Within the semiconductor manufacturing chain the automated testing steps are coming increasingly into focus. Delivering enhanced functionality per IC is expected, with the costs per die being reduced, while, at the same time, the costs of semiconductor electrical tests increase disproportionately. In addition, the requirements for quality are significantly growing, in general, and in particular, being ensured by automated testing. Hence, the execution of test development and test method quality are becoming an important, competitive advantage topic. This paper presents a case study that evidences such advantage by adopting software engineering methodologies in test program generation. A software cost model applied to test program development parameters, assessed in combination with Bayesian analysis and Gaussian statistical methods, is discussed in detail. Furthermore, the results obtained indicate the effectiveness of the proposed approach, evidencing a remarkable effort reduction, and address quality robustness in semiconductor test engineering.
|Journal||Journal of Electronic Testing Theory and Applications|
|Publication status||Published - 18 Jun 2014|
- Semiconductor test
- Software quality
- Automated test equipment
- System-on-a-chip test
- Mixed-signal test.