UWSpace

UWSpace is the University of Waterloo’s institutional repository for the free, secure, and long-term home of research produced by faculty, students, and staff.

Depositing Theses/Dissertations or Research to UWSpace

Are you a Graduate Student depositing your thesis to UWSpace? See our Thesis Deposit Help and UWSpace Thesis FAQ pages to learn more.

Are you a Faculty or Staff member depositing research to UWSpace? See our Waterloo Research Deposit Help and Self-Archiving pages to learn more.

Photo by Waterloo staff

Communities in UWSpace

Select a community to browse its collections.

Recent Submissions

  • Thumbnail Image
    Item type: Item ,
    The Unreasonable Aesthetic of Mathematics in the Sciences
    (University of Waterloo, 2026-04-23) Naik, Armand
    Eugene Wigner was a Nobel prize winning physicist, recognized for his work related to fundamental symmetry principles. In his 1960 speech-turned-publication, “The Unreasonable Effectiveness of Mathematics in the Natural Sciences” he claimed that some applications of math are miraculous. He was amazed that mathematical concepts appear unexpectedly in the natural science of physics, and when they do appear, they are often inspired by intuitions of beauty. Still, applied mathematics shows accurate measurements with unparalleled regularity and precision. In his discussion, Wigner defines mathematics and physics before delving into the role and success of mathematics in the natural sciences. Yet estranged from the rest of the text, the example he opens with discusses the social sciences. Though Wigner can be read as providing an account of why math is justified, at least within physics, the application of math within social sciences, like economics, is left for the reader to ponder. The following is an extension of Wigner’s curiosity applied to the social sciences, with particular attention to the role of beauty in applied mathematics. The central research question is the following: do the same aesthetic principles that define the miraculous application of mathematics in physics, apply in economics? After examining Wigner’s (1960) original paper, I draw upon the work of Areezo Islami (2016), Mark Wilson (2000), Nancy Cartwright (1999), Jennifer Jhun (2016), and Philip Mirowski (2012) to develop aesthetic categories that serve three purposes: (1) they provide clear vocabulary for explaining why certain theories and applied mathematics are found convincing, by identifying the aesthetic principles that underwrite belief in them; (2) they enable the retrospective abstraction of successful theories, allowing us to abstract and articulate the aesthetic criteria of successful theories and then attempt to reverse engineer their success using those same aesthetic principles; and (3) they establish a standpoint for evaluating new ideas, either by assessing their conformity to existing aesthetic standards or by identifying the emergence of new ones.
  • Thumbnail Image
    Item type: Item ,
    Association between the use of Accredited Social Health Activist (ASHA) services and uptake of institutional deliveries in India
    (Public Library of Science, 2024-01-16) Mishra, Sujata; Horton, Susan; Bhutta, Zulfiqar A.; Essue, Beverley M.
    This study examines the impact of accredited social health activists (ASHAs), on increasing rates of institution-based deliveries among Indian women with a specific focus on the nine low-performing, empowered action group states and Assam (EAGA) in India. Using the latest round of the National Family Health Survey-V (2019–21), we first investigate the association between the use of ASHA services and socio-demographic attributes of women using a multivariate logistic regression. We then use propensity-score matching (PSM) to address observable selection bias in the data and assess the impact of ASHA services on the likelihood of institution-based deliveries using a generalized estimating equations model. Of the 232,920 women in our sample, 55.5% lived in EAGA states. Overall, 63.3% of women (70.6% in EAGA states) reported utilizing ASHA services, and 88.6% had an institution-based delivery (84.0% in EAGA states). Younger women from the poorest wealth index were more likely to use ASHA services and women in rural areas had a two-fold likelihood. Conversely, women with health insurance were less likely to use ASHA services compared to those without. Using PSM, the average treatment effect of using ASHA services on institution-based deliveries was 5.1% for all India (EAGA = 7.4%). The generalized estimating equations model indicated that the use of ASHA services significantly increased the likelihood of institution-based delivery by 1.6 times (95%CI = 1.5–1.7) for all India (EAGA = 1.8; 95%CI = 1.7–1.9). Our study finds that ASHAs are effective in enhancing the uptake of maternal services particularly institution-based deliveries. These findings underscore the necessity for continual, systematic investments to strengthen the ASHA program and to optimize the program’s effectiveness in varied settings that rely on the community health worker model, thereby advancing child and maternal health outcomes.
  • Thumbnail Image
    Item type: Item ,
    Understanding the Impact of Inputs on LLM-Based Automated Test Generation
    (University of Waterloo, 2026-04-23) Agarwal, Saarang
    Large Language Models (LLMs) and software development agents are driving a paradigm shift in software engineering, transitioning the field from a human-first to an Artificial Intelligence (AI)-first approach to development. This shift has significantly improved the efficiency of tasks such as code generation and automated testing. However, the performance of these LLMs and agents remains highly dependent on the quality and type of input information they receive. This thesis investigates how different types of input and contextual information influence the effectiveness of LLMs and automated test generation agents through two studies: one focusing on LLMs and the other on test generation agents, each using a distinct dataset. The first study focuses on LLMs and the impact of different inputs on their ability to generate unit tests, with particular emphasis on the availability of software requirements and the correctness of the code under test. We evaluate five state-of-the-art LLMs of varying scales on the CodeChef dataset and analyze how different input configurations affect the correctness, bug detection capability, and code coverage of the generated unit tests. Our findings indicate that combining code with clear requirements produces the highest quality test cases, whereas generating tests from incorrect code alone yields significantly poorer results. The second study focuses on understanding which features of bug reports influence the performance of test generation agents in generating bug-reproducing tests. We identify a set of salient features in bug reports and manually annotate 709 reports from the SWT Bench Lite and Verified datasets based on the presence of these features. Using selected agents from the SWT-Bench leaderboards, we analyze their test generation capabilities and examine overlaps in the bug reports they resolve. We further leverage the annotated dataset to assess how these features affect agent performance and conduct statistical analyses to determine their relative importance in enabling agents to generate bug-reproducing tests. Our findings indicate that including natural-language solutions, localization information, and descriptions of correct behavior is associated with improved performance in bug-reproducing test generation. Moreover, different agents prioritize different features, reflecting variations in their underlying architectures and LLMs. Together, these studies provide critical insights into how different types of information influence the effectiveness of LLMs and test generation agents. Readers can use these insights to guide the effective use of current LLMs and agents, as well as to inform the design and development of future systems.
  • Thumbnail Image
    Item type: Item ,
    SQLyzr: A Comprehensive Benchmark and Framework for Evaluating Text-to-SQL Systems
    (University of Waterloo, 2026-04-23) Abedini, Sepideh
    Natural language–to–SQL (text-to-SQL) systems aim to enable users to interact with relational databases using natural language instead of SQL. Recent advances in large language models have significantly improved the performance of these systems, making them increasingly practical for real-world applications. With the rapid pace of progress and the growing adoption of text-to-SQL systems, robust benchmarking has become essential. However, existing benchmarks typically rely on a single correctness metric, lack alignment with real-world query usage patterns, and do not evaluate the scalability of generated queries, which limits their ability to provide realistic and practically meaningful evaluation. This thesis introduces SQLyzr, a comprehensive text-to-SQL benchmark and evaluation framework designed to address these limitations. SQLyzr incorporates a fine-grained taxonomy of SQL queries and reports evaluation results at the level of query categories and subcategories, enabling detailed insights into system performance across different query types. In addition, SQLyzr extends traditional evaluation by introducing complementary metrics that assess not only the correctness but also the efficiency and structural complexity of generated SQL queries. To better reflect real-world usage, SQLyzr aligns the distribution of query categories with empirical SQL workload distributions and supports dataset scaling to enable evaluation on larger databases. Building on these ideas, we also introduce a configurable text-to-SQL benchmarking framework that allows users to customize and extend benchmark components such as workloads, datasets, and evaluation metrics. The framework further provides novel features such as detailed error analysis for identifying incorrect queries with minor issues and workload augmentation for synthesizing additional question-SQL pairs that target weaknesses of a given text-to-SQL system. We use SQLyzr to evaluate two state-of-the-art text-to-SQL systems with similar overall correctness scores. Our results demonstrate that SQLyzr enables clearer comparison between systems and reveals deeper insights into their relative strengths and weaknesses.
  • Thumbnail Image
    Item type: Item ,
    State Complexity of Linear Relations and Linear Subsequences of Automatic Sequences
    (University of Waterloo, 2026-04-23) Moradi, Delaram
    In this thesis, we study the state complexity of specific formal languages; for example, we study the number of states required in the minimal automaton reading the representation of two integers $i, j$ in parallel and accepting them if and only $i+c = j$ for some constant integer $c \geq 1$. We also study the state complexity of linear subsequences of automatic sequences; for example, we study the number of states required in the minimal automaton generating the linear subsequence $(h(i+c))_{i \geq 0}$ for some automatic sequences $(h(i))_{i \geq 0}$ and some constant integer $c \geq 1$. Moreover, we study the runtime complexity of generating automata for specific formal languages and linear subsequences of automatic sequences using a reasonable interpretation of B\"uchi arithmetic; for example we study the runtime complexity of creating an automaton reading the representation of two integers $i, j$ in parallel and accepting them if and only if $ni=j$ for some constant $n \geq 2$. We also state some open problems. The above topics are studied both for automata with input in base-$k$ representation for some integer $k \geq 2$ and for automata with input in Fibonacci representation. Most results are for automata reading input in most-significant-digit-first format and some results are stated for automata reading input in least-significant-digit-first format.