the 2008 IEEE International Conference on Software Testing Verification and Validation Workshop
Using program data-state scarcity to guide automatic test data generation
Software Quality Control
ASIAN'04 Proceedings of the 9th Asian Computing Science conference on Advances in Computer Science: dedicated to Jean-Louis Lassez on the Occasion of His 5th Cycle Birthday
An Evaluation of Random Testing
IEEE Transactions on Software Engineering
IEEE Transactions on Software Engineering
Automatic generation of basis test paths using variable length genetic algorithm
Information Processing Letters
Hi-index | 0.07 |
We present a new test data generation technique which uses the concept of diversity of test sets as a basis for the diversity oriented test data generation - DOTG. Using DOTG we translate into an automatic test data generation technique the intuitive belief that increasing the variety, or diversity, of the test data used to test a program can lead to an improvement on the completeness, or quality, of the testing performed. We define the input domain perspective for diversity (DOTG-ID), which considers the distances among the test data in the program input domain to compute a diversity value for test sets. We describe metaheuristics which can be used to automate the generation of test sets for the DOTG-ID testing technique: simulated annealing; a genetic algorithm; and a proposed metaheuristic named simulated repulsion. The effectiveness of DOTG-ID was evaluated by using a Monte Carlo simulation, and also by applying the technique to test simple programs and measuring the data-flow coverage and mutation scores achieved. The standard random testing technique was used as a baseline for these evaluations. Results provide an understanding of the potential gains in terms of testing effectiveness of DOTG-ID over random testing and also reveal testing factors which can make DOTG-ID less effective.