Software Engineering Commons^™

Api Recommendation For Event-Driven Android Application Development, Weizhao Yuan, Huu Hoang Nguyen, Lingxiao Jiang, Yuting Chen, Jianjun Zhao, Haibo Yu

Research Collection School Of Computing and Information Systems

Context: Software development is increasingly dependent on existing libraries. Developers need help to find suitable library APIs. Although many studies have been proposed to recommend relevant functional APIs that can be invoked for implementing a functionality, few studies have paid attention to an orthogonal need associated with event-driven programming frameworks, such as the Android framework. In addition to invoking functional APIs, Android developers need to know where to place functional code according to various events that may be triggered within the framework.Objective: This paper aims to develop an API recommendation engine for Android application development that can recommend both (1) …

Careful-Packing: A Practical And Scalable Anti-Tampering Software Protection Enforced By Trusted Computing, Flavio Toffalini, Martín Ochoa, Jun Sun, Jianying Zhou

Research Collection School Of Computing and Information Systems

Ensuring the correct behaviour of an application is a critical security issue. One of the most popular ways to modify the intended behaviour of a program is to tamper its binary. Several solutions have been proposed to solve this problem, including trusted computing and anti-tampering techniques. Both can substantially increase security, and yet both have limitations. In this work, we propose an approach which combines trusted computing technologies and anti-tampering techniques, and that synergistically overcomes some of their inherent limitations. In our approach critical software regions are protected by leveraging on trusted computing technologies and cryptographic packing, without introducing additional …

Automatic, Highly Accurate App Permission Recommendation, Zhongxin Liu, Xin Xia, David Lo, John Grundy

Research Collection School Of Computing and Information Systems

To ensure security and privacy, Android employs a permission mechanism which requires developers to explicitly declare the permissions needed by their applications (apps). Users must grant those permissions before they install apps or during runtime. This mechanism protects users’ private data, but also imposes additional requirements on developers. For permission declaration, developers need knowledge about what permissions are necessary to implement various features of their apps, which is difficult to acquire due to the incompleteness of Android documentation. To address this problem, we present a novel permission recommendation system named PerRec for Android apps. PerRec leverages mining-based techniques and data …

Microbtc: Efficient, Flexible And Fair Micropayment For Bitcoin Using Hash Chains, Zhiguo Wan, Robert H. Deng, David Kuo Chuen Lee, Ying Li

Research Collection School Of Computing and Information Systems

While Bitcoin gains increasing popularity in different payment scenarios, the transaction fees make it difficult to be applied to micropayment. Given the wide applicability of micropayment, it is crucial for all cryptocurrencies including Bitcoin to provide effective support therein. In light of this, a number of low-cost micropayment schemes for Bitcoin have been proposed recently to reduce micropayment costs. Existing schemes, however, suffer from drawbacks such as high computation cost, inflexible payment value, and possibly unfair exchanges. The paper proposes two new micropayment schemes, namely the basic MicroBTC and the advanced MicroBTC, for Bitcoin by integrating the hash chain technique …

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

Research Collection School Of Computing and Information Systems

No abstract provided.

Neural Network Based Detection Of Self-Admitted Technical Debt: From Performance To Explainability, Xiaoxue Ren, Zhenchang Xing, Xin Xia, David Lo, Xinyu Wang, John Grundy

Research Collection School Of Computing and Information Systems

Technical debt is a metaphor to reflect the tradeoff software engineers make between short term benefitsand long term stability. Self-admitted technical debt (SATD), a variant of technical debt, has been proposed to identify debt that is intentionally introduced during software development, e.g., temporary fixes and workarounds. Previous studies have leveraged human-summarized patterns (which represent n-gram phrases that can be used to identify SATD) or text mining techniques to detect SATD in source code comments. However, several characteristics of SATD features in code comments, such as vocabulary diversity, project uniqueness, length and semantic variations, pose a big challenge to the accuracy …

Fc2: Cloud-Based Cluster Provisioning For Distributed Machine Learning, Nguyen Binh Duong Ta

Research Collection School Of Computing and Information Systems

Training large, complex machine learning models such as deep neural networks with big data requires powerful computing clusters, which are costly to acquire, use and maintain. As a result, many machine learning researchers turn to cloud computing services for on-demand and elastic resource provisioning capabilities. Two issues have arisen from this trend: (1) if not configured properly, training models on cloud-based clusters could incur significant cost and time, and (2) many researchers in machine learning tend to focus more on model and algorithm development, so they may not have the time or skills to deal with system setup, resource selection …

Unveiling Exception Handling Guidelines Adopted By Java Developers, Hugo Melo, Roberta Coelho, Christoph Treude

Research Collection School Of Computing and Information Systems

Despite being an old language feature, Java exception handling code is one of the least understood parts of many systems. Several studies have analyzed the characteristics of exception handling code, trying to identify common practices or even link such practices to software bugs. Few works, however, have investigated exception handling issues from the point of view of developers. None of the works have focused on discovering exception handling guidelines adopted by current systems - which are likely to be a driver of common practices. In this work, we conducted a qualitative study based on semi-structured interviews and a survey whose …

Grand Challenges In Accessible Maps, Jon E. Froehlich, Anke M. Brock, Anat Caspi, Joao Guerreiro, Kotaro Hara, Reuben Kirkham, Johannes Schoning, Benjamin Tannert

Research Collection School Of Computing and Information Systems

In this forum we celebrate research that helps to successfully bring the benefits of computing technologies to children, older adults, people with disabilities, and other populations that are often ignored in the design of mass-marketed products.

Preference-Aware Task Assignment In On-Demand Taxi Dispatching: An Online Stable Matching Approach, Boming Zhao, Pan Xu, Yexuan Shi, Yongxin Tong, Zimu Zhou, Yuxiang Zeng

Research Collection School Of Computing and Information Systems

No abstract provided.

Bilateral Dependency Neural Networks For Cross-Language Algorithm Classification, Duy Quoc Nghi Bui, Yijun Yu, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Algorithm classification is to automatically identify the classes of a program based on the algorithm(s) and/or data structure(s) implemented in the program. It can be useful for various tasks, such as code reuse, code theft detection, and malware detection. Code similarity metrics, on the basis of features extracted from syntax and semantics, have been used to classify programs. Such features, however, often need manual selection effort and are specific to individual programming languages, limiting the classifiers to programs in the same language.To recognise the similarities and differences among algorithms implemented in different languages, this paper describes a framework of Bilateral …

Recommending New Features From Mobile App Descriptions, He Jiang, Jingxuan Zhang, Xiaochen Li, Zhilei Ren, David Lo, Xindong Wu, Zhongxuan Luo

Research Collection School Of Computing and Information Systems

The rapidly evolving mobile applications (apps) have brought great demand for developers to identify new features by inspecting the descriptions of similar apps and acquire missing features for their apps. Unfortunately, due to the huge number of apps, this manual process is time-consuming and unscalable. To help developers identify new features, we propose a new approach named SAFER. In this study, we first develop a tool to automatically extract features from app descriptions. Then, given an app, we leverage the topic model to identify its similar apps based on the extracted features and API names of apps. Finally, we design …

Deception In Finitely Repeated Security Games, Thanh H. Nguyen, Yongzhao Wang, Arunesh Sinha, Michael P. Wellman

Research Collection School Of Computing and Information Systems

Allocating resources to defend targets from attack is often complicated by uncertainty about the attacker’s capabilities, objectives, or other underlying characteristics. In a repeated interaction setting, the defender can collect attack data over time to reduce this uncertainty and learn an effective defense. However, a clever attacker can manipulate the attack data to mislead the defender, influencing the learning process toward its own benefit. We investigate strategic deception on the part of an attacker with private type information, who interacts repeatedly with a defender. We present a detailed computation and analysis of both players’ optimal strategies given the attacker may …

Evolutionary Trends In The Collaborative Review Process Of A Large Software System, Subhajit Datta, Poulami Sarkar

Research Collection School Of Computing and Information Systems

In this paper, we study the evolutionary trends in the collaborative review process of a large open source software system. As expected, the number of reviews, the number of reviews commented on, as well as the number of reviewers, and the interactions between them show increasing trends over time. But unexpectedly, levels of clustering between developers in their interaction networks show a decreasing trend, even as connections between them increase. In the context of our study, clustering is an indicator of developer collaboration, whereas connection points to how intensely developers work together. Thus the trends we observe can inform how …

Automatic Code Review By Learning The Revision Of Source Code, Shu-Ting Shi, Ming Li, David Lo, Ferdian Thung, Xuan Huo

Research Collection School Of Computing and Information Systems

Code review is the process of manual inspection on the revision of the source code in order to find out whether the revised source code eventually meets the revision requirements. However, manual code review is time-consuming, and automating such the code review process will alleviate the burden of code reviewers and speed up the software maintenance process. To construct the model for automatic code review, the characteristics of the revisions of source code (i.e., the difference between the two pieces of source code) should be properly captured and modeled. Unfortunately, most of the existing techniques can easily model the overall …

Successor Features Based Multi-Agent Rl For Event-Based Decentralized Mdps, Tarun Gupta, Akshat Kumar, Praveen Paruchuri

Research Collection School Of Computing and Information Systems

Decentralized MDPs (Dec-MDPs) provide a rigorous framework for collaborative multi-agent sequential decisionmaking under uncertainty. However, their computational complexity limits the practical impact. To address this, we focus on a class of Dec-MDPs consisting of independent collaborating agents that are tied together through a global reward function that depends upon their entire histories of states and actions to accomplish joint tasks. To overcome scalability barrier, our main contributions are: (a) We propose a new actor-critic based Reinforcement Learning (RL) approach for event-based Dec-MDPs using successor features (SF) which is a value function representation that decouples the dynamics of the environment from …

Preface To The Special Issue On Program Comprehension, David Lo, Alexander Serebrenik

Research Collection School Of Computing and Information Systems

We are delighted to present a selection of the best papers presented at the 25th IEEE International Conference on Program Comprehension (ICPC 2017) that took place in Buenos Aires, Argentina. The program committee has received 83 submissions originating from 97 abstracts and co-authored by researchers from 26 countries from Africa, Asia, Europe, North and South America and Oceania. This is more than double of the 39 submissions received back in 2000. To select the papers for the special issue the PC chairs have selected the top five papers with the highest ratings from the reviewers. Each of these papers receives …

Automatic Query Reformulation For Code Search Using Crowdsourced Knowledge, Mohammad M. Rahman, Chanchal K. Roy, David Lo

Research Collection School Of Computing and Information Systems

Traditional code search engines (e.g., Krugle) often do not perform well with natural language queries. They mostly apply keyword matching between query and source code. Hence, they need carefully designed queries containing references to relevant APIs for the code search. Unfortunately, preparing an effective search query is not only challenging but also time-consuming for the developers according to existing studies. In this article, we propose a novel query reformulation technique–RACK–that suggests a list of relevant API classes for a natural language query intended for code search. Our technique offers such suggestions by exploiting keyword-API associations from the questions and answers …

A First Look At Unfollowing Behavior On Github, Jing Jiang, David Lo, Yun Yang, Jianfeng Li, Li Zhang

Research Collection School Of Computing and Information Systems

Many open source software projects rely on contributors to fix bugs and contribute new features. On GitHub, developers often broadcast their activities to followers, which may entice followers to be project contributors. It is important to understand unfollowing behavior, maintain current followers, and attract some followers to become contributors in OSS projects.Our objective in this paper is to provide a comprehensive analysis of unfollowing behavior on GitHub. To the best of our knowledge, we present a first look at unfollowing behavior on GitHub. We collect a dataset containing 701,364 developers and their 4,602,440 following relationships in March 2016. We also …

Person Re-Identification Over Encrypted Outsourced Surveillance Videos, Hang Cheng, Huaxiong Wang, Ximeng Liu, Yan Fang, Meiqing Wang, Xiaojun Zhang

Research Collection School Of Computing and Information Systems

Person re-identification (Re-ID) has attracted extensive attention due to its potential to identify a person of interest from different surveillance videos. With the increasing amount of the surveillance videos, high computation and storage costs have posed a great challenge for the resource-constrained users. In recent years, the cloud storage services have made a large volume of video data outsourcing become possible. However, person Re-ID over outsourced surveillance videos could lead to a security threat, i.e., the privacy leakage of the innocent person in these videos. Therefore, we propose an efFicient privAcy-preseRving peRson Re-ID Scheme (FARRIS) over outsourced surveillance videos, which …

Deep Code Comment Generation With Hybrid Lexical And Syntactical Information, Xing Hu, Ge Li, Xin Xia, David Lo, Zhi Jin

Research Collection School Of Computing and Information Systems

During software maintenance, developers spend a lot of time understanding the source code. Existing studies show that code comments help developers comprehend programs and reduce additional time spent on reading and navigating source code. Unfortunately, these comments are often mismatched, missing or outdated in software projects. Developers have to infer the functionality from the source code. This paper proposes a new approach named Hybrid-DeepCom to automatically generate code comments for the functional units of Java language, namely, Java methods. The generated comments aim to help developers understand the functionality of Java methods. Hybrid-DeepCom applies Natural Language Processing (NLP) techniques to …

Software Engineering Dashboards: Types, Risks, And Future, Margaret-Anne Storey, Christoph Treude

Research Collection School Of Computing and Information Systems

The large number of artifacts created or modified in a software project and the flood of information exchanged in the process of creating a software product call for tools that aggregate this data to communicate higher-level insights to all stakeholders involved. In many projects—in software engineering as well as in other domains—dashboards are used to communicate information that may bring insights on the productivity of project activities and other aspects. Stephen Few defines a dashboard as “a visual display of the most important information needed to achieve one or more objectives which fits entirely on a single computer screen so …

Automatic Query Reformulation For Code Search Using Crowdsourced Knowledge, Mohammad M. Rahman, Chanchal K. Roy, David Lo

Research Collection School Of Computing and Information Systems

Traditional code search engines (e.g., Krugle) often do not perform well with natural language queries. They mostly apply keyword matching between query and source code. Hence, they need carefully designed queries containing references to relevant APIs for the code search. Unfortunately, preparing an effective search query is not only challenging but also time-consuming for the developers according to existing studies. In this article, we propose a novel query reformulation technique–RACK–that suggests a list of relevant API classes for a natural language query intended for code search. Our technique offers such suggestions by exploiting keyword-API associations from the questions and answers …

How Team Awareness Influences Perceptions Of Developer Productivity, Christoph Treude, Fernando Figueira Filho

Research Collection School Of Computing and Information Systems

In their day-to-day work, software developers perform many different activities: they use numerous tools to develop software artifacts ranging from source code and models to documentation and test cases, they use other tools to manage and coordinate their development work, and they spend a substantial amount of time communicating and exchanging knowledge with other members on their teams and the larger software development community. Making sense of this flood of activity and information is becoming harder with every new artifact created. Yet, being aware of all relevant information in a software project is crucial to enable productivity in software development.

Quantifying Activity Levels Of Community-Dwelling Seniors Through Beacon Monitoring, Jin Qiang Goh, Hwee-Pink Tan, Hwee Xian Tan

Research Collection School Of Computing and Information Systems

The ageing population is rapidly increasing, both in Singapore and worldwide. Due to the shortage of healthcare professionals and institutionalized care, there is a pertinent need for seniors to age-in-place-safely and in the familiarity of their neighborhoods. In addition, changing family structures and rising divorce rates, coupled with the desire for more personal space and independence, have resulted in a significant proportion of seniors who live alone at home. In this paper, we describe a scalable and low-cost monitoring system that can help to identify community-dwelling seniors who are at risk of social isolation and/or frailty. This is achieved by …

Multi-Task Zipping Via Layer-Wise Neuron Sharing, Xiaoxi He, Zimu Zhou, Lothar Thiele

Research Collection School Of Computing and Information Systems

Future mobile devices are anticipated to perceive, understand and react to the world on their own by running multiple correlated deep neural networks on-device. Yet the complexity of these neural networks needs to be trimmed down both within-model and cross-model to fit in mobile storage and memory. Previous studies squeeze the redundancy within a single model. In this work, we aim to reduce the redundancy across multiple models. We propose Multi-Task Zipping (MTZ), a framework to automatically merge correlated, pre-trained deep neural networks for cross-model compression. Central in MTZ is a layer-wise neuron sharing and incoming weight updating scheme that …

Comparison Mining From Text, Maksim Tkachenko

Dissertations and Theses Collection (Open Access)

Online product reviews are important factors of consumers' purchase decisions. They invade more and more spheres of our life, we have reviews on books, electronics, groceries, entertainments, restaurants, travel experiences, etc. More than 90 percent of consumers read online reviews before they purchase products as reported by various consumers surveys. This observation suggests that product review information enhances consumer experience and helps them to make better-informed purchase decisions. There is an enormous amount of online reviews posted on e-commerce platforms, such as Amazon, Apple, Yelp, TripAdvisor. They vary in information and may be written with different experiences and preferences.

If …

Perflearner: Learning From Bug Reports To Understand And Generate Performance Test Frames, Xue Han, Tingting Yu, David Lo

Research Collection School Of Computing and Information Systems

Software performance is important for ensuring the quality of software products. Performance bugs, defined as programming errors that cause significant performance degradation, can lead to slow systems and poor user experience. While there has been some research on automated performance testing such as test case generation, the main idea is to select workload values to increase the program execution times. These techniques often assume the initial test cases have the right combination of input parameters and focus on evolving values of certain input parameters. However, such an assumption may not hold for highly configurable real-word applications, in which the combinations …

Applying Design Thinking To Student Outreach Projects: Experiences From An Information Systems School, Swapna Gottipati, Venky Shankararaman, Alan Megargel

Research Collection School Of Computing and Information Systems

As countries turn into Smart Nations, Infocom Technology plays a key role in enhancing their competitiveness through high skilled workforces. Reaching to younger generations and attracting them to computing programs such as Information Systems (IS) and Computer Science (CS) is a key challenge faced by universities. Many high quality students from junior colleges either don’t choose IS programs or choose IS programs as their last option during the application process. A School of Information Systems (SIS) from a large metropolitan university decided to implement an innovative outreach program to attract high quality high school aka Junior College (JC) students. JC …

Message From The Chairs, Toshiki Hirao, Yutaro Kashiwa, Christoph Treude, Raula Gaikovina Kula

Research Collection School Of Computing and Information Systems

It is our great pleasure to welcome everyone to the 2018 International Workshop on Empirical Software Engineering in Practice (IWESEP 2018). Our workshop aims to foster the development of the area by providing a forum where researchers and practitioners can report on and discuss new research results and applications in the area of empirical software engineering. The workshop encourages the exchange of ideas within the international community so as to be able to understand, from an empirical viewpoint, the strengths and weaknesses of technology in use and new technologies, with the expectation of advancing the field of software engineering in …