Software Engineering Commons^™

Lightsense: Exploiting Smart Bulbs For Practical Multimodal Localization, Huynh Nguyen, Archan Misra, Youngki Lee

Research Collection School Of Computing and Information Systems

Visible Light Positioning (VLP) is an exciting new approach but has to overcome considerable challenges before it becomes practical. In particular, the line-of-sight requirement which imports the constraint on the working condition of VLP and can not be solved by the VLP itself. This paper develops techniques to allow VLP to be augmented with traditional WI-FI approach by leveraging the WI-FI enabled smart bulbs which are now widely available. Those Smart bulbs offer several intriguing properties: a very dense deployment (roughly every 2 meters apart), ability to act as sensors that continually provide Wi-Fi signal strength measurements. We utilize these …

Where Am I? Characterizing And Improving The Localization Performance Of Off-The-Shelf Mobile Devices Through Cooperation, Huiguang Liang, Hyong S. Kim, Hwee-Pink Tan, Wai-Leong Yeow

Research Collection School Of Computing and Information Systems

We are increasingly reliant on cellular data services for many types of day-to-day activities, from hailing a cab, to searching for nearby restaurants. Geo-location has become a ubiquitous feature that underpins the functionality of such applications. Network operators can also benefit from accurate mobile terminal localization in order to quickly detect and identify location-related network performance issues, such as coverage holes and congestion, based on mobile measurements. Current implementations of mobile localization on the wildly-popular Android platform depend on either the Global Positioning System (GPS), Android's Network Location Provider (NLP), or a combination of both. In this paper, we extensively …

Rate Distortion Balanced Data Compression In Wireless Sensor Networks, Mohammad Abu Alsheikh, Shaowei Lin, Dusit Niyato, Hwee-Pink Tan

Research Collection School Of Computing and Information Systems

This paper presents a data compression algorithm with error bound guarantee for wireless sensor networks (WSNs) using compressing neural networks. The proposed algorithm minimizes data congestion and reduces energy consumption by exploring spatio-temporal correlations among data samples. The adaptive rate-distortion feature balances the compressed data size (data rate) with the required error bound guarantee (distortion level). This compression relieves the strain on energy and bandwidth resources while collecting WSN data within tolerable error margins, thereby increasing the scale of WSNs. The algorithm is evaluated using real-world data sets and compared with conventional methods for temporal and spatial data compression. The …

Crowdsourcing: A Building Block For Smart Cities, Archan Misra

Research Collection School Of Computing and Information Systems

This talk will present a vision, and real-world examples, of the use of mobile crowdsourcing for building a variety of smart-city applications and services. I will first describe the paradigm of centrally-coordinated crowdsourcing, where the crowdsourcing platform intelligently recommends different tasks to different candidate workers, and contrast it with today's prevalent paradigm, where workers select and perform tasks in an uncoordinated, opportunistic fashion. I will then describe real-world examples of such crowdsourcing (and participatory sensing) for two applications: (a) smart campus monitoring and (b) last-mile urban logistics (package pickup and delivery). The talk will also describe the opportunities and open …

Quality And Context-Aware Smart Health Care: Evaluating The Cost-Quality Dynamics, Nirmalya Roy, Christine Julien, Archan Misra, Sajal Das

Research Collection School Of Computing and Information Systems

Many emerging pervasive health-care applications require the determination of a variety of context attributes of an individual's activities and medical parameters and her surrounding environment. Context is a high-level representation of an entity's state, which captures activities, relationships, capabilities, etc. In practice, high-level context measures are often difficult to sense from a single data source and must instead be inferred using multiple sensors embedded in the environment. A key challenge in deploying context-driven health-care applications involves energy-efficient determination or inference of high-level context information from low-level sensor data streams. Because this abstraction has the potential to reduce the quality of …

Predicting Changes To Source Code, Justin James Roll

Master's Theses

Organizations typically use issue tracking systems (ITS) such as Jira to plan software releases and assign requirements to developers. Organizations typically also use source control management (SCM) repositories such as Git to track historical changes to a code-base. These ITS and SCM repositories contain valuable data that remains largely untapped. As developers churn through an organization, it becomes expensive for developers to spend time determining which software artifact must be modified to implement a requirement. In this work we created, developed, tested and evaluated a tool called Class Change Predictor, otherwise known as CCP, for predicting which class will implement …

Introduction To Atomic Requirements, William L. Honig

Computer Science: Faculty Publications and Other Works

An introduction to requirements and the importance of making single atomic requirements statements. Atomic requirements have advantages and improve the requirements process, support requirement verification and validation, enable traceability, support testability of systems, and provide management advantages.

Why has there been so little emphasis on atomic requirements?

Ontology-Aided Feature Correlation For Multi-Modal Urban Sensing, Archan Misra, Zaman Lantra, Kasthuri Jayarajah

Research Collection School Of Computing and Information Systems

The paper explores the use of correlation across features extracted from different sensing channels to help in urban situational understanding. We use real-world datasets to show how such correlation can improve the accuracy of detection of city-wide events by combining metadata analysis with image analysis of Instagram content. We demonstrate this through a case study on the Singapore Haze. We show that simple ontological relationships and reasoning can significantly help in automating such correlation-based understanding of transient urban events.

Tuning By Turning: Enabling Phased Array Signal Processing For Wifi With Inertial Sensors, Kun Qian, Chenshu Wu, Zheng Yang, Zimu Zhou, Xu Wang, Yunhao Liu

Research Collection School Of Computing and Information Systems

Modern mobile devices are equipped with multiple antennas, which brings various wireless sensing applications such as accurate localization, contactless human detection and wireless human-device interaction. A key enabler for these applications is phased array signal processing, especially Angle of Arrival (AoA) estimation. However, accurate AoA estimation on commodity devices is non-trivial due to limited number of antennas and uncertain phase offsets. Previous works either rely on elaborate calibration or involve contrived human interactions. In this paper, we aim to enable practical AoA measurements on commodity off-the-shelf (COTS) mobile devices. The key insight is to involve users’ natural rotation to formulate …

Not You Too? Distilling Local Contexts Of Poor Cellular Network Performance Through Participatory Sensing, Huiguang Liang, Ido Nevat, Hyong S. Kim, Hwee-Pink Tan, Wai-Leong Yeow

Research Collection School Of Computing and Information Systems

Cellular service subscribers are increasingly reliant on cellular data services for all kinds of mobile applications. Oftentimes, when subscribers experience frustratingly high network delays and timeouts, they like to know whether their experiences are shared by other users nearby. The question that is often asked is essentially this: “is it just me, or do others around me face the same problem?” In this paper, we describe how we use Tattle, a distributed real-time participatory sensing and monitoring framework, to glean network performance information from users nearby. Tattle relies on recent advances in peer-to-peer device networking, such as Wi-Fi Direct, Bluetooth …

Incentive Mechanism Design For Crowdsourcing: An All-Pay Auction Approach, Tie Luo, Sajal K. Das, Hwee-Pink Tan, Lirong Xia

Research Collection School Of Computing and Information Systems

Crowdsourcing can be modeled as a principal-agent problem in which the principal (crowdsourcer) desires to solicit maximal contribution from a group of agents (participants) while agents are only motivated to act to their own respective advantages. To reconcile this tension, we propose an all-pay auction approach to incentivize agents to act in the principal's interst, i.e., maximizing profit, while allowing agents to reap strictly positive utility. Our rationale for advocating all-pay auctions is based on two merits that we identify, namely all-pay auctions (i) compress the common, two-stage "bid-contribute" crowdsourcing process into a single "bid-cum-contribute" stage, and (ii) eliminate the …

Analysis Of Software Design Patterns In Human Cognitive Performance Experiments, Alexander C. Roosma

Theses and Dissertations

As Air Force operations continue to move toward the use of more autonomous systems and more human-machine teaming in general, there is a corresponding need to swiftly evaluate systems with these capabilities. We support this development through software design improvements of the execution of human cognitive performance experiments. This thesis sought to answer the following two research questions addressing the core functionality that these experiments rely on for execution and analysis: 1) What data infrastructure software requirements are necessary to execute the experimental design of human cognitive performance experiments? 2) How effectively does a central data mediator design pattern meet …

Using A Dynamic Domain-Specific Modeling Language For The Model-Driven Development Of Cross-Platform Mobile Applications, Christopher A. Jones

College of Computing and Digital Media Dissertations

There has been a gradual but steady convergence of dynamic programming languages with modeling languages. One area that can benefit from this convergence is modeldriven development (MDD) especially in the domain of mobile application development. By using a dynamic language to construct a domain-specific modeling language (DSML), it is possible to create models that are executable, exhibit flexible type checking, and provide a smaller cognitive gap between business users, modelers and developers than more traditional model-driven approaches.

Dynamic languages have found strong adoption by practitioners of Agile development processes. These processes often rely on developers to rapidly produce working code …

Sefo: A Package For Generating Probabilistic Forecasts From Nmme Predictive Ensembles, Nir Krakauer

Publications and Research

Long-range weather forecasts based on output from ensembles of computer simulations are attracting increasing interest. A variety of methods have been proposed to convert the ensemble outputs to calibrated probabilistic forecasts. The package presented here (SeFo, for Seasonal Forecasting) implements a number of methods for producing forecasts of monthly surface air temperature anomalies up to 9 months in advance using output from the North American Multi-Model Ensemble (NMME). The package contains modules for downloading and reading past observations and ensemble output; producing forecast probability distributions; and verifying and calibrating a user-determined subset of methods using arbitrary past periods. By changing …

A Reflection On Types, Simon. Peyton Jones, Stephanie Weirich, Richard A. Eisenberg, Dimitrios Vytiniotis

Computer Science Faculty Research and Scholarship

The ability to perform type tests at runtime blurs the line between statically-typed and dynamically-checked languages. Recent developments in Haskell’s type system allow even programs that use reflection to themselves be statically typed, using a type-indexed runtime representation of types called \𝗍𝖾𝗑𝗍𝗂𝗍{𝖳𝗒𝗉𝖾𝖱𝖾𝗉}\textit{TypeRep}. As a result we can build dynamic types as an ordinary, statically-typed library, on top of \𝗍𝖾𝗑𝗍𝗂𝗍{𝖳𝗒𝗉𝖾𝖱𝖾𝗉}\textit{TypeRep} in an open-world context.

Semantic Memory Modeling And Memory Interaction In Learning Agents, Wenwen Wang, Ah-Hwee Tan, Loo-Nin Teow

Research Collection School Of Computing and Information Systems

Semantic memory plays a critical role in reasoning and decision making. It enables an agent to abstract useful knowledge learned from its past experience. Based on an extension of fusion adaptive resonance theory network, this paper presents a novel self-organizing memory model to represent and learn various types of semantic knowledge in a unified manner. The proposed model, called fusion adaptive resonance theory for multimemory learning, incorporates a set of neural processes, through which it may transfer knowledge and cooperate with other long-term memory systems, including episodic memory and procedural memory. Specifically, we present a generic learning process, under which …

Venncafe, Daniel Johnson, Christopher Clark, Jonathan Amireh

Computer Science and Software Engineering

Our senior project involved creating a simple dating application and service. From other dating applications, we observed that the logistics of scheduling a first date are a tedious way to start a conversation with someone you've never met. The main concept of our application was that it would use user schedule availability and their favorite cafes to automatically plan optimal dates.

We started the project with the intent of...

• Working through the entire development cycle of a large project as a team

• Devising techniques for determining overlapping preferences, especially when handling large amounts of location and time data

• Exploring different …

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History Driven Program Repair, Xuan-Bach D. Le, David Lo, Claire Le Goues

Research Collection School Of Computing and Information Systems

Effective automated program repair techniques have great potential to reduce the costs of debugging and maintenance. Previously proposed automated program repair (APR) techniques often follow a generate-and-validate and test- case-driven procedure: They first randomly generate a large pool of fix candidates and then exhaustively validate the quality of the candidates by testing them against existing or provided test suites. Unfortunately, many real-world bugs cannot be repaired by existing techniques even after more than 12 hours of computation in a multi-core cloud environment. More work is needed to advance the capabilities of modern APR techniques. We propose a new technique that …

Value-Inspired Service Design In Elderly Home-Monitoring Systems, Na Liu, Sandeep Purao, Hwee-Pink Tan

Research Collection School Of Computing and Information Systems

The provision of elderly home-monitoring systems to enhance aging-in-place requires the service to meet the needs of both the elderly and their caregivers. The design of such IT services requires interdisciplinary efforts to look beyond the technical requirements. Taking a value-inspired design perspective, the study argues that service design for promoting aging-in-place needs to reconcile the values of both the elderly and caregivers. Drawn from the framework of basic human values and the unique experience of the SHINESeniors project, the study extracts the core values for elderly and caregivers using a multi-method case analysis. We suggest that both system and …

Rack: Automatic Api Recommendation Using Crowdsourced Knowledge, Mohammad M. Rahman, Chanchal K. Roy, David Lo

Research Collection School Of Computing and Information Systems

Traditional code search engines often do not perform well with natural language queries since they mostly apply keyword matching. These engines thus need carefully designed queries containing information about programming APIs for code search. Unfortunately, existing studies suggest that preparing an effective code search query is both challenging and time consuming for the developers. In this paper, we propose a novel API recommendation technique -- RACK that recommends a list of relevant APIs for a natural language query for code search by exploiting keyword-API associations from the crowdsourced knowledge of Stack Overflow. We first motivate our technique using an exploratory …