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作者 Jha, Susmit Kumar
書名 Towards Automated System Synthesis Using SCIDUCTION
國際標準書號 9781267226525
book jacket
說明 175 p
附註 Source: Dissertation Abstracts International, Volume: 73-07, Section: B, page:
Adviser: Sanjit A. Seshia
Thesis (Ph.D.)--University of California, Berkeley, 2011
Automated synthesis of systems that are correct by construction has been a long-standing goal of computer science. Synthesis is a creative task and requires human intuition and skill. Its complete automation is currently beyond the capacity of programs that do automated reasoning. However, there is a pressing need for tools and techniques that can automate non-intuitive and error-prone synthesis tasks. This thesis proposes a novel synthesis approach to solve such tasks in the synthesis of programs as well as the synthesis of switching logic for cyberphysical systems
The common underlying theme of the proposed synthesis techniques is a novel combination of deductive reasoning, inductive reasoning and structure hypotheses on the system under synthesis. We call this combined reasoning technique SCIDUCTION that stands for Structurally Constrained Induction and D eduction. SCIDUCTION constrains inductive and deductive reasoning using structure hypotheses, and actively combines inductive and deductive reasoning: for instance, deductive techniques generate examples for learning, and inductive techniques generate generalizations as candidate designs to be proved or disproved by deduction
We use the proposed synthesis approach for automated synthesis of loop-free programs from black-box oracle specifications using functions from a library of component functions, synthesizing optimal cost fixed-point code with specified accuracy from floating-point code, and synthesizing switching logic of hybrid systems for safety and performance properties. We illustrate that our approach can be used to automate system synthesis, and thus, can prove to be an effective aid to designers and developers
School code: 0028
Host Item Dissertation Abstracts International 73-07B
主題 Engineering, Robotics
Artificial Intelligence
Computer Science
Alt Author University of California, Berkeley. Electrical Engineering & Computer Sciences
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