Abstract-Automated testing is a basic principle of agile development. Its benefits include early defect detection, defect cause localization and removal of fear to apply changes to the code. Therefore, maintaining high quality test code is essential. This study introduces a model that assesses test code quality by combining source code metrics that reflect three main aspects of test code quality: completeness, effectiveness and maintainability. The model is inspired by the Software Quality Model of the Software Improvement Group which aggregates source code metrics into quality ratings based on benchmarking. To validate the model we assess the relation between test code quality, as measured by the model, and issue handling performance. An experiment is conducted in which the test code quality model is applied to 18 open source systems. The test quality ratings are tested for correlation with issue handling indicators, which are obtained by mining issue repositories. In particular, we study the (1) defect resolution speed, (2) throughput and (3) productivity issue handling metrics. The results reveal a significant positive correlation between test code quality and two out of the three issue handling metrics (throughput and productivity), indicating that good test code quality positively influences issue handling performance.
The UML (Unified Modeling Language) has become the de facto standard for software modeling in the software industry. Despite its wide acceptance, little is known about how UML is used in practice, let alone the challenges and difficulties faced by engineers who work with this modeling notation. In this paper, we provide empirical findings from a survey on the use of UML amongst 80 professional software engineers. We explore software engineers' opinions on common styles of using UML and how they perceive the impact of using UML on productivity and quality in software development. One of the results reveals that the impact of using the UML on productivity is perceived mostly in the design, analysis, and implementation phases.
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