Early estimation of software quality using in-process testing metrics: a controlled case study
3-WoSQ Proceedings of the third workshop on Software quality
Dependability metrics
Usage of multiple prediction models based on defect categories
Proceedings of the 6th International Conference on Predictive Models in Software Engineering
Reducing test effort: A systematic mapping study on existing approaches
Information and Software Technology
| Hi-index | 0.00 |
In industrial practice, information on the software field quality of a product is available too late in the software lifecycle to guide affordable corrective action. An important step towards remediation of this problem lies in the ability to provide an early estimation of post-release field quality. This paper evaluates the Software Testing and Reliability Early Warning for Java (STREW-J) metric suite leveraging the software testing effort to predict post-release field quality early in the software development phases. The metric suite is applicable for software products implemented in Java for which an extensive suite of automated unit test cases are incrementally created as development proceeds. We validated the prediction model using the STREW-J metrics via a two-phase case study approach which involved 27 medium-sized open source projects, and five industrial projects. The error in estimation and the sensitivity of the predictions indicate the STREW-J metric suite can be used effectively to predict post-release software field quality.