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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Corrêa, U.B. Lamb, L. Carro, L. Brisolara, L. Mattos, J. |
| Copyright Year | 2010 |
| Abstract | The complexity of embedded devices poses new challenges to embedded software development in addition to the traditional physical requirements. Therefore, the evaluation of the quality of embedded software and its impact on these traditional properties becomes increasingly relevant. Concepts such as reuse, abstraction, cohesion, coupling, and other software attributes have been used as quality metrics in the software engineering domain. However, they have not been used in the embedded software domain. In embedded systems development, another set of tools is used to estimate physical properties such as power consumption, memory footprint, and performance. These tools usually require costly synthesis-and-simulation design cycles. In current complex embedded devices, one must rely on tools that can help design space exploration at the highest possible level, identifying a solution that represents the best design strategy in terms of software quality, while simultaneously meeting physical requirements. We present an analysis of the cross-correlation between software quality metrics, which can be extracted before the final system is synthesized, and physical metrics for embedded software. Using a neural network, we investigate the use of these cross-correlations to predict the impact that a given modification on the software solution will have on embedded software physical metrics. This estimation can be used to guide design decisions towards improving physical properties of embedded systems, while maintaining an adequate trade-off regarding software quality. |
| Starting Page | 2381 |
| Ending Page | 2386 |
| File Size | 361001 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424475476 |
| e-ISBN | 9781424475483 |
| DOI | 10.1109/CIT.2010.409 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-06-29 |
| Publisher Place | United Kingdom |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Measurement Embedded Software Embedded system Artificial neural networks Software quality software engineering quality metrics Books measurement Embedded software |
| Content Type | Text |
| Resource Type | Article |
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