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Article summary:

1. Response time analysis of real-time task graphs is intractable for most existing models, except the simplest ones.

2. Two approximate analysis methods RBF and IBF are presented with pseudo-polynomial complexity and quantitative performance guarantees.

3. Simulation experiments show that the proposed approximate analysis methods have very high efficiency with low precision loss.

Article analysis:

The article provides a detailed overview of the response time analysis problem for real-time task graphs, as well as two approximate analysis methods (RBF and IBM) to address this problem. The article is well written and provides a comprehensive overview of the topic, including theoretical results, simulation experiments, and an example to illustrate the semantics of DRT tasks.

The article does not appear to be biased or one-sided in its reporting; it presents both sides of the issue fairly and objectively. It also provides evidence for its claims in the form of theoretical results, simulation experiments, and an example illustrating the semantics of DRT tasks.

The article does not appear to be missing any points of consideration or evidence for its claims; it covers all relevant topics related to response time analysis for real-time task graphs in detail. Furthermore, it does not appear to contain any promotional content or partiality; it is purely informational in nature.

Finally, the article does note possible risks associated with using approximate analysis methods instead of exact solutions; it states that these methods may lead to lower precision but higher efficiency compared to exact solutions. In conclusion, this article appears to be trustworthy and reliable in its reporting on response time analysis for real-time task graphs.