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.

SENSORIMOTOR WORKING MEMORY CAPACITY LIMITS

Two novel studies examining the capacity and characteristics of working memory for object weights, experienced through lifting, were completed. Both studies employed visually identical objects of varying weight and focused on memories linking object locations and weights. Whereas numerous studies have examined the capacity of visual working memory, the capacity of sensorimotor memory involved in motor control and object manipulation has not yet been explored. In addition to assessing working memory for object weights using an explicit perceptual test, we also assessed memory for weight using an implicit measure based on motor performance. The vertical lifting or LF and the horizontal GF applied during lifts, measured from force sensors embedded in the object handles, were used to assess participants’ ability to predict object weights. In Experiment 1, participants were presented with sets of 3, 4, 5, 7 or 9 objects. They lifted each object in the set and then repeated this procedure 10 times with the objects lifted either in a fixed or random order. Sensorimotor memory was examined by assessing, as a function of object set size, how lifting forces changed across successive lifts of a given object. The results indicated that force scaling for weight improved across the repetitions of lifts, and was better for smaller set sizes when compared to the larger set sizes, with the latter effect being clearest when objects were lifting in a random order. However, in general the observed force scaling was poorly scaled. In Experiment 2, working memory was examined in two ways: by determining participants’ ability to detect a change in the weight of one of 3 to 6 objects lifted twice, and by simultaneously measuring the fingertip forces applied when lifting the objects. The results showed that, even when presented with 6 objects, participants were extremely accurate in explicitly detecting which object changed weight. In addition, force scaling for object weight, which was generally quite weak, was similar across set sizes. Thus, a capacity limit less than 6 was not found for either the explicit or implicit measures collected.

Fleshing Out and Losing Flesh: The Decomposing Corpse as Narrative Object in American Hardboiled Detective Fiction

This dissertation examines the corpse as an object in and of American hardboiled detective fiction written between 1920 and 1950. I deploy several theoretical frames, including narratology, body-as-text theory, object relations theory, and genre theory, in order to demonstrate the significance of objects, symbols, and things primarily in the clever and crafty work of Dashiell Hammett (1894-1961) and Raymond Chandler (1888-1959), but also touching on the writings of their lesser known accomplices. I construct a literary genealogy of American hardboiled detective fiction originating in the writings of Edgar Allan Poe, compare the contributions of classic or Golden Age detective fiction in England, and describe the socio-economic contexts, particularly the predominance of the “pulps,” that gave birth to the realism of the Hardboiled School. Taking seriously Chandler’s obsession with the art of murder, I engage with how authors pre-empt their readers’ knowledge of the tricks of the trade and manipulate their expectations, as well as discuss the characteristics and effect of the inimitable hardboiled style, its sharpshooting language and deadpan humour. Critical scholarship has rarely addressed the body and figure of the corpse, preferring to focus instead on the machinations of the femme fatale, the performance of masculinity, or the prevalence of violence. I cast new light on the world of hardboiled detective fiction by dissecting the corpse as the object that both motivates and de-composes (or rots away from) the narrative that makes it signify. I treat the corpse as an inanimate object, indifferent to representation, that destabilizes the integrity and self-possession, as well as the ratiocination, of the detective who authors the narrative of how the corpse came to be. The corpse is all deceptive and dangerous surface rather than the container of hidden depths of life and meaning that the detective hopes to uncover and reconstruct. I conclude with a chapter that is both critical denouement and creative writing experiment to reveal the self-reflexive (and at times metafictional) dimensions of hardboiled fiction. My dissertation, too, in the manner of hardboiled fiction, hopes to incriminate my readers as much as enlighten them.