The Software Design Laboratory

Software Design Laboratory is an undergraduate practicum in software design, which focuses on principles and practices of large-scale software design. Concepts and examples borrowed from elsewhere in Computer Science are applied to the construction of a significant project, namely a command interpreter resembling the Bourne shell. The course focus is on long-lived software systems of a size requiring group effort. We therefore address maintenance, testing, documentation, code readability, version control, and group dynamics

Focal Spot, Summer/Fall 2009

https://digitalcommons.wustl.edu/focal_spot_archives/1112/thumbnail.jp

A Practical Course in Software Design

In practical disciplines, "Those who can, do. Those who can‘t, teach." and you "Learn by doing". Our presentation of an undergraduate semester course in Software Design, "Software Design Laboratory", has the spirit of the second adage and attempts to refute the first. In our description of the course, we focus on the relationship between the different programming assignments, and the role of these assignments in developing the student's capabilities, rather than on management, group structure, or formal techniques. We argue that a laboratory course is as essential to Computer Science as it is lo Physics or Chemistry

Overview 1996-1998 Virginia Institute of Marine Science

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Reports to the President

A compilation of annual reports for the 1988-1989 academic year, including a report from the President of the Massachusetts Institute of Technology, as well as reports from the academic and administrative units of the Institute. The reports outline the year's goals, accomplishments, honors and awards, and future plans

Reports to the President

A compilation of annual reports for the 1999-2000 academic year, including a report from the President of the Massachusetts Institute of Technology, as well as reports from the academic and administrative units of the Institute. The reports outline the year's goals, accomplishments, honors and awards, and future plans

Reports to the President

A compilation of annual reports for the 1985-1986 academic year, including a report from the President of the Massachusetts Institute of Technology, as well as reports from the academic and administrative units of the Institute. The reports outline the year's goals, accomplishments, honors and awards, and future plans

Reports to the President

A compilation of annual reports for the 1989-1990 academic year, including a report from the President of the Massachusetts Institute of Technology, as well as reports from the academic and administrative units of the Institute. The reports outline the year's goals, accomplishments, honors and awards, and future plans

Predictive engineering and optimization of tryptophan metabolism in yeast through a combination of mechanistic and machine learning models

In combination with advanced mechanistic modeling and the generation of high-quality multi-dimensional data sets, machine learning is becoming an integral part of understanding and engineering living systems. Here we show that mechanistic and machine learning models can complement each other and be used in a combined approach to enable accurate genotype-to-phenotype predictions. We use a genome-scale model to pinpoint engineering targets and produce a large combinatorial library of metabolic pathway designs with different promoters which, once phenotyped, provide the basis for machine learning algorithms to be trained and used for new design recommendations. The approach enables successful forward engineering of aromatic amino acid metabolism in yeast, with the new recommended designs improving tryptophan production by up to 17% compared to the best designs used for algorithm training, and ultimately producing a total increase of 106% in tryptophan accumulation compared to optimized reference designs. Based on a single high-throughput data-generation iteration, this study highlights the power of combining mechanistic and machine learning models to enhance their predictive power and effectively direct metabolic engineering efforts