Software Engineering Commons^™

Transfer Equivalency Site For The Registrar, Janelle N. Rohrbach, Alissa C. Cielecki, Jules A. Turner

Capstone Showcase

The website, arcadia-transfer-equiv.com, was drafted and created for Bill Enick, Registrar at Arcadia University. This was an expansion of a preliminary version of the website created by Caleigh Diefenthaler, Christian Charney, and Dylan Power. The site includes two transfer equivalency tools which can be used to search for course equivalencies by academic institution or by a given Arcadia course. The tools, which pull from a database maintained by the Registrar, will display courses that have transferred to the University successfully. The website also hosts two interactive forms. These forms allow Arcadia students to request approval for courses that have or …

Managing Inventory: A Study Of Databases And Database Management Systems, Jemal M. Jemal

Senior Independent Study Theses

Databases play an important role in the storage and manipulation of data. Databases and database management systems allow for fast and efficient data querying that has recently become increasingly important in most companies and organizations. This paper introduces a few of the different types of database management systems that are in widespread use today. It introduces some important terminology related to databases and database management systems. This paper also briefly discusses web user interfaces, highlighting important user interface design principles. Finally, an inventory management system is implemented for a local stationery store and is integrated with a web application to …

Sop Development For Erp/Software Project Management Of A Consulting Company, Piyanat Viengcome

Chulalongkorn University Theses and Dissertations (Chula ETD)

Presently, ERP/software consulting company has experienced in information gathering process from users in customer company which lead to insufficient to-be process development and vendor selection process. The unexpected results would be extra budget and high manual workload in organization. The possible root cause is uncleared procedure to proceed the project management in ERP/software implementation. The objective of this research is to develop the standard operating procedure for ERP/software project management of a consulting company concentrated in manufacturing industry in Thailand. The methodology starts with studying of competitors' approach from their websites. The ERP expert interview is the next step, 3 …

Optimal Management Of Virtual Infrastructures Under Flexible Cloud Service Agreements, Zhiling Guo, Jin Li, Ram Ramesh

Research Collection School Of Computing and Information Systems

A cloud service agreement entails the provisioning of a required set of virtual infrastructure resources at a specified level of availability to a client. The agreement also lays out the price charged to the client and a penalty to the provider when the assured availability is not met. The availability assurance involves backup resource provisioning, and the provider needs to allocate backups cost-effectively by balancing the resource-provisioning costs with the potential penalty costs. We develop stochastic dynamic optimization models of the backup resource-provisioning problem, leading to cost-effective resource-management policies in different practical settings. We present two sets of dynamic provisioning …

Twenty Years Of Open Source Software: From Skepticism To Mainstream, Gregorio Robles, Igor Steinmacher, Paul Adams, Christoph Treude

Research Collection School Of Computing and Information Systems

Open source software (OSS) has conquered the software world. You can see it nearly everywhere, from Internet infrastructure to mobile phones to the desktop. In addition to that, although many OSS practices were viewed with skepticism 20 years ago, several have become mainstream in software engineering today: from development tools such as Git to practices such as modern code reviews.

Salience-Aware Adaptive Resonance Theory For Large-Scale Sparse Data Clustering, Lei Meng, Ah-Hwee Tan, Chunyan Miao

Research Collection School Of Computing and Information Systems

Sparse data is known to pose challenges to cluster analysis, as the similarity between data tends to be ill-posed in the high-dimensional Hilbert space. Solutions in the literature typically extend either k-means or spectral clustering with additional steps on representation learning and/or feature weighting. However, adding these usually introduces new parameters and increases computational cost, thus inevitably lowering the robustness of these algorithms when handling massive ill-represented data. To alleviate these issues, this paper presents a class of self-organizing neural networks, called the salience-aware adaptive resonance theory (SA-ART) model. SA-ART extends Fuzzy ART with measures for cluster-wise salient feature modeling. …

Influence, Information And Team Outcomes In Large Scale Software Development, Subhajit Datta

Research Collection School Of Computing and Information Systems

It is widely perceived that the egalitarian ecosystems of large scale open source software development foster effective team outcomes. In this study, we question this conventional wisdom by examining whether and how the centralization of information and influence in a software development team relate to the quality of the team's work products. Analyzing data from more than a hundred real world projects that include development activities over close to a decade, involving 2000+ developers, who collectively resolve more than two hundred thousand defects through discussions covering more than six hundred thousand comments, we arrive at statistically significant evidence indicating that …

Automatic Recall Of Software Lessons Learned For Software Project Managers, Tamer Mohamed Abdellatif Mohamed, Luiz Fernando Capretz, Danny Ho

Electrical and Computer Engineering Publications

Context: Lessons learned (LL) records constitute the software organization memory of successes and failures. LL are recorded within the organization repository for future reference to optimize planning, gain experience, and elevate market competitiveness. However, manually searching this repository is a daunting task, so it is often disregarded. This can lead to the repetition of previous mistakes or even missing potential opportunities. This, in turn, can negatively affect the organization’s profitability and competitiveness.

Objective: We aim to present a novel solution that provides an automatic process to recall relevant LL and to push those LL to project managers. This will dramatically …

Automatic Generation Of Pull Request Descriptions, Zhongxin Liu, Xin Xia, Christoph Treude, David Lo, Shanping Li

Research Collection School Of Computing and Information Systems

Enabled by the pull-based development model, developers can easily contribute to a project through pull requests (PRs). When creating a PR, developers can add a free-form description to describe what changes are made in this PR and/or why. Such a description is helpful for reviewers and other developers to gain a quick understanding of the PR without touching the details and may reduce the possibility of the PR being ignored or rejected. However, developers sometimes neglect to write descriptions for PRs. For example, in our collected dataset with over 333K PRs, more than 34% of the PR descriptions are empty. …

Ad-Link: An Adaptive Approach For User Identity Linkage, Xin Mu, Wei Xie, Ka Wei, Roy Lee, Feida Zhu, Ee Peng Lim

Research Collection School Of Computing and Information Systems

User identity linkage (UIL) refers to linking accounts of the same user across different online social platforms. The state-of-the-art UIL methods usually perform account matching using user account’s features derived from the profile attributes, content and relationships. They are however static and do not adapt well to fast-changing online social data due to: (a) new content and activities generated by users; as well as (b) new platform functions introduced to users. In particular, the importance of features used in UIL methods may change over time and new important user features may be introduced. In this paper, we proposed AD-Link, a …

Ml4iot: A Framework To Orchestrate Machine Learning Workflows On Internet Of Things Data, Jose Miguel Alves, Leonardo Honorio, Miriam A M Capretz

Electrical and Computer Engineering Publications

Internet of Things (IoT) applications generate vast amounts of real-time data. Temporal analysis of these data series to discover behavioural patterns may lead to qualified knowledge affecting a broad range of industries. Hence, the use of machine learning (ML) algorithms over IoT data has the potential to improve safety, economy, and performance in critical processes. However, creating ML workflows at scale is a challenging task that depends upon both production and specialized skills. Such tasks require investigation, understanding, selection, and implementation of specific ML workflows, which often lead to bottlenecks, production issues, and code management complexity and even then may …

Why Reinventing The Wheels? An Empirical Study On Library Reuse And Re-Implementation, Bowen Xu, Le An, Ferdian Thung, Foutse Khomh, David Lo

Research Collection School Of Computing and Information Systems

Nowadays, with the rapid growth of open source software (OSS), library reuse becomes more and more popular since a large amount of third- party libraries are available to download and reuse. A deeper understanding on why developers reuse a library (i.e., replacing self-implemented code with an external library) or re-implement a library (i.e., replacing an imported external library with self-implemented code) could help researchers better understand the factors that developers are concerned with when reusing code. This understanding can then be used to improve existing libraries and API recommendation tools for researchers and practitioners by using the developers concerns identified …

Predicting The Hardness Of Turf Surfaces From A Soil Moisture Sensor Using Iot Technologies, Ann Marie Mckeon

Other

In horseracing, “the going” is a term to describe the racetrack ground conditions. In Ireland presently, a groundskeeper or course clerk walks the racecourse poking it with a blackthorn stick, assesses conditions, and declares the going – it is a subjective measurement.

This thesis will propose using remote low-cost soil moisture sensors to gather high frequency data about the soil water content in the ground and to enable informed decisions to be made. This will remove the subjective element from the ground hardness, and look at the data in an objective way.

The soil moisture sensor will systematically collect high …

Industry 4.0: Ethical And Moral Predicaments, W. Wang, Keng Siau

Research Collection School Of Computing and Information Systems

The advancements in software technology and data science are enabling Industry 4.0, aka the Fourth Industrial Revolution or the Industrial Internet of Things (IIoT). While the first three industrial revolutions have brought about immense change, the impact of Industry 4.0 will be much wider and far greater, especially with regard to the easily overlooked ethical and moral aspects. Widening wealth gaps between countries and among classes of people within countries, a potential growing unemployment rate, data privacy and accessibility issues, and the treatment of intelligent agents (e.g., military robots) present new and complex ethical and moral dilemmas. In this article, …

Compositional Coding For Collaborative Filtering, Chenghao Liu, Tao Lu, Xin Wang, Zhiyong Cheng, Jianling Sun, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Efficiency is crucial to the online recommender systems, especially for the ones which needs to deal with tens of millions of users and items. Because representing users and items as binary vectors for Collaborative Filtering (CF) can achieve fast user-item affinity computation in the Hamming space, in recent years, we have witnessed an emerging research effort in exploiting binary hashing techniques for CF methods. However, CF with binary codes naturally suffers from low accuracy due to limited representation capability in each bit, which impedes it from modeling complex structure of the data. In this work, we attempt to improve the …

Redpc: A Residual Error-Based Density Peak Clustering Algorithm, Milan Parmar, Di Wang, Xiaofeng Zhang, Ah-Hwee Tan, Chunyan Miao, You Zhou

Research Collection School Of Computing and Information Systems

The density peak clustering (DPC) algorithm was designed to identify arbitrary-shaped clusters by finding density peaks in the underlying dataset. Due to its aptitudes of relatively low computational complexity and a small number of control parameters in use, DPC soon became widely adopted. However, because DPC takes the entire data space into consideration during the computation of local density, which is then used to generate a decision graph for the identification of cluster centroids, DPC may face difficulty in differentiating overlapping clusters and in dealing with low-density data points. In this paper, we propose a residual error-based density peak clustering …

Keylime, Eli William Partker

Computer Engineering

Josh, Matt and I knew we wanted to develop a mobile app for our senior project because that is what we found ourselves to be most passionate about during our time here at Cal Poly. We started to think of problems we wanted to solve using an application and we came up with a couple ideas but chose to expand on one. Students come to Cal Poly every year new to the area and the food options San Luis Obispo provides. Many of the restaurants in SLO offer a variety of deals to the community and most of them to …

Reach - A Community Service Application, Samuel Noel Magana

Computer Engineering

Communities are familiar threads that unite people through several shared attributes and interests. These commonalities are the core elements that link and bond us together. Many of us are part of multiple communities, moving in and out of them depending on our needs. These common threads allow us to support and advocate for each other when facing a common threat or difficult situation. Healthy and vibrant communities are fundamental to the operation of our society. These interactions within our communities define the way we as individuals interact with each other, and society at large. Being part of a community helps …

Radish: A Cross Platform Meal Prepping App For Beginner Weightlifters, Spoorthy S. Vemula, Tanay Gottigundala, Cory Baxes

Computer Science and Software Engineering

With the increasing ease of access and decreasing price of most food, obesity rates in the developing world have risen dramatically in recent years. As of March 23rd, 2019, obesity rates had reached 39.6%, a 6% increase in just 8 years. Research has shown that people with obesity have a significantly increased risk of heart disease, stroke, type 2 diabetes, and certain cancers, among other life-threatening diseases. In addition, 42% of people who begin weightlifting quit because it’s too difficult to follow a diet or workout regimen.

We created Radish in an attempt to tackle these problems. Radish makes it …

Peerlens: Peer-Inspired Interactive Learning Path Planning In Online Question Pool, Meng Xia, Mingfei Sun, Huan Wei, Qing Chen, Yong Wang, Lei Shi, Huamin Qu, Xiaojuan Ma

Research Collection School Of Computing and Information Systems

Online question pools like LeetCode provide hands-on exercises of skills and knowledge. However, due to the large volume of questions and the intent of hiding the tested knowledge behind them, many users find it hard to decide where to start or how to proceed based on their goals and performance. To overcome these limitations, we present PeerLens, an interactive visual analysis system that enables peer-inspired learning path planning. PeerLens can recommend a customized, adaptable sequence of practice questions to individual learners, based on the exercise history of other users in a similar learning scenario. We propose a new way to …

Robust Factorization Machine: A Doubly Capped Norms Minimization, Chenghao Liu, Teng Zhang, Jundong Li, Jianwen Yin, Peilin Zhao, Jianling Sun, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Factorization Machine (FM) is a general supervised learning framework for many AI applications due to its powerful capability of feature engineering. Despite being extensively studied, existing FM methods have several limitations in common. First of all, most existing FM methods often adopt the squared loss in the modeling process, which can be very sensitive when the data for learning contains noises and outliers. Second, some recent FM variants often explore the low-rank structure of the feature interactions matrix by relaxing the low-rank minimization problem as a trace norm minimization, which cannot always achieve a tight approximation to the original one. …

Concluding Remarks, Lei Meng, Ah-Hwee Tan, Donald C. Wunsch

Research Collection School Of Computing and Information Systems

This chapter summarizes the major contributions in this book and discusses their possible positions and requirements in some future scenarios. Section 8.1 follows the book structure to revisit the key contributions of this book in both theories and applications. The developed algorithms, such as the VA-ARTs for hyperparameter adaptation and the GHF-ART for multimedia representation and fusion, and the four applications, such as clustering and retrieving socially enriched multimedia data, are concentrated using one paragraph and three paragraphs, respectively. In Sect. 8.2, the roles of the proposed ART-embodied algorithms in social media clustering tasks are highlighted, and their possible evolutions …

Clustering And Its Extensions In The Social Media Domain, Lei Meng, Ah-Hwee Tan, Donald C. Wunsch

Research Collection School Of Computing and Information Systems

This chapter summarizes existing clustering and related approaches for the identified challenges as described in Sect. 1.2 and presents the key branches of social media mining applications where clustering holds a potential. Specifically, several important types of clustering algorithms are first illustrated, including clustering, semi-supervised clustering, heterogeneous data co-clustering, and online clustering. Subsequently, Sect. 2.5 presents a review on existing techniques that help decide the value of the predefined number of clusters (required by most clustering algorithms) automatically and highlights the clustering algorithms that do not require such a parameter. It better illustrates the challenge of input parameter sensitivity of …

Yelp Improved : Aggregating Restaurant Reviews, Kunal Sonar

Creative Activity and Research Day - CARD

In the near future, online food delivery service companies would occupy a big market share in the food industry. This project aims to provide factual information from customer reviews as part of the numerous innovations in place to drive business and demands. Natural Language Processing is used to provide a comprehensive view of individual restaurants using technologies like NLTK, SpaCy, Gensim and Sklearn. Data of one million Las Vegas restaurant customer reviews is curated from the Yelp Dataset Challenge. Reviews are pre-processed, split into chunks of phrases and mapped to attributes like food, budget, service etc. These attributes are derived …

Building Consumer Trust In The Cloud: An Experimental Analysis Of The Cloud Trust Label Approach, Lisa Van Der Werff, Grace Fox, Ieva Masevic, Vincent C. Emeakaroha, John P. Morrison, Theo Lynn

Department of Computer Science Publications

The lack of transparency surrounding cloud service provision makes it difficult for consumers to make knowledge based purchasing decisions. As a result, consumer trust has become a major impediment to cloud computing adoption. Cloud Trust Labels represent a means of communicating relevant service and security information to potential customers on the cloud service provided, thereby facilitating informed decision making. This research investigates the potential of a Cloud Trust Label system to overcome the trust barrier. Specifically, it examines the impact of a Cloud Trust Label on consumer perceptions of a service and cloud service provider trustworthiness and trust in the …

Flashlight In A Dark Room: A Grounded Theory Study On Information Security Management At Small Healthcare Provider Organizations, Gerald Auger

Masters Theses & Doctoral Dissertations

Healthcare providers have a responsibility to protect patient’s privacy and a business motivation to properly secure their assets. These providers encounter barriers to achieving these objectives and limited academic research has been conducted to examine the causes and strategies to overcome them. A subset of this demographic, businesses with less than 10 providers, compose a majority 57% of provider organizations in the United States. This grounded theory study provides exploratory findings, discovering these small healthcare provider organizations (SHPO) have limited knowledge on information technology (IT) and information security that results in assumptions and misappropriations of information security implementation, who is …

Welcome Message From The General Chairs, Nabil I. Alshurafa, Archan Misra, Abhishek Mukherji

Research Collection School Of Computing and Information Systems

No abstract provided.

Dish: Democracy In State Houses, Nicholas A. Russo

Master's Theses

In our current political climate, state level legislators have become increasingly impor- tant. Due to cuts in funding and growing focus at the national level, public oversight for these legislators has drastically decreased. This makes it difficult for citizens and activists to understand the relationships and commonalities between legislators. This thesis provides three contributions to address this issue. First, we created a data set containing over 1200 features focused on a legislator’s activity on bills. Second, we created embeddings that represented a legislator’s level of activity and engagement for a given bill using a custom model called Democracy2Vec. Third, we …

Learning To Map The Visual And Auditory World, Tawfiq Salem

Theses and Dissertations--Computer Science

The appearance of the world varies dramatically not only from place to place but also from hour to hour and month to month. Billions of images that capture this complex relationship are uploaded to social-media websites every day and often are associated with precise time and location metadata. This rich source of data can be beneficial to improve our understanding of the globe. In this work, we propose a general framework that uses these publicly available images for constructing dense maps of different ground-level attributes from overhead imagery. In particular, we use well-defined probabilistic models and a weakly-supervised, multi-task training …

Building Recommendation Systems, Orion Davis

Williams Honors College, Honors Research Projects

Recommendation systems are pieces of software that suggest new items to a user. There are many moving parts to these systems including data, the actual recommendation model, processing data and finally displaying data. This project explores the role each part plays in the overall system and how to develop a recommendation system for beer from scratch. This project highlights the algorithm behind the recommendations and a user facing Android application.