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Practical Considerations in Automatic Code Generation

Practical Considerations in Automatic Code Generation

Paul Dietz, Aswin van den Berg, Kevin Marth, Thomas Weigert, Frank Weil
Copyright: © 2007 |Pages: 63
ISBN13: 9781591409410|ISBN10: 1591409411|ISBN13 Softcover: 9781591409427|EISBN13: 9781591409434
DOI: 10.4018/978-1-59140-941-1.ch014
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MLA

Dietz, Paul, et al. "Practical Considerations in Automatic Code Generation." Advances in Machine Learning Applications in Software Engineering, edited by Du Zhang and Jeffery J.P. Tsai, IGI Global, 2007, pp. 346-408. https://doi.org/10.4018/978-1-59140-941-1.ch014

APA

Dietz, P., van den Berg, A., Marth, K., Weigert, T., & Weil, F. (2007). Practical Considerations in Automatic Code Generation. In D. Zhang & J. Tsai (Eds.), Advances in Machine Learning Applications in Software Engineering (pp. 346-408). IGI Global. https://doi.org/10.4018/978-1-59140-941-1.ch014

Chicago

Dietz, Paul, et al. "Practical Considerations in Automatic Code Generation." In Advances in Machine Learning Applications in Software Engineering, edited by Du Zhang and Jeffery J.P. Tsai, 346-408. Hershey, PA: IGI Global, 2007. https://doi.org/10.4018/978-1-59140-941-1.ch014

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Abstract

Model-driven engineering proposes to develop software systems by first creating an executable model of the system design and then transforming this model into an implementation. This chapter discusses how to automatically transform such design models into product implementations for industrial-strength systems. It provides insights, practical considerations, and lessons learned when developing code generators for applications that must conform to the constraints imposed by real-world, high-performance systems. This deeper understanding of the relevant issues will enable developers of automatic code generation systems to build transformation tools that can be deployed in industrial applications with stringent performance requirements.

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