Knot/Knotting Practice in Craft and Space

Knot/knotting Practice in Craft and Space is a three part research-creation project that used a study of knotting techniques to locate craft in an expanded field of spatial practice. The first part consisted of practical, studio based exercises in which I worked with various natural and synthetic fibres to learn common knotting techniques. The second part was an art historical study that combined craft and architecture history with critical theory related to the social production of space. The third part was an exhibition of drawing and knotted objects titled Opening Closures. This document unifies the lines inquiry that define my project. The first chapter presents the art historical justification for knotting to be understood as a spatial practice. Nineteenth-century German architect and theorist Gottfried Semper’s idea that architectural form is derived from four basic material practices allies craft and architecture in my project and is the point of departure from which I make my argument. In the second chapter, to consider the methodological concerns of research-creation as a form of knowledge production and dissemination, I adopt the format of an instruction manual to conduct an analysis of knot types and to provide instructions for the production of several common knots. In the third chapter, I address the formal and conceptual underpinnings of each artwork presented in my exhibition. I conclude with a proposal for an expanded field of spatial practice by adapting art critic and theorist Rosalind Krauss’s well-known framework for assessing sculpture in 1960s.

IMPROVING THE PERFORMANCE OF DATABASE-CENTRIC APPLICATIONS THROUGH PROGRAM ANALYSIS

Modern software applications are becoming more dependent on database management systems (DBMSs). DBMSs are usually used as black boxes by software developers. For example, Object-Relational Mapping (ORM) is one of the most popular database abstraction approaches that developers use nowadays. Using ORM, objects in Object-Oriented languages are mapped to records in the database, and object manipulations are automatically translated to SQL queries. As a result of such conceptual abstraction, developers do not need deep knowledge of databases; however, all too often this abstraction leads to inefficient and incorrect database access code. Thus, this thesis proposes a series of approaches to improve the performance of database-centric software applications that are implemented using ORM. Our approaches focus on troubleshooting and detecting inefficient (i.e., performance problems) database accesses in the source code, and we rank the detected problems based on their severity. We first conduct an empirical study on the maintenance of ORM code in both open source and industrial applications. We find that ORM performance-related configurations are rarely tuned in practice, and there is a need for tools that can help improve/tune the performance of ORM-based applications. Thus, we propose approaches along two dimensions to help developers improve the performance of ORM-based applications: 1) helping developers write more performant ORM code; and 2) helping developers configure ORM configurations. To provide tooling support to developers, we first propose static analysis approaches to detect performance anti-patterns in the source code. We automatically rank the detected anti-pattern instances according to their performance impacts. Our study finds that by resolving the detected anti-patterns, the application performance can be improved by 34% on average. We then discuss our experience and lessons learned when integrating our anti-pattern detection tool into industrial practice. We hope our experience can help improve the industrial adoption of future research tools. However, as static analysis approaches are prone to false positives and lack runtime information, we also propose dynamic analysis approaches to further help developers improve the performance of their database access code. We propose automated approaches to detect redundant data access anti-patterns in the database access code, and our study finds that resolving such redundant data access anti-patterns can improve application performance by an average of 17%. Finally, we propose an automated approach to tune performance-related ORM configurations using both static and dynamic analysis. Our study shows that our approach can help improve application throughput by 27--138%. Through our case studies on real-world applications, we show that all of our proposed approaches can provide valuable support to developers and help improve application performance significantly.