La implementación de Rhinoscript en facultades de arquitectura en Latinoamérica se realizó en Santiago de Chile (2006, 2007) y Lima (2008), estableciendo algunos criterios para explorar formas complejas usando la programación, con estudiantes de pregrado bajo estrategias de postgrado. Después de documentar los resultados de las dos primeras experiencias [1], se hallaron métodos que se usaron durante la implementación. El objetivo es evidenciar como las experiencias llevadas a cabo pueden aplicarse a otros contextos regionales, proponiendo tipologías para empezar y recursos disponibles que permitan a los estudiantes desarrollar por si mismos nuevas exploraciones.

Spreadsheets are arguably the most widely used programming language in use today, yet spreadsheets commonly contain errors. Research shows that regardless of the experience of the end user, an alarming number of spreadsheets contain errors (91% in recent field audits). Most spreadsheets are created by end users with little or no programming experience. Unfortunately, software engineering research has largely ignored these users. In an attempt to reduce this high error rate, our research is aimed at bringing the benefits of software engineering to end users without requiring that they first learn software engineering principles. One mechanism for creating error-free programs is assertions. An assertion is a program property that always holds. It provides a way to attach more of the specification to the program. We have developed an assertion tool for spreadsheet languages that extends Microsoft Excel's validation scheme and includes capabilities such as assertion propagation. This work describes an empirical study done to assess how well end users understand and use the information provided by the assertion tool as they perform maintenance tasks. The study also provides information about end users' testing behavior. / Graduation date: 2002

Traditionally, research into end-user programming has focused on how to make programming more accessible to end users. However, few researchers have considered providing end users with devices to help improve the reliability of the programs they create. To help improve the reliability of spreadsheets created by end users, we are working to allow users to communicate the purpose and other underlying information about their spreadsheets using a form of requirement specifications we call "guards." Guards were initially designed for individual cells but, for large spreadsheets, with replicated/shared formulas across groups of rows or columns, guards can only be practical if users can enter them across these groups of rows or columns. The problem is, this introduces many-to-many relationships, at the intersection of rows and columns with guards. It is not clear how the system should reason and communicate about many-to-many relationships in a way that will make sense to end users. In this thesis, we present the human-centric design rationale for our approach to how the system should reason about such many-to-many relationships. The design decisions are presented with their reasons gleaned from two design-time models--Cognitive Dimensions and Attention Investment--and from the users themselves in a small think-aloud study. / Graduation date: 2003

Thesis (M.S.)--Oregon State University, 2006. / Printout. Includes bibliographical references (leaves 51-55). Also available on the World Wide Web.

Thesis (M.S.)--Oregon State University, 2007. / Printout. Includes bibliographical references (leaves 34-36). Also available on the World Wide Web.

Thesis (M.S.)--Oregon State University, 2008. / Printout. Includes bibliographical references (leaves 51-55). Also available on the World Wide Web.

Spreadsheets are routinely used in business and scientific contexts, and one of the most vexing challenges data analysts face is performing data cleaning prior to analysis and evaluation. The ad-hoc and arbitrary nature of data cleaning problems, such as typos, inconsistent formatting, missing values, and a lack of standardization, often creates the need for highly specialized pipelines. We ask whether an LLM can find its way around a spreadsheet and how to support end-users in taking their free-form data processing requests to fruition. Just like RAG retrieves context to answer users' queries, we demonstrate how we can retrieve elements from a code library to compose data processing pipelines. Through comprehensive experiments, we demonstrate the quality of our system and how it is able to continuously augment its vocabulary by saving new codes and pipelines back to the code library for future retrieval. / Master of Science / Spreadsheets are frequently utilized in both business and scientific settings, and one of the most challenging tasks that must be accomplished before analysis and evaluation can take place is the cleansing of the data. The ad-hoc and arbitrary nature of issues in data quality, such as typos, inconsistent formatting, missing values, and lack of standardization, often creates the need for highly specialized data cleaning pipelines. Within the scope of this thesis, we investigate whether a large language model (LLM) can navigate its way around a spreadsheet, as well as how to assist end-users in bringing their free-form data processing requests to fruition. Just like Retrieval-Augmented Generation (RAG) retrieves context to answer user queries, we demonstrate how we can retrieve elements from a Python code reference to compose data processing pipelines. Through comprehensive experiments, we showcase the quality of our system and how it is capable of continuously improving its code-writing ability by saving new codes and pipelines back to the code library for future retrieval.

Thesis (M.S.)--Oregon State University, 2010. / Printout. Includes bibliographical references (leaves 48-51). Also available on the World Wide Web.

Thesis (M.P.A.)--University of Hong Kong, 1993.

Thesis (M.P.A.)--University of Hong Kong, 1993. / Also available in print.