Code anomalies, also known as code smells, are any characteristics in software code that indicate amore severe problem exists deep in the code. These anomalies do not always prevent a system fromfunctioning, but they can restrict development and increase the difficulty of maintaining the software.The idea of code anomalies in conventional software is the subject of many research papers. However,very few explicitly examine web application anomalies and offer solutions to web applicationanomalies. Additionally, there aren't enough studies looking at whether anomalies found inconventional software systems can also be found in web applications. Web application code anomaliesmay potentially differ from traditional software systems in a few ways. For instance, web applicationshave a client-server architecture that can create unique challenges for communication between theclient and server. This may result in code anomalies that relate to network delays or resource-intensiveoperations. Additionally, web applications often rely on third-party libraries and frameworks, whichcan introduce additional code anomalies. This study aims to fill the gaps mentioned above byinvestigating code anomalies in web applications using a systemic mapping study. This study usessystematic mapping to collect and analyze literature through predefined criteria and procedures.Furthermore, this study provides an overview of approaches and tools that can identify and detectanomalies, determine where code anomalies occur, and whether refactoring has been considered. Theresults of this study show that there’s a wide array of techniques to detect anomalies, code anomaliesoccur everywhere. Refactoring is a technique to solve code anomalies and while there are alreadymany refactoring techniques cataloged for traditional software, there is a lack of refactoringsspecifically cataloged for web applications.

How can observation of a legacy system be used for design? To answer this question, we observed a teacher doing live coding with a conventional code editor and used the observations to design an editor better suited to this style of teaching. In particular, we found strong evidence that a projectional editor would better meet this need. Reflecting on this experience, we describe two types of requirements which can be inferred from observing a user using a legacy system: hidden requirements, in which users use existing features in unexpected ways, and novel requirements inferred from pain points observed in current system use. / Thesis / Master of Applied Science (MASc)

Software bugs prediction is one of the most active research areas in the software engineering community. The process of testing and debugging code proves to be costly during the software development life cycle. Software metrics measure the quality of source code to identify software bugs and vulnerabilities. Traceable code patterns are able to de- scribe code at a finer granularity level to measure quality. Micro patterns will be used in this research to mechanically describe java code at the class level. Machine learning has also been introduced for bug prediction to localize source code for testing and debugging. Deep Learning is a branch of Machine Learning that is relatively new. This research looks to improve the prediction of software bugs by utilizing micro patterns with deep learning techniques. Software bug prediction at a finer granularity level will enable developers to localize code to test and debug during the development process.

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Loop vectorization is a powerful optimization technique that can significantly boost the runtime of loops. This optimization depends on functional equivalence between the original and optimized code versions, a requirement typically established through the compiler's static analysis. When this condition is not met, the compiler will miss the optimization. The process of manually rewriting the source code to pass an already missed compiler optimization is time-consuming, given the multitude of potential code variations, and demands a high level of expertise, making it impractical in many scenarios. In this work, we propose a novel framework that aims to take the code blocks that the compiler failed to optimize and transform them to another code block that passes the compiler optimization. We develop an algorithm to efficiently search for a code structure that automatically passes the compiler optimization (weakly verified through a correctness test). We focus on loop-vectorize optimization inside OpenMP directives, where the introduction of parallelism adds complexity to the compiler's vectorization task and is shown to hinder optimizations. Furthermore, we introduce a modified version of TSVC, a loop vectorization benchmark in which all original loops are executed within OpenMP directives. Our evaluation shows that our framework enables " loop-vectorize" optimizations that the compiler failed to pass, resulting in a speedup up to 340× in the blocks optimized. Furthermore, applying our tool to HPC benchmark applications, where those applications are already built with optimization and performance in mind, demonstrates that our technique successfully enables extended compiler optimization, thereby accelerating the execution time of the optimized blocks in 15 loops and the entire execution time of the three applications by up to 1.58 times. / Master of Science / Loop vectorization is a powerful technique for improving the performance of specific sections in computer programs known as loops. Particularly, it simultaneously executes instructions of different iterations in a loop, providing a considerable speedup on its runtime due to this parallelism. To apply this optimization, the code needs to meet certain conditions, which are usually checked by the compiler. However, sometimes the compiler cannot verify these conditions, and the optimization fails. Our research introduces a new approach to fix these issues automatically. Normally, fixing the code manually to meet these conditions is time-consuming and requires high expertise. To overcome this, we've developed a tool that can efficiently find ways to make the code satisfy the conditions needed for optimization. Our focus is on a specific type of code that uses OpenMP directives to split the loop on multiple processor cores and runs them simultaneously, where adding this parallelism makes the code more complex for the compiler to optimize. Our tests show that our approach successfully improves the speed of computer programs by enabling optimizations initially missed by the compiler. This results in significant speed improvements for specific parts of the code, sometimes up to 340 times faster. We've also applied our method to well-optimized computer programs, and it still managed to make them run up to 1.58 times faster.

This thesis identifies two accounts within David Novak’s Jewish natural law theory. In the earlier account, Novak locates natural law within the Noahide commandments; in the later account, he also locates it within the reasons for the commandments and rabbinic enactments. The change between these accounts is marked by a shift in his description of rationality. The norms of the Noahide code are originally described as known strictly by reference to themselves. As he begins grounding the norms in the imago Dei, that knowledge becomes dependent on a “cultural heritage,” by which Novak comes to mean an explanation based on a doctrine of creation. By comparing the original presentation of the later account with its more developed iteration and highlighting the features that are unique to the earlier and later accounts, it becomes possible to identify components of the later account that are added to his subsequent treatment of the Noahide code and facets of the earlier account that are later added to his discussion of the reasons for the commandments and rabbinic enactments. These efforts at reconciliation include the normative content incorporated into the later account, the metaphysical background added to the later treatment of the Noahide code, the mediating concept of personhood, the phenomenological retrieval of the Noahide commandments, and the argument for minimal and maximal claims. Finally, this thesis analyzes the relationship between Novak’s natural law theory and his view of redemption. Given that as Novak’s natural law theory becomes less dependent on reason and more heavily based on a doctrine of creation, his treatment of redemption changes from being associated with a period of greater human understanding to a time that is characterized by God’s accomplishments on humanity’s behalf, I argue that there is a parallel between those concepts. I then draw on that parallel to show that Novak’s natural law is compatible with, and perhaps inseparable from, his covenantal thought. / Thesis / Doctor of Philosophy (PhD)

Drasil is a framework for generating high-quality documentation and code for Scientific Computing Software (SCS). Despite the tendency of SCS code to follow an Input-Calculate-Output design pattern, there are many design variabilities in SCS. Drasil should therefore allow its users to specify a design for their generated program. To this end, a language that encodes the design variabilities present in SCS was implemented in Drasil. Drasil's code generator was updated to generate code based on a user's design choices. A Generic Object-Oriented Language, GOOL, from which Python, Java, C#, or C++ code can be generated, was implemented. Drasil's code generator targets GOOL, enabling the choice of programming language to be included in the design language. Other choices included in the language are related to the modularity, the generation of record classes to bundle variables, the inlining of constants, the code types used to represent different mathematical spaces, which external library to use to solve ODEs, the behaviour when a constraint is violated, and the presence of documentation, logging, or a controller. The design language is implemented as a record type in Haskell, and is designed to be understandable, extensible, and usable. A design specification can be easily changed, to generate a different version of the same program, which would often require time-consuming refactoring if the program was written manually. During the regular build process of Drasil, working code is generated in all four target languages for three examples of SCS, each using a different design specification. / Thesis / Master of Applied Science (MASc)