Applying UML and Patterns: An Introduction to Object-Oriented Analysis and Design and the Unified Process
Testability Analysis of a UML Class Diagram
METRICS '02 Proceedings of the 8th International Symposium on Software Metrics
Analyzing Testability on Data Flow Designs
ISSRE '00 Proceedings of the 11th International Symposium on Software Reliability Engineering
Measuring and Improving Design Patterns Testability
METRICS '03 Proceedings of the 9th International Symposium on Software Metrics
Predicting Class Testability using Object-Oriented Metrics
SCAM '04 Proceedings of the Source Code Analysis and Manipulation, Fourth IEEE International Workshop
Effort estimation of use cases for incremental large-scale software development
Proceedings of the 27th international conference on Software engineering
An empirical study into class testability
Journal of Systems and Software - Special issue: Selected papers from the 4th source code analysis and manipulation (SCAM 2004) workshop
Early Estimate the Size of Test Suites from Use Cases
APSEC '08 Proceedings of the 2008 15th Asia-Pacific Software Engineering Conference
Metric based testability model for object oriented design (MTMOOD)
ACM SIGSOFT Software Engineering Notes
An Alternative Approach to Test Effort Estimation Based on Use Cases
ICST '09 Proceedings of the 2009 International Conference on Software Testing Verification and Validation
Transactions and paths: Two use case based metrics which improve the early effort estimation
ESEM '09 Proceedings of the 2009 3rd International Symposium on Empirical Software Engineering and Measurement
Empirical validation of object-oriented metrics for predicting fault proneness models
Software Quality Control
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Software testing, which plays a crucial role in software quality assurance, is a time and resource consuming process. It is, therefore, necessary to estimate as soon as possible the effort required to test software, so that activities can be planned and resources can be optimally allocated. Unfortunately, little is known about the prediction of the testing effort. In this paper, we address the testing effort from the perspective of test suites size. The study presented aims at exploring empirically the relationships between use cases and the size of test suites in object-oriented systems. We introduce four metrics to characterize the size and complexity of use cases. The size of test suites is measured in terms of lines of test code. We performed an experimental study using data collected from five cases studies. Results provide evidence that there is a significant relationship between use case metrics and the size of test suites.