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    Information Technology Patents (Intellectual Property Law Series) (English Edition)

    Por LandMark Publications

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    THIS CASEBOOK contains a selection of 176 U. S. Court of Appeals decisions that analyze and discuss issues surrounding information technology patents. The selection of decisions spans from 2005 to the date of publication.

    Chip designers write source code that determines the set of basic operations that can be executed by the circuits that make up a computer chip. For example, a chip designer may indicate that a particular "gate"—or component of the circuit—is supposed to provide a particular output given a particular input. The source code indicates this using general logical statements, such as "if A=0, then B=0, else B=1."

    The source code must first be "translated" into the actual design of the chip. Specialized software "synthesizes," i.e., translates, the source code into a "gate-level netlist," or a basic schematic of the chip. The design is then tested for errors and inefficiencies, as it may contain redundant circuitry based on a direct translation from the source code. The design is optimized to remove superfluous components from the circuit. The result is a simpler and more efficient circuit without any loss of functionality.

    An error in the design of a computer chip, even a minor one, can be extremely problematic and costly for the company that produces the chip. Thus, before a chip is manufactured, the design undergoes significant testing to make sure that the chip performs as intended.

    When the design process is complete, chip designers use specialized software or hardware to imitate the behavior of the final circuitry to test whether the chip does what it is supposed to do. The testing involves simulations of the circuit from the original source code.

    During the testing, the designers can fix problems by going back to the source code to make necessary modifications. However, it is often difficult to trace back errors to the right place in the source code because high level information in the code is lost during translation and optimization. The loss of this information makes identifying and correcting errors much more costly and time consuming.
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