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Inference and Regeneration of Programs that Store and Retrieve Data

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dc.contributor.advisor Martin Rinard
dc.contributor.author Rinard, Martin en_US
dc.contributor.author Shen, Jiasi en_US
dc.contributor.other Program Analysis and Compilation en
dc.date.accessioned 2017-04-24T19:45:07Z
dc.date.available 2017-04-24T19:45:07Z
dc.date.issued 2017-04-24
dc.identifier.uri http://hdl.handle.net/1721.1/108383
dc.description.abstract As modern computation platforms become increasingly complex, their programming interfaces are increasingly difficult to use. This complexity is especially inappropriate given the relatively simple core functionality that many of the computations implement. We present a new approach for obtaining so ware that executes on modern computing platforms with complex programming interfaces. Our approach starts with a simple seed program, written in the language of the developer's choice, that implements the desired core functionality. It then systematically generates inputs and observes the resulting outputs to learn the core functionality. It finally automatically regenerates new code that implements the learned core functionality on the target computing platform. This regenerated code contains both (a) boilerplate code for the complex programming interfaces that the target computing platform presents and (b) systematic error and vulnerability checking code that makes the new implementations robust and secure. By providing a productive new mechanism for capturing and encapsulating knowledge about how to use modern complex interfaces, this new approach promises to greatly reduce the developer effort required to obtain secure, robust so ware that executes on modern computing platforms. en_US
dc.format.extent 22 p. en_US
dc.relation.ispartofseries MIT-CSAIL-TR-2017-006
dc.title Inference and Regeneration of Programs that Store and Retrieve Data en_US
dc.date.updated 2017-04-24T19:45:07Z


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