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Full-Text Articles in Entire DC Network
Xai4fl: Enhancing Spectrum-Based Fault Localization With Explainable Artificial Intelligence, Ratnadira Widyasari, Gede Artha Azriadi Prana, Stefanus Agus Haryono, Yuan Tian, Hafil Noer Zachiary, David Lo
Xai4fl: Enhancing Spectrum-Based Fault Localization With Explainable Artificial Intelligence, Ratnadira Widyasari, Gede Artha Azriadi Prana, Stefanus Agus Haryono, Yuan Tian, Hafil Noer Zachiary, David Lo
Research Collection School Of Computing and Information Systems
Manually finding the program unit (e.g., class, method, or statement) responsible for a fault is tedious and time-consuming. To mitigate this problem, many fault localization techniques have been proposed. A popular family of such techniques is spectrum-based fault localization (SBFL), which takes program execution traces (spectra) of failed and passed test cases as input and applies a ranking formula to compute a suspiciousness score for each program unit. However, most existing SBFL techniques fail to consider two facts: 1) not all failed test cases contribute equally to a considered fault(s), and 2) program units collaboratively contribute to the failure/pass of …
Topic-Guided Conversational Recommender In Multiple Domains, Lizi Liao, Ryuichi Takanobu, Yunshan Ma, Xun Yang, Minlie Huang, Tat-Seng Chua
Topic-Guided Conversational Recommender In Multiple Domains, Lizi Liao, Ryuichi Takanobu, Yunshan Ma, Xun Yang, Minlie Huang, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Conversational systems have recently attracted significant attention. Both the research community and industry believe that it will exert huge impact on human-computer interaction, and specifically, the IR/RecSys community has begun to explore Conversational Recommendation. In real-life scenarios, such systems are often urgently needed in helping users accomplishing different tasks under various situations. However, existing works still face several shortcomings: (1) Most efforts are largely confined in single task setting. They fall short of hands in handling tasks across domains. (2) Aside from soliciting user preference from dialogue history, a conversational recommender naturally has access to the back-end data structure which …
Practitioners' Expectations On Automated Code Comment Generation, Xing Hu, Xin Xia, David Lo, Zhiyuan Wan, Qiuyuan Chen, Thomas Zimmermann
Practitioners' Expectations On Automated Code Comment Generation, Xing Hu, Xin Xia, David Lo, Zhiyuan Wan, Qiuyuan Chen, Thomas Zimmermann
Research Collection School Of Computing and Information Systems
Good comments are invaluable assets to software projects, as they help developers understand and maintain projects. However, due to some poor commenting practices, comments are often missing or inconsistent with the source code. Software engineering practitioners often spend a significant amount of time and effort reading and understanding programs without or with poor comments. To counter this, researchers have proposed various techniques to automatically generate code comments in recent years, which can not only save developers time writing comments but also help them better understand existing software projects. However, it is unclear whether these techniques can alleviate comment issues and …
Arseek: Identifying Api Resource Using Code And Discussion On Stack Overflow, Gia Kien Luong, Mohammad Hadi, Thung Ferdian, Fatemeh H. Fard, David Lo
Arseek: Identifying Api Resource Using Code And Discussion On Stack Overflow, Gia Kien Luong, Mohammad Hadi, Thung Ferdian, Fatemeh H. Fard, David Lo
Research Collection School Of Computing and Information Systems
It is not a trivial problem to collect API-relevant examples, usages, and mentions on venues such as Stack Overflow. It requires efforts to correctly recognize whether the discussion refers to the API method that developers/tools are searching for. The content of the Stack Overflow thread, which consists of both text paragraphs describing the involvement of the API method in the discussion and the code snippets containing the API invocation, may refer to the given API method. Leveraging this observation, we develop ARSeek, a context-specific algorithm to capture the semantic and syntactic information of the paragraphs and code snippets in a …
An Exploratory Study On Code Attention In Bert, Rishab Sharma, Fuxiang Chen, Fatemeh H. Fard, David Lo
An Exploratory Study On Code Attention In Bert, Rishab Sharma, Fuxiang Chen, Fatemeh H. Fard, David Lo
Research Collection School Of Computing and Information Systems
Many recent models in software engineering introduced deep neural models based on the Transformer architecture or use transformerbased Pre-trained Language Models (PLM) trained on code. Although these models achieve the state of the arts results in many downstream tasks such as code summarization and bug detection, they are based on Transformer and PLM, which are mainly studied in the Natural Language Processing (NLP) field. The current studies rely on the reasoning and practices from NLP for these models in code, despite the differences between natural languages and programming languages. There is also limited literature on explaining how code is modeled. …
An Empirical Study Of Memorization In Nlp, Xiaosen Zheng, Jing Jiang
An Empirical Study Of Memorization In Nlp, Xiaosen Zheng, Jing Jiang
Research Collection School Of Computing and Information Systems
A recent study by Feldman (2020) proposed a long-tail theory to explain the memorization behavior of deep learning models. However, memorization has not been empirically verified in the context of NLP, a gap addressed by this work. In this paper, we use three different NLP tasks to check if the long-tail theory holds. Our experiments demonstrate that top-ranked memorized training instances are likely atypical, and removing the top-memorized training instances leads to a more serious drop in test accuracy compared with removing training instances randomly. Furthermore, we develop an attribution method to better understand why a training instance is memorized. …
Structure-Aware Visualization Retrieval, Haotian Li, Yong Wang, Wu Aoyu, Huan Wei, Huamin Qu
Structure-Aware Visualization Retrieval, Haotian Li, Yong Wang, Wu Aoyu, Huan Wei, Huamin Qu
Research Collection School Of Computing and Information Systems
With the wide usage of data visualizations, a huge number of Scalable Vector Graphic (SVG)-based visualizations have been created and shared online. Accordingly, there has been an increasing interest in exploring how to retrieve perceptually similar visualizations from a large corpus, since it can beneft various downstream applications such as visualization recommendation. Existing methods mainly focus on the visual appearance of visualizations by regarding them as bitmap images. However, the structural information intrinsically existing in SVG-based visualizations is ignored. Such structural information can delineate the spatial and hierarchical relationship among visual elements, and characterize visualizations thoroughly from a new perspective. …
Exais: Executable Ai Semantics, Richard Schumi, Jun Sun
Exais: Executable Ai Semantics, Richard Schumi, Jun Sun
Research Collection School Of Computing and Information Systems
Neural networks can be regarded as a new programming paradigm, i.e., instead of building ever-more complex programs through (often informal) logical reasoning in the programmers' mind, complex 'AI' systems are built by optimising generic neural network models with big data. In this new paradigm, AI frameworks such as TensorFlow and PyTorch play a key role, which is as essential as the compiler for traditional programs. It is known that the lack of a proper semantics for programming languages (such as C), i.e., a correctness specification for compilers, has contributed to many problematic program behaviours and security issues. While it is …
Efficient Encrypted Data Search With Expressive Queries And Flexible Update, Jianting Ning, Jiageng Chen, Kaitai Liang, Joseph K. Liu, Chunhua Su, Qianhong Wu
Efficient Encrypted Data Search With Expressive Queries And Flexible Update, Jianting Ning, Jiageng Chen, Kaitai Liang, Joseph K. Liu, Chunhua Su, Qianhong Wu
Research Collection School Of Computing and Information Systems
Outsourcing encrypted data to cloud servers that has become a prevalent trend among Internet users to date. There is a long list of advantages on data outsourcing, such as the reduction cost of local data management. How to securely operate encrypted data (remotely), however, is the top-rank concern over data owner. Liang et al. proposed a novel encrypted cloud-based data share and search system without loss of privacy. The system allows users to flexibly search and share encrypted data as well as updating keyword field. However, the search complexity of the system is of extreme inefficiency, O(nd), where d is …
Press A To Jump: Design Strategies For Video Game Learnability, Lev Poretski, Anthony Tang
Press A To Jump: Design Strategies For Video Game Learnability, Lev Poretski, Anthony Tang
Research Collection School Of Computing and Information Systems
Learnability is a core aspect of software usability. Video games are not an exception, as game designers need to teach players how to play their creations. We analyzed 40 contemporary video games to identify how video games approach learning experiences. We found that games have advanced far beyond using simple tutorials or demonstration screens and adopt a range of repeatable and reusable design strategies using visual cues to facilitate learning. We provide a detailed descriptive framework of these design strategies, elucidating how and when they can be used, and describing how the visual cues are used to build them. Our …
Active Warden Attack: On The (In)Effectiveness Of Android App Repackage-Proofing, Haoyu Ma, Shijia Li, Debin Gao, Daoyuan Wu, Qiaowen Jia, Chunfu Jia
Active Warden Attack: On The (In)Effectiveness Of Android App Repackage-Proofing, Haoyu Ma, Shijia Li, Debin Gao, Daoyuan Wu, Qiaowen Jia, Chunfu Jia
Research Collection School Of Computing and Information Systems
App repackaging has raised serious concerns to the Android ecosystem with the repackage-proofing technology attracting attention in the Android research community. In this paper, we first show that existing repackage-proofing schemes rely on a flawed security assumption, and then propose a new class of active warden attack that intercepts and falsifies the metrics used by repackage-proofing for detecting the integrity violations during repackaging. We develop a proof-of-concept toolkit to demonstrate that all the existing repackage-proofing schemes can be bypassed by our attack toolkit. On the positive side, our analysis further identifies a new integrity metric in the Android ART runtime …
Competition And Third-Party Platform-Integration In Ride-Sourcing Markets, Yaqian Zhou, Hai Yang, Jintao Ke, Hai Wang, Xinwei Li
Competition And Third-Party Platform-Integration In Ride-Sourcing Markets, Yaqian Zhou, Hai Yang, Jintao Ke, Hai Wang, Xinwei Li
Research Collection School Of Computing and Information Systems
Recently, some third-party integrators attempt to integrate the ride services offered by multiple independent ride-sourcing platforms. Accordingly, passengers can request ride through the integrators and receive ride service from any one of the ride-sourcing platforms. This novel business model, termed as third-party platform-integration in this work, has potentials to alleviate market fragmentation cost resulting from demand splitting among multiple platforms. Although most existing studies focus on operation strategies for one single monopolist platform, much less is known about the competition and platform-integration and their implications on operation strategy and system efficiency. In this work, we propose mathematical models to describe …
Itss: Interactive Web-Based Authoring And Playback Integrated Environment For Programming Tutorials, Eng Lieh Ouh, Benjamin Gan, David Lo
Itss: Interactive Web-Based Authoring And Playback Integrated Environment For Programming Tutorials, Eng Lieh Ouh, Benjamin Gan, David Lo
Research Collection School Of Computing and Information Systems
Video-based programming tutorials are a popular form of tutorial used by authors to guide learners to code. Still, the interactivity of these videos is limited primarily to control video flow. There are existing works with increased interactivity that are shown to improve the learning experience. Still, these solutions require setting up a custom recording environment and are not well-integrated with the playback environment. This paper describes our integrated ITSS environment and evaluates the ease of authoring and playback of our interactive programming tutorials. Our environment is designed to run within the browser sandbox and is less intrusive to record interactivity …
Undiscounted Recursive Path Choice Models: Convergence Properties And Algorithms, Tien Mai, Emma Frejinger
Undiscounted Recursive Path Choice Models: Convergence Properties And Algorithms, Tien Mai, Emma Frejinger
Research Collection School Of Computing and Information Systems
Traffic flow predictions are central to a wealth of problems in transportation. Path choice models can be used for this purpose, and in state-of-the-art models—so-called recursive path choice (RPC) models—the choice of a path is formulated as a sequential arc choice process using undiscounted Markov decision process (MDP) with an absorbing state. The MDP has a utility maximization objective with unknown parameters that are estimated based on data. The estimation and prediction using RPC models require repeatedly solving value functions that are solutions to the Bellman equation. Although there are several examples of successful applications of RPC models in the …
Unified Route Planning For Shared Mobility: An Insertion-Based Framework, Yongxin Tong, Yuxiang Zeng, Zimu Zhou, Lei Chen, Ke. Xu
Unified Route Planning For Shared Mobility: An Insertion-Based Framework, Yongxin Tong, Yuxiang Zeng, Zimu Zhou, Lei Chen, Ke. Xu
Research Collection School Of Computing and Information Systems
There has been a dramatic growth of shared mobility applications such as ride-sharing, food delivery, and crowdsourced parcel delivery. Shared mobility refers to transportation services that are shared among users, where a central issue is route planning. Given a set of workers and requests, route planning finds for each worker a route, i.e., a sequence of locations to pick up and drop off passengers/parcels that arrive from time to time, with different optimization objectives. Previous studies lack practicability due to their conflicted objectives and inefficiency in inserting a new request into a route, a basic operation called insertion. In addition, …
Adaptive Task Planning For Large-Scale Robotized Warehouses, Dingyuan Shi, Yongxin Tong, Zimu Zhou, Ke Xu, Wenzhe Tan, Hongbo Li
Adaptive Task Planning For Large-Scale Robotized Warehouses, Dingyuan Shi, Yongxin Tong, Zimu Zhou, Ke Xu, Wenzhe Tan, Hongbo Li
Research Collection School Of Computing and Information Systems
Robotized warehouses are deployed to automatically distribute millions of items brought by the massive logistic orders from e-commerce. A key to automated item distribution is to plan paths for robots, also known as task planning, where each task is to deliver racks with items to pickers for processing and then return the rack back. Prior solutions are unfit for large-scale robotized warehouses due to the inflexibility to time-varying item arrivals and the low efficiency for high throughput. In this paper, we propose a new task planning problem called TPRW, which aims to minimize the end-to-end makespan that incorporates the entire …
Guided Attention Multimodal Multitask Financial Forecasting With Inter-Company Relationships And Global And Local News, Meng Kiat Gary Ang, Ee-Peng Lim
Guided Attention Multimodal Multitask Financial Forecasting With Inter-Company Relationships And Global And Local News, Meng Kiat Gary Ang, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Most works on financial forecasting use information directly associated with individual companies (e.g., stock prices, news on the company) to predict stock returns for trading. We refer to such company-specific information as local information. Stock returns may also be influenced by global information (e.g., news on the economy in general), and inter-company relationships. Capturing such diverse information is challenging due to the low signal-to-noise ratios, different time-scales, sparsity and distributions of global and local information from different modalities. In this paper, we propose a model that captures both global and local multimodal information for investment and risk management-related forecasting tasks. …
Indoor Localization Using Solar Cells, Hamada Rizk, Dong Ma, Mahbub Hassan, Moustafa Youssef
Indoor Localization Using Solar Cells, Hamada Rizk, Dong Ma, Mahbub Hassan, Moustafa Youssef
Research Collection School Of Computing and Information Systems
The development of the Internet of Things (IoT) opens the doors for innovative solutions in indoor positioning systems. Recently, light-based positioning has attracted much attention due to the dense and pervasive nature of light sources (e.g., Light-emitting Diode lighting) in indoor environments. Nevertheless, most existing solutions necessitate carrying a high-end phone at hand in a specific orientation to detect the light intensity with the phone's light sensing capability (i.e., light sensor or camera). This limits the ease of deployment of these solutions and leads to drainage of the phone battery. We propose PVDeepLoc, a device-free light-based indoor localization system that …
Quid Pro Quo: An Exploration Of Reciprocity In Code Review, Carlos Gavidia-Calderon, Donggyun Han, Amel Bennaceur
Quid Pro Quo: An Exploration Of Reciprocity In Code Review, Carlos Gavidia-Calderon, Donggyun Han, Amel Bennaceur
Research Collection School Of Computing and Information Systems
We explore the role of reciprocity in code review processes. Reciprocity manifests itself in two ways: 1) reviewing code for others translates to accepted code contributions, and 2) having contributions accepted increases the reviews made for others. We use vector autoregressive (VAR) models to explore the causal relation between reviews performed and accepted contributions. After fitting VAR models for 24 active open-source developers, we found evidence of reciprocity in 6 of them. These results suggest reciprocity does play a role in code review, that can potentially be exploited to increase reviewer participation.
Uipdroid: Unrooted Dynamic Monitor Of Android App Uis For Fine-Grained Permission Control, Mulin Duan, Lingxiao Jiang, Lwin Khin Shar, Debin Gao
Uipdroid: Unrooted Dynamic Monitor Of Android App Uis For Fine-Grained Permission Control, Mulin Duan, Lingxiao Jiang, Lwin Khin Shar, Debin Gao
Research Collection School Of Computing and Information Systems
Proper permission controls in Android systems are important for protecting users' private data when running applications installed on the devices. Currently Android systems require apps to obtain authorization from users at the first time when they try to access users' sensitive data, but every permission is only managed at the application level, allowing apps to (mis)use permissions granted by users at the beginning for different purposes subsequently without informing users. Based on privacy-by-design principles, this paper develops a new permission manager, named UIPDroid, that (1) enforces the users' basic right-to-know through user interfaces whenever an app uses permissions, and (2) …
Neighborhood Cooperative Multiagent Reinforcement Learning For Adaptive Traffic Signal Control In Epidemic Regions, Chengwei Zhang, Yu Tian, Zhibin Zhang, Wanli Xue, Xiaofei Xie, Tianpei Yang, Xin Ge, Rong Chen
Neighborhood Cooperative Multiagent Reinforcement Learning For Adaptive Traffic Signal Control In Epidemic Regions, Chengwei Zhang, Yu Tian, Zhibin Zhang, Wanli Xue, Xiaofei Xie, Tianpei Yang, Xin Ge, Rong Chen
Research Collection School Of Computing and Information Systems
Nowadays, multiagent reinforcement learning (MARL) have shared significant advances in the adaptive traffic signal control (ATSC) problems. For most of the researches, agents are all isomorphic, which disregards the situation in which isomerous intersections cooperative together in a real ATSC scenario, especially in epidemic regions where different intersections have quite different levels of importance. To this end, this paper models the ATSC problem as a networked Markov game (NMG), in which agents take into account information, including traffic conditions of it and its connected neighbors. A cooperative MARL framework named neighborhood cooperative hysteretic DQN (NC-HDQN) is proposed. Specifically, for each …
Optimal In‐Place Suffix Sorting, Zhize Li, Jian Li, Hongwei Huo
Optimal In‐Place Suffix Sorting, Zhize Li, Jian Li, Hongwei Huo
Research Collection School Of Computing and Information Systems
The suffix array is a fundamental data structure for many applications that involve string searching and data compression. Designing time/space-efficient suffix array construction algorithms has attracted significant attention and considerable advances have been made for the past 20 years. We obtain the \emph{first} in-place suffix array construction algorithms that are optimal both in time and space for (read-only) integer alphabets. Concretely, we make the following contributions: 1. For integer alphabets, we obtain the first suffix sorting algorithm which takes linear time and uses only $O(1)$ workspace (the workspace is the total space needed beyond the input string and the output …
Exploring And Adapting Chinese Gpt To Pinyin Input Method, Minghuan Tan, Yong Dai, Duyu Tang, Zhangyin Feng, Guoping Huang, Jing Jiang, Jiwei Li, Shuming Shi
Exploring And Adapting Chinese Gpt To Pinyin Input Method, Minghuan Tan, Yong Dai, Duyu Tang, Zhangyin Feng, Guoping Huang, Jing Jiang, Jiwei Li, Shuming Shi
Research Collection School Of Computing and Information Systems
While GPT has become the de-facto method for text generation tasks, its application to pinyin input method remains unexplored. In this work, we make the first exploration to leverage Chinese GPT for pinyin input method. We find that a frozen GPT achieves state-of-the-art performance on perfect pinyin. However, the performance drops dramatically when the input includes abbreviated pinyin. A reason is that an abbreviated pinyin can be mapped to many perfect pinyin, which links to even larger number of Chinese characters. We mitigate this issue with two strategies, including enriching the context with pinyin and optimizing the training process to …
Rumorlens: Interactive Analysis And Validation Of Suspected Rumors On Social Media, Ran Wang, Kehan Du, Qianhe Chen, Yifei Zhao, Mojie Tang, Hongxi Tao, Shipan Wang, Yiyao Li, Yong Wang
Rumorlens: Interactive Analysis And Validation Of Suspected Rumors On Social Media, Ran Wang, Kehan Du, Qianhe Chen, Yifei Zhao, Mojie Tang, Hongxi Tao, Shipan Wang, Yiyao Li, Yong Wang
Research Collection School Of Computing and Information Systems
With the development of social media, various rumors can be easily spread on the Internet and such rumors can have serious negative effects on society. Thus, it has become a critical task for social media platforms to deal with suspected rumors. However, due to the lack of effective tools, it is often difficult for platform administrators to analyze and validate rumors from a large volume of information on a social media platform efficiently. We have worked closely with social media platform administrators for four months to summarize their requirements of identifying and analyzing rumors, and further proposed an interactive visual …
Ptm4tag: Sharpening Tag Recommendation Of Stack Overflow Posts With Pre-Trained Models, Junda He, Bowen Xu, Zhou Yang, Donggyun Han, Chengran Yang, David Lo
Ptm4tag: Sharpening Tag Recommendation Of Stack Overflow Posts With Pre-Trained Models, Junda He, Bowen Xu, Zhou Yang, Donggyun Han, Chengran Yang, David Lo
Research Collection School Of Computing and Information Systems
Stack Overflow is often viewed as one of the most influential Software Question & Answer (SQA) websites, containing millions of programming-related questions and answers. Tags play a critical role in efficiently structuring the contents in Stack Overflow and are vital to support a range of site operations, e.g., querying relevant contents. Poorly selected tags often introduce extra noise and redundancy, which raises problems like tag synonym and tag explosion. Thus, an automated tag recommendation technique that can accurately recommend high-quality tags is desired to alleviate the problems mentioned above.
Data Pricing In Machine Learning Pipelines, Zicun Cong, Xuan Luo, Jian Pei, Feida Zhu, Yong Zhang
Data Pricing In Machine Learning Pipelines, Zicun Cong, Xuan Luo, Jian Pei, Feida Zhu, Yong Zhang
Research Collection School Of Computing and Information Systems
Machine learning is disruptive. At the same time, machine learning can only succeed by collaboration among many parties in multiple steps naturally as pipelines in an eco-system, such as collecting data for possible machine learning applications, collaboratively training models by multiple parties and delivering machine learning services to end users. Data are critical and penetrating in the whole machine learning pipelines. As machine learning pipelines involve many parties and, in order to be successful, have to form a constructive and dynamic eco-system, marketplaces and data pricing are fundamental in connecting and facilitating those many parties. In this article, we survey …
Gdefects4dl: A Dataset Of General Real-World Deep Learning Program Defects, Yunkai Liang, Yun Lin, Xuezhi Song, Jun Sun, Zhiyong Feng, Jin Song Dong
Gdefects4dl: A Dataset Of General Real-World Deep Learning Program Defects, Yunkai Liang, Yun Lin, Xuezhi Song, Jun Sun, Zhiyong Feng, Jin Song Dong
Research Collection School Of Computing and Information Systems
The development of deep learning programs, as a new programming paradigm, is observed to suffer from various defects. Emerging research works have been proposed to detect, debug, and repair deep learning bugs, which drive the need to construct the bug benchmarks. In this work, we present gDefects4DL, a dataset for general bugs of deep learning programs. Comparing to existing datasets, gDefects4DL collects bugs where the root causes and fix solutions can be well generalized to other projects. Our general bugs include deep learning program bugs such as (1) violation of deep learning API usage pattern (e.g., the standard to implement …
Cost-Effective And Collaborative Methods To Author Video's Scene Description For Blind People, Rosiana Natalie
Cost-Effective And Collaborative Methods To Author Video's Scene Description For Blind People, Rosiana Natalie
Research Collection School Of Computing and Information Systems
The majority of online video content remains inaccessible for blind people due to the lack of audio descriptions. Content creators have traditionally relied on professionals to author audio descriptions, but their service is costly and not readily available. In this research, I introduce four threads of research that I will conduct for my Ph.D. dissertation, aimed to create methods and tools that are both time- and cost-effective in providing good quality audio descriptions. They are: (i) The development and evaluation of mixed-ability collaboration authoring tool, (ii) The formative study to uncover the feedback pattern from the reviewer, (iii) the evaluation …
Software Engineering User Study Recruitment On Prolific: An Experience Report, Brittany Reid, Markus Wagner, Marcelo D’Amorim, Christoph Treude
Software Engineering User Study Recruitment On Prolific: An Experience Report, Brittany Reid, Markus Wagner, Marcelo D’Amorim, Christoph Treude
Research Collection School Of Computing and Information Systems
Online participant recruitment platforms such as Prolific have been gaining popularity in research, as they enable researchers to easily access large pools of participants. However, participant quality can be an issue; participants may give incorrect information to gain access to more studies, adding unwanted noise to results. This paper details our experience recruiting participants from Prolific for a user study requiring programming skills in Node.js, with the aim of helping other researchers conduct similar studies. We explore a method of recruiting programmer participants using prescreening validation, attention checks and a series of programming knowledge questions. We received 680 responses, and …
Is Surprisal In Issue Trackers Actionable?, James Caddy, Markus Wagner, Christoph Treude, Earl T. Barr, Miltiadis Allamanis
Is Surprisal In Issue Trackers Actionable?, James Caddy, Markus Wagner, Christoph Treude, Earl T. Barr, Miltiadis Allamanis
Research Collection School Of Computing and Information Systems
Background. From information theory, surprisal is a measurement of how unexpected an event is. Statistical language models provide a probabilistic approximation of natural languages, and because surprisal is constructed with the probability of an event occuring, it is therefore possible to determine the surprisal associated with English sentences. The issues and pull requests of software repository issue trackers give insight into the development process and likely contain the surprising events of this process. Objective. Prior works have identified that unusual events in software repositories are of interest to developers, and use simple code metrics-based methods for detecting them. In this …