Programming Languages and Compilers Commons^™

Improving Developers' Understanding Of Regex Denial Of Service Tools Through Anti-Patterns And Fix Strategies, Sk Adnan Hassan, Zainab Aamir, Dongyoon Lee, James C. Davis, Francisco Servant

Department of Electrical and Computer Engineering Faculty Publications

Regular expressions are used for diverse purposes, including input validation and firewalls. Unfortunately, they can also lead to a security vulnerability called ReDoS (Regular Expression Denial of Service), caused by a super-linear worst-case execution time during regex matching. Due to the severity and prevalence of ReDoS, past work proposed automatic tools to detect and fix regexes. Although these tools were evaluated in automatic experiments, their usability has not yet been studied; usability has not been a focus of prior work. Our insight is that the usability of existing tools to detect and fix regexes will improve if we complement them …

Advances In The Automatic Detection Of Optimization Opportunities In Computer Programs, Delaram Talaashrafi

Electronic Thesis and Dissertation Repository

Massively parallel and heterogeneous systems together with their APIs have been used for various applications. To achieve high-performance software, the programmer should develop optimized algorithms to maximize the system’s resource utilization. However, designing such algorithms is challenging and time-consuming. Therefore, optimizing compilers are developed to take part in the programmer’s optimization burden. Developing effective optimizing compilers is an active area of research. Specifically, because loop nests are usually the hot spots in a program, their optimization has been the main subject of many optimization algorithms. This thesis aims to improve the scope and applicability of performance optimization algorithms used in …

Examining The Relationship Between Stomiiform Fish Morphology And Their Ecological Traits, Mikayla L. Twiss

All HCAS Student Capstones, Theses, and Dissertations

Trait-based ecology characterizes individuals’ functional attributes to better understand and predict their interactions with other species and their environments. Utilizing morphological traits to describe functional groups has helped group species with similar ecological niches that are not necessarily taxonomically related. Within the deep-pelagic fishes, the Order Stomiiformes exhibits high morphological and species diversity, and many species undertake diel vertical migration (DVM). While the morphology and behavior of stomiiform fishes have been extensively studied and described through taxonomic assessments, the connection between their form and function regarding their DVM types, morphotypes, and daytime depth distributions is not well known. Here, three …

A Logistic Regression And Linear Programming Approach For Multi-Skill Staffing Optimization In Call Centers, Thuy Anh Ta, Tien Mai, Fabian Bastin, Pierre L'Ecuyer

Research Collection School Of Computing and Information Systems

We study a staffing optimization problem in multi-skill call centers. The objective is to minimize the total cost of agents under some quality of service (QoS) constraints. The key challenge lies in the fact that the QoS functions have no closed-form and need to be approximated by simulation. In this paper we propose a new way to approximate the QoS functions by logistic functions and design a new algorithm that combines logistic regression, cut generations and logistic-based local search to efficiently find good staffing solutions. We report computational results using examples up to 65 call types and 89 agent groups …

Conversation Disentanglement With Bi-Level Contrastive Learning, Chengyu Huang, Hao Fei, Lizi Liao, Lizi Liao

Research Collection School Of Computing and Information Systems

Conversation disentanglement aims to group utterances into detached sessions, which is a fundamental task in processing multi-party conversations. Existing methods have two main drawbacks. First, they overemphasize pairwise utterance relations but pay inadequate attention to the utterance-to-context relation modeling. Second, a huge amount of human annotated data is required for training, which is expensive to obtain in practice. To address these issues, we propose a general disentangle model based on bi-level contrastive learning. It brings closer utterances in the same session while encourages each utterance to be near its clustered session prototypes in the representation space. Unlike existing approaches, our …

R2f: A General Retrieval, Reading And Fusion Framework For Document-Level Natural Language Inference, Hao Wang, Yixin Cao, Yangguang Li, Zhen Huang, Kun Wang, Jing Shao

Research Collection School Of Computing and Information Systems

Document-level natural language inference (DocNLI) is a new challenging task in natural language processing, aiming at judging the entailment relationship between a pair of hypothesis and premise documents. Current datasets and baselines largely follow sentence-level settings, but fail to address the issues raised by longer documents. In this paper, we establish a general solution, named Retrieval, Reading and Fusion (R2F) framework, and a new setting, by analyzing the main challenges of DocNLI: interpretability, long-range dependency, and cross-sentence inference. The basic idea of the framework is to simplify document-level task into a set of sentence-level tasks, and improve both performance and …

Evaluation Of Distributed Programming Models And Extensions To Task-Based Runtime Systems, Yu Pei

Doctoral Dissertations

High Performance Computing (HPC) has always been a key foundation for scientific simulation and discovery. And more recently, deep learning models' training have further accelerated the demand of computational power and lower precision arithmetic. In this era following the end of Dennard's Scaling and when Moore's Law seemingly still holds true to a lesser extent, it is not a coincidence that HPC systems are equipped with multi-cores CPUs and a variety of hardware accelerators that are all massively parallel. Coupling this with interconnect networks' speed improvements lagging behind those of computational power increases, the current state of HPC systems is …

Using Landsat Satellite Imagery To Estimate Groundcover In The Grainbelt Of Western Australia, Justin Laycock, Nick Middleton, Karen Holmes

Resource management technical reports

Maintaining vegetative groundcover is an important component of sustainable agricultural systems and plays a critical function for soil and land conservation in Western Australia’s (WA) grainbelt (the south-west cropping region). This report describes how satellite imagery can be used to quantitatively and objectively estimate total vegetative groundcover, both in near real time and historically across large areas. We used the Landsat seasonal fractional groundcover products developed by the Joint Remote Sensing Research Program from the extensive archive of Landsat imagery. These products provide an estimate of the percentage of green vegetation, non-green vegetation and bare soil for each 30 m …

Three Contributions To The Theory And Practice Of Optimizing Compilers, Linxiao Wang

Electronic Thesis and Dissertation Repository

The theory and practice of optimizing compilers gather techniques that, from input computer programs, aim at generating code making the best use of modern computer hardware. On the theory side, this thesis contributes new results and algorithms in polyhedral geometry. On the practical side, this thesis contributes techniques for the tuning of parameters of programs targeting GPUs. We detailed these two fronts of our work below.

Consider a convex polyhedral set P given by a system of linear inequalities A*x <= b, where A is an integer matrix and b is an integer vector. We are interested in the integer hull P_I of P which is the smallest convex polyhedral set that contains all the integer points in P. In Chapter …

Compilation Optimizations To Enhance Resilience Of Big Data Programs And Quantum Processors, Travis D. Lecompte

LSU Doctoral Dissertations

Modern computers can experience a variety of transient errors due to the surrounding environment, known as soft faults. Although the frequency of these faults is low enough to not be noticeable on personal computers, they become a considerable concern during large-scale distributed computations or systems in more vulnerable environments like satellites. These faults occur as a bit flip of some value in a register, operation, or memory during execution. They surface as either program crashes, hangs, or silent data corruption (SDC), each of which can waste time, money, and resources. Hardware methods, such as shielding or error correcting memory (ECM), …

Large-Scale Analysis Of Non-Termination Bugs In Real-World Oss Projects, Xiuhan Shi, Xiaofei Xie, Yi Li, Yao Zhang, Sen Chen, Xiaohong Li

Research Collection School Of Computing and Information Systems

Termination is a crucial program property. Non-termination bugs can be subtle to detect and may remain hidden for long before they take effect. Many real-world programs still suffer from vast consequences (e.g., no response) caused by non-termination bugs. As a classic problem, termination proving has been studied for many years. Many termination checking tools and techniques have been developed and demonstrated effectiveness on existing wellestablished benchmarks. However, the capability of these tools in finding practical non-termination bugs has yet to be tested on real-world projects. To fill in this gap, in this paper, we conducted the first large-scale empirical study …

Investigating Bloom's Cognitive Skills In Foundation And Advanced Programming Courses From Students' Discussions, Joel Jer Wei Lim, Gottipati Swapna, Kyong Jin Shim

Research Collection School Of Computing and Information Systems

Programming courses provide students with the skills to develop complex business applications. Teaching and learning programming is challenging, and collaborative learning is proposed to help with this challenge. Online discussion forums promote networking with other learners such that they can build knowledge collaboratively. It aids students open their horizons of thought processes to acquire cognitive skills. Cognitive analysis of discussion is critical to understand students' learning process. In this paper, we propose Bloom's taxonomy based cognitive model for programming discussion forums. We present machine learning (ML) based solution to extract students' cognitive skills. Our evaluations on compupting courses show that …

Vlstereoset: A Study Of Stereotypical Bias In Pre-Trained Vision-Language Models, Kankan Zhou, Yibin Lai, Jing Jiang

Research Collection School Of Computing and Information Systems

In this paper we study how to measure stereotypical bias in pre-trained vision-language models. We leverage a recently released text-only dataset, StereoSet, which covers a wide range of stereotypical bias, and extend it into a vision-language probing dataset called VLStereoSet to measure stereotypical bias in vision-language models. We analyze the differences between text and image and propose a probing task that detects bias by evaluating a model’s tendency to pick stereotypical statements as captions for anti-stereotypical images. We further define several metrics to measure both a vision-language model’s overall stereotypical bias and its intra-modal and inter-modal bias. Experiments on six …

Languages And Compilers For Writing Efficient High-Performance Computing Applications, Abhinav Jangda

Doctoral Dissertations

Many everyday applications, such as web search, speech recognition, and weather prediction, are executed on high-performance systems containing thousands of Central Processing Units (CPUs) and Graphics Processing Units (GPUs). These applications can be written in either low-level programming languages, such as NVIDIA CUDA, or domain specific languages, like Halide for image processing and PyTorch for machine learning programs. Despite the popularity of these languages, there are several challenges that programmers face when developing efficient high-performance computing applications. First, since every hardware support a different low-level programming model, to utilize new hardware programmers need to rewrite their applications in another programming …

Transrepair: Context-Aware Program Repair For Compilation Errors, Xueyang Li, Shangqing Liu, Ruitao Feng, Guozhu Meng, Xiaofei Xie, Kai Chen, Yang Liu

Research Collection School Of Computing and Information Systems

Automatically fixing compilation errors can greatly raise the productivity of software development, by guiding the novice or AI programmers to write and debug code. Recently, learning-based program repair has gained extensive attention and became the stateof-the-art in practice. But it still leaves plenty of space for improvement. In this paper, we propose an end-to-end solution TransRepair to locate the error lines and create the correct substitute for a C program simultaneously. Superior to the counterpart, our approach takes into account the context of erroneous code and diagnostic compilation feedback. Then we devise a Transformer-based neural network to learn the ways …

Towards Understanding The Faults Of Javascript-Based Deep Learning Systems, Lili Quan, Qianyu Guo, Xiaofei Xie, Sen Chen, Xiaohong Li, Yang Liu

Research Collection School Of Computing and Information Systems

Quality assurance is of great importance for deep learning (DL) systems, especially when they are applied in safety-critical applications. While quality issues of native DL applications have been extensively analyzed, the issues of JavaScript-based DL applications have never been systematically studied. Compared with native DL applications, JavaScript-based DL applications can run on major browsers, making the platform- and device-independent. Specifically, the quality of JavaScript-based DL applications depends on the 3 parts: the application, the third-party DL library used and the underlying DL framework (e.g., TensorFlow.js), called JavaScript-based DL system. In this paper, we conduct the first empirical study on the …

How Many Mutex Bugs Can A Simple Analysis Find In Go Programs?, Fumi Takeuchi, Hidehiko Masuhara, Raffi T. Khatchadourian, Youyou Cong, Keisuke Ishibashi

Publications and Research

In open-source software, it is known that there are many concurrency bugs. A previous study in Go revealed that a considerable number of such bugs are simple (for example, 9% of the bugs are the ones that forget to unlock a mutex,) through a manual program investigation. This paper tries to detect such bugs by applying a simple analysis to see how far such a tool can match the manual analysis. We built a simple intraprocedural control flow analysis in Go, and evaluated its performance concerning the open source programs with concurrency bugs reported in the previous study. Consequently, as …

User Guided Abductive Proof Generation For Answer Set Programming Queries, Avishkar Mahajan, Martin Strecker, Meng Weng (Huang Mingrong) Wong

Research Collection Yong Pung How School Of Law

We present a method for generating possible proofs of a query with respect to a given Answer Set Programming (ASP) rule set using an abductive process where the space of abducibles is automatically constructed just from the input rules alone. Given a (possibly empty) set of user provided facts, our method infers any additional facts that may be needed for the entailment of a query and then outputs these extra facts, without the user needing to explicitly specify the space of all abducibles. We also present a method to generate a set of directed edges corresponding to the justification graph …

Effective Knowledge Graph Aggregation For Malware-Related Cybersecurity Text, Phillip Ryan Boudreau

Graduate Theses and Dissertations

With the rate at which malware spreads in the modern age, it is extremely important that cyber security analysts are able to extract relevant information pertaining to new and active threats in a timely and effective manner. Having to manually read through articles and blog posts on the internet is time consuming and usually involves sifting through much repeated information. Knowledge graphs, a structured representation of relationship information, are an effective way to visually condense information presented in large amounts of unstructured text for human readers. Thusly, they are useful for sifting through the abundance of cyber security information that …

Task-Based Runtime Optimizations Towards High Performance Computing Applications, Qinglei Cao

Doctoral Dissertations

The last decades have witnessed a rapid improvement of computational capabilities in high-performance computing (HPC) platforms thanks to hardware technology scaling. HPC architectures benefit from mainstream advances on the hardware with many-core systems, deep hierarchical memory subsystem, non-uniform memory access, and an ever-increasing gap between computational power and memory bandwidth. This has necessitated continuous adaptations across the software stack to maintain high hardware utilization. In this HPC landscape of potentially million-way parallelism, task-based programming models associated with dynamic runtime systems are becoming more popular, which fosters developers’ productivity at extreme scale by abstracting the underlying hardware complexity.

In this context, …