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Articles 1411 - 1440 of 2149
Full-Text Articles in Software Engineering
Poster: Air Quality Friendly Route Recommendation System, Savina Singla, Divya Bansal, Archan Misra
Poster: Air Quality Friendly Route Recommendation System, Savina Singla, Divya Bansal, Archan Misra
Research Collection School Of Computing and Information Systems
To model the overall personal inhalation of hazardous gases through the air (both indoor and outdoor) by an individual, provide air quality friendly route recommendations, thus raising the overall quality of urban movement and living healthy life.
Cdrep: Automatic Repair Of Cryptographic-Misuses In Android Applications, Siqi Ma, David Lo, Teng Li, Robert H. Deng
Cdrep: Automatic Repair Of Cryptographic-Misuses In Android Applications, Siqi Ma, David Lo, Teng Li, Robert H. Deng
Research Collection School Of Computing and Information Systems
Cryptography is increasingly being used in mobile applications to provide various security services; from user authentication, data privacy, to secure communications. However, there are plenty of mistakes that developers could accidentally make when using cryptography in their mobile apps and such mistakes can lead to a false sense of security. Recent research efforts indeed show that a significant portion of mobile apps in both Android and iOS platforms misused cryptographic APIs. In this paper, we present CDRep, a tool for automatically repairing cryptographic misuse defects in Android apps. We classify such defects into seven types and manually assemble the corresponding …
Deepsense: A Gpu-Based Deep Convolutional Neural Network Framework On Commodity Mobile Devices, Huynh Nguyen Loc, Rajesh Krishna Balan, Youngki Lee
Deepsense: A Gpu-Based Deep Convolutional Neural Network Framework On Commodity Mobile Devices, Huynh Nguyen Loc, Rajesh Krishna Balan, Youngki Lee
Research Collection School Of Computing and Information Systems
Recently, a branch of machine learning algorithms called deep learning gained huge attention to boost up accuracy of a variety of sensing applications. However, execution of deep learning algorithm such as convolutional neural network on mobile processor is non-trivial due to intensive computational requirements. In this paper, we present our early design of DeepSense - a mobile GPU-based deep convolutional neural network (CNN) framework. For its design, we first explored the differences between server-class and mobile-class GPUs, and studied effectiveness of various optimization strategies such as branch divergence elimination and memory vectorization. Our results show that DeepSense is able to …
Livelabs: Building In-Situ Mobile Sensing And Behavioural Experimentation Testbeds, Kasthuri Jayarajah, Rajesh Krishna Balan, Meera Radhakrishnan, Archan Misra, Youngki Lee
Livelabs: Building In-Situ Mobile Sensing And Behavioural Experimentation Testbeds, Kasthuri Jayarajah, Rajesh Krishna Balan, Meera Radhakrishnan, Archan Misra, Youngki Lee
Research Collection School Of Computing and Information Systems
In this paper, we present LiveLabs, a first-of-its-kind testbed that isdeployed across a university campus, convention centre, and resortisland and collects real-time attributes such as location, group contextetc., from hundreds of opt-in participants. These venues, data,and participants are then made available for running rich humancentricbehavioural experiments that could test new mobile sensinginfrastructure, applications, analytics, or more social-sciencetype hypotheses that influence and then observe actual user behaviour.We share case studies of how researchers from aroundthe world have and are using LiveLabs, and our experiences andlessons learned from building, maintaining, and expanding LiveLabsover the last three years.
Poster: A Device-Free Evaluation System For Gymnastics Using Passive Rfid Tags, Binbin Xie, Jie Xiong, Dingyi Fang, Xiaojiang Chen, Anwen Wang, Zhanyong Tang
Poster: A Device-Free Evaluation System For Gymnastics Using Passive Rfid Tags, Binbin Xie, Jie Xiong, Dingyi Fang, Xiaojiang Chen, Anwen Wang, Zhanyong Tang
Research Collection School Of Computing and Information Systems
No abstract provided.
Condensing Class Diagrams With Minimal Manual Labeling Cost, Xinli Yang, David Lo, Xin Xia, Jianling Sun
Condensing Class Diagrams With Minimal Manual Labeling Cost, Xinli Yang, David Lo, Xin Xia, Jianling Sun
Research Collection School Of Computing and Information Systems
Traditionally, to better understand the design of a project, developers can reconstruct a class diagram from source code using a reverse engineering technique. However, the raw diagram is often perplexing because there are too many classes in it. Condensing the reverse engineered class diagram into a compact class diagram which contains only the important classes would enhance the understandability of the corresponding project. A number of recent works have proposed several supervised machine learning solutions that can be used for condensing reverse engineered class diagrams given a set of classes that are manually labeled as important or not. However, a …
Automated Identification Of High Impact Bug Reports Leveraging Imbalanced Learning Strategies, Xinli Yang, David Lo, Qiao Huang, Xin Xia, Jianling Sun
Automated Identification Of High Impact Bug Reports Leveraging Imbalanced Learning Strategies, Xinli Yang, David Lo, Qiao Huang, Xin Xia, Jianling Sun
Research Collection School Of Computing and Information Systems
In practice, some bugs have more impact than others and thus deserve more immediate attention. Due to tight schedule and limited human resource, developers may not have enough time to inspect all bugs. Thus, they often concentrate on bugs that are highly impactful. In the literature, high impact bugs are used to refer to the bugs which appear in unexpected time or locations and bring more unexpected effects, or break pre-existing functionalities and destroy the user experience. Unfortunately, identifying high impact bugs from the thousands of bug reports in a bug tracking system is not an easy feat. Thus, an …
The Social Side Of Software Platform Ecosystems, Cleidson R. B. Da Souza, Fernando Figueira Filho, Müller Miranda, Renato Pina Ferreira, Christoph Treude, Leif Singer
The Social Side Of Software Platform Ecosystems, Cleidson R. B. Da Souza, Fernando Figueira Filho, Müller Miranda, Renato Pina Ferreira, Christoph Treude, Leif Singer
Research Collection School Of Computing and Information Systems
Software ecosystems as a paradigm for large-scale software development encompass a complex mix of technical, business, and social aspects. While significant research has been conducted to understand both the technical and business aspects, the social aspects of software ecosystems are less well understood. To close this gap, this paper presents the results of an empirical study aimed at understanding the influence of social aspects on developers’ participation in software ecosystems. We conducted 25 interviews with mobile software developers and an online survey with 83 respondents from the mobile software development community. Our results point out a complex social system based …
Optimizing Selection Of Competing Services With Probabilistic Hierarchical Refinement, Tian Huat Tan, Manman Chen, Jun Sun, Yang Liu, Étienne André, Yinxing Xue, Jin Song Dong
Optimizing Selection Of Competing Services With Probabilistic Hierarchical Refinement, Tian Huat Tan, Manman Chen, Jun Sun, Yang Liu, Étienne André, Yinxing Xue, Jin Song Dong
Research Collection School Of Computing and Information Systems
Recently, many large enterprises (e.g., Netflix, Amazon) have decomposed their monolithic application into services, and composed them to fulfill their business functionalities. Many hosting services on the cloud, with different Quality of Service (QoS) (e.g., availability, cost), can be used to host the services. This is an example of competing services. QoS is crucial for the satisfaction of users. It is important to choose a set of services that maximize the overall QoS, and satisfy all QoS requirements for the service composition. This problem, known as optimal service selection, is NPhard. Therefore, an effective method for reducing the search space …
Leveraging Automated Privacy Checking For Design Of Mobile Privacy Protection Mechanisms, Joseph Joo Keng Chan, Lingxiao Jiang, Kiat Wee Tan, Rajesh Balan
Leveraging Automated Privacy Checking For Design Of Mobile Privacy Protection Mechanisms, Joseph Joo Keng Chan, Lingxiao Jiang, Kiat Wee Tan, Rajesh Balan
Research Collection School Of Computing and Information Systems
While mobile platforms rely on developers to follow good practices in privacy design, developers might not always adhere. In addition, it is often difficult for users to understand the privacy behaviour of their applications without some prolonged usage. To aid in these issues, we describe on-going research to improve privacy protection by utilizing techniques that mine privacy information from application binaries as a grey-box (Automated Privacy Checking). The outputs can then be utilized to improve the users' ability to exercise privacy-motivated discretion. We conducted a user study to observe the effects of presenting information on leak-causing triggers within applications in …
Deeper Look Into Bug Fixes: Patterns, Replacements, Deletions, And Additions, Mauricio Soto, Ferdian Thung, Chu-Pan Wong, Claire Le Goues, David Lo
Deeper Look Into Bug Fixes: Patterns, Replacements, Deletions, And Additions, Mauricio Soto, Ferdian Thung, Chu-Pan Wong, Claire Le Goues, David Lo
Research Collection School Of Computing and Information Systems
Many implementations of research techniques that automatically repair software bugs target programs written in C. Work that targets Java often begins from or compares to direct translations of such techniques to a Java context. However, Java and C are very different languages, and Java should be studied to inform the construction of repair approaches to target it. We conduct a large-scale study of bugfixing commits in Java projects, focusing on assumptions underlying common search-based repair approaches. We make observations that can be leveraged to guide high quality automatic software repair to target Java specifically, including common and uncommon statement modifications …
You Are Being Watched: Bystanders' Perspective On The Use Of Camera Devices In Public Spaces, Samarth Singhal, Carman Neustaedter, Thecla Schiphorst, Anthony Tang, Abhisekh Patra, Rui Pan
You Are Being Watched: Bystanders' Perspective On The Use Of Camera Devices In Public Spaces, Samarth Singhal, Carman Neustaedter, Thecla Schiphorst, Anthony Tang, Abhisekh Patra, Rui Pan
Research Collection School Of Computing and Information Systems
We are observing an increase in the use of smartphones and wearable devices in public places for streaming and recording video. Yet the use of cameras in these devices can infringe upon the privacy of the people in the surrounding environment by inadvertently capturing them. This paper presents findings from an in-situ exploratory study that investigates bystanders' reactions and feelings towards streaming and recording videos with smartphones and wearable glasses in public spaces. We use the interview results to guide an exploration of design directions for mobile video.
Augmenting Api Documentation With Insights From Stack Overflow, Christoph Treude, Martin P. Robillard
Augmenting Api Documentation With Insights From Stack Overflow, Christoph Treude, Martin P. Robillard
Research Collection School Of Computing and Information Systems
Software developers need access to different kinds of information which is often dispersed among different documentation sources, such as API documentation or Stack Overflow. We present an approach to automatically augment API documentation with “insight sentences” from Stack Overflow— sentences that are related to a particular API type and that provide insight not contained in the API documentation of that type. Based on a development set of 1,574 sentences, we compare the performance of two state-of-the-art summarization techniques as well as a pattern-based approach for insight sentence extraction. We then present SISE, a novel machine learning based approach that uses …
The Design Of Assistive Location-Based Technologies For People With Ambulatory Disabilities: A Formative Study, Kotaro Hara, Christine Chen, Jon E. Froehlich
The Design Of Assistive Location-Based Technologies For People With Ambulatory Disabilities: A Formative Study, Kotaro Hara, Christine Chen, Jon E. Froehlich
Research Collection School Of Computing and Information Systems
In this paper, we investigate how people with mobility impairments assess and evaluate accessibility in the built environment and the role of current and emerging location-based technologies therein. We conducted a three-part formative study with 20 mobility impaired participants: a semi-structured interview (Part 1), a participatory design activity (Part 2), and a design probe activity (Part 3). Part 2 and 3 actively engaged our participants in exploring and designing the future of what we call assistive location-based technologies (ALTs) location-based technologies that specifically incorporate accessibility features to support navigating, searching, and exploring the physical world. Our Part 1 findings highlight …
Overcoming Open Source Project Entry Barriers With A Portal For Newcomers, Igor Steinmacher, Tayana U. Conte, Christoph Treude, Marco Aurélio Gerosa
Overcoming Open Source Project Entry Barriers With A Portal For Newcomers, Igor Steinmacher, Tayana U. Conte, Christoph Treude, Marco Aurélio Gerosa
Research Collection School Of Computing and Information Systems
Community-based Open Source Software (OSS) projects are usually self-organized and dynamic, receiving contributions from distributed volunteers. Newcomer are important to the survival, long-term success, and continuity of these communities. However, newcomers face many barriers when making their first contribution to an OSS project, leading in many cases to dropouts. Therefore, a major challenge for OSS projects is to provide ways to support newcomers during their first contribution. In this paper, we propose and evaluate FLOSScoach, a portal created to support newcomers to OSS projects. FLOSScoach was designed based on a conceptual model of barriers created in our previous work. To …
Graph-Aided Directed Testing Of Android Applications For Checking Runtime Privacy Behaviours, Joseph Joo Keng Chan, Lingxiao Jiang, Kiat Wee Tan, Rajesh Krishna Balan
Graph-Aided Directed Testing Of Android Applications For Checking Runtime Privacy Behaviours, Joseph Joo Keng Chan, Lingxiao Jiang, Kiat Wee Tan, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
While automated testing of mobile applications is very useful for checking run-time behaviours and specifications, its capability in discovering issues in apps is often limited in practice due to long testing time. A common practice is to randomly and exhaustively explore the whole app test space, which takes a lot of time and resource to achieve good coverage and reach targeted parts of the apps. In this paper, we present MAMBA, a directed testing system for checking privacy in Android apps. MAMBA performs path searches of user events in control-flow graphs of callbacks generated from static analysis of app bytecode. …
Learning To Rank For Bug Report Assignee Recommendation, Yuan Tian, Withthige Dinusha Ruchira Wijedasa, David Lo, Claire Le Goues
Learning To Rank For Bug Report Assignee Recommendation, Yuan Tian, Withthige Dinusha Ruchira Wijedasa, David Lo, Claire Le Goues
Research Collection School Of Computing and Information Systems
Projects receive a large number of bug reports, and resolving these reports take considerable time and human resources. To aid developers in the resolution of bug reports, various automated techniques have been proposed to identify and recommend developers to address newly reported bugs. Two families of bug assignee recommendation techniques include those that recommend developers who have fixed similar bugs before (a.k.a. activity-based techniques) and those recommend suitable developers based on the location of the bug (a.k.a. location-based techniques). Previously, each of these techniques has been investigated separately. In this work, we propose a unified model that combines information from …
A Graph-Based Semantics Workbench For Concurrent Asynchronous Programs, Claudio Corrodi, Alexander Heußner, Christopher M. Poskitt
A Graph-Based Semantics Workbench For Concurrent Asynchronous Programs, Claudio Corrodi, Alexander Heußner, Christopher M. Poskitt
Research Collection School Of Computing and Information Systems
A number of novel programming languages and libraries have been proposed that offer simpler-to-use models of concurrency than threads. It is challenging, however, to devise execution models that successfully realise their abstractions without forfeiting performance or introducing unintended behaviours. This is exemplified by Scoop—a concurrent object-oriented message-passing language—which has seen multiple semantics proposed and implemented over its evolution. We propose a “semantics workbench” with fully and semi-automatic tools for Scoop, that can be used to analyse and compare programs with respect to different execution models. We demonstrate its use in checking the consistency of semantics by applying it to a …
Smokey: Ubiquitous Smoking Detection With Commercial Wifi Infrastructures, Xiaolong Zheng, Jiliang Wang, Longfei Shangguan, Zimu Zhou, Yunhao Liu
Smokey: Ubiquitous Smoking Detection With Commercial Wifi Infrastructures, Xiaolong Zheng, Jiliang Wang, Longfei Shangguan, Zimu Zhou, Yunhao Liu
Research Collection School Of Computing and Information Systems
Even though indoor smoking ban is being put into practice in civilized countries, existing vision or sensor-based smoking detection methods cannot provide ubiquitous smoking detection. In this paper, we take the first attempt to build a ubiquitous passive smoking detection system, which leverages the patterns smoking leaves on WiFi signals to identify the smoking activity even in the non-line-of-sight and through-wall environments. We study the behaviors of smokers and leverage the common features to recognize the series of motions during smoking, avoiding the target-dependent training set to achieve the high accuracy. We design a foreground detection based motion acquisition method …
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
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
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
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
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 …
Ontology-Aided Feature Correlation For Multi-Modal Urban Sensing, Archan Misra, Zaman Lantra, Kasthuri Jayarajah
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.
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
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
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 …
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
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 …
Lightsense: Exploiting Smart Bulbs For Practical Multimodal Localization, Huynh Nguyen, Archan Misra, Youngki Lee
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 …
Semantic Memory Modeling And Memory Interaction In Learning Agents, Wenwen Wang, Ah-Hwee Tan, Loo-Nin Teow
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 …
History Driven Program Repair, Xuan-Bach D. Le, David Lo, Claire Le Goues
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 …