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41st IEEE/ACM International Conference on Software Engineering (ICSE)

作者： Rahman, Musfiqur Palani, Dharani Rigby, Peter C. Concordia Univ Dept Comp Sci & Software Engn Montreal PQ Canada

ISBN: (纸本)9781728108698

Recent works have concluded that software code is more repetitive and predictable, i.e. more natural, than English texts. On re-examination, we find that much of the apparent "naturalness" of source code is due to the presence of language specific syntax, especially separators, such as semi-colons and brackets. For example, separators account for 44% of all tokens in our Java corpus. When we follow the NLP practices of eliminating punctuation (e.g., separators) and stopwords (e.g., keywords), we find that code is still repetitive and predictable, but to a lesser degree than previously thought. We suggest that SyntaxTokens be filtered to reduce noise in code recommenders. Unlike the code written for a particular project, API code usage is similar across projects: a file is opened and closed in the same manner regardless of domain. When we restrict our n-grams to those contained in the Java API, we find that API usages are highly repetitive. Since API calls are common across programs, researchers have made reliable statistical models to recommend sophisticated API call sequences. Sequential n-gram models were developed for natural languages. Code is usually represented by an AST which contains control and data flow, making n-grams models a poor representation of code. Comparing n-grams to statistical graph representations of the same codebase, we find that graphs are more repetitive and contain higherlevel patterns than n-grams. We suggest that future work focus on statistical code graphs models that accurately capture complex coding patterns. Our replication package makes our scripts and data available to future researchers [1].

关键词： Basic Science Entropy Language Models Statistical Code Graphs stackoverflow

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Going Green: An Exploratory Analysis of Energy-Related Questions 12

Going Green: An Exploratory Analysis of Energy-Related Quest...

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12th Working Conference on Mining Software Repositories (MSR)

作者： Malik, Haroon Zhao, Peng Godfrey, Michael Univ Waterloo David R Cheriton Sch Comp Sci Waterloo ON N2L 3G1 Canada

ISBN: (纸本)9780769555942

The popularity of smartphones - small computers that run on battery power - has exploded in the last decade. Unsurprisingly, power consumption is an overarching concern for mobile app developers, who are anxious to learn about power-related problems that are encountered by others. In this paper, we present an empirical study exploring the characteristics of energy-related questions posed in stackoverflow, issues faced by the developers, and the most significantly discussed APIs. We extracted a sample of 5009 stackoverflow questions, and manually analyzed 1000 posts of Android-related energy questions. Our study shows that developers are most concerned about energy-related issues that concern improper implementations, sensor, and radio utilization.

关键词： stackoverflow Energy Power API

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Learning from Gurus: Analysis and Modeling of Reopened Questions on Stack Overflow 16

Learning from Gurus: Analysis and Modeling of Reopened Quest...

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3rd ACM IKDD Conference on Data Sciences (CODS)

作者： Gupta, Rishabh Reddy, P. Krishna Int Inst Informat Technol Hyderabad Andhra Pradesh India

ISBN: (纸本)9781450342179

Community-driven Question Answering (Q&A) platforms are gaining popularity now-a-days and the number of posts on such platforms are increasing tremendously. Thus, the challenge to keep these platforms noise-free is attracting the interest of research community. Stack Overflow is one such popular computer programming related Q&A platform. The established users on Stack Overflow have learnt the acceptable format and scope of questions in due course. Even if their questions get closed, they are aware of the required edits, therefore the chances of their questions being reopened increases. On the other hand, non-established users have not adapted to the Stack Overflow system and find difficulty in editing their closed questions. In this work, we aim to identify features which help differentiate editing approaches of established and non-established users, and motivate the need of recommendation model. Such a recommendation model can assist every user to edit their closed questions leveraging the edit-style of the established users of the platform.

关键词： stackoverflow reopened questions closed questions edits

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How Do Developers React to RESTful API Evolution? 12

How Do Developers React to RESTful API Evolution?

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12th International Conference on Service-Oriented Computing (ICSOC)

作者： Wang, Shaohua Keivanloo, Iman Zou, Ying Queens Univ Kingston ON Canada

ISBN: (纸本)9783662453919;9783662453902

With the rapid adoption of REpresentational State Transfer (REST), more software organizations expose their applications as RESTful web APIs and client code developers integrate RESTful APIs into their applications. When web APIs evolve, the client code developers have to update their applications to incorporate the API changes accordingly. However client code developers often encounter challenges during the migration and API providers have little knowledge of how client code developers react to the API changes. In this paper, we investigate the changes among subsequent versions of APIs and classify the identified changes to understand how the RESTful web APIs evolve. We study the on-line discussion from developers to the API changes by analyzing the stackoverflow questions. Through an empirical study, we identify 21 change types and 7 of them are new compared with existing studies. We find that a larger portion of RESTful web API elements are changed between versions compared with Java APIs and WSDL services. Moreover, our results show that adding new methods in the new version causes more questions and views from developers. However the deleted methods draw more relevant discussions. In general, our results provide valuable insights of RESTful web API evolution and help service providers understand how their consumers react to the API changes in order to improve the practice of evolving the service APIs.

关键词： REST API API Evolution stackoverflow Social Media

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Modeling Information Sharing Behavior on Q&A Forums 1

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21st Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD)

作者： Cui, Biru Yang, Shanchieh Jay Homan, Christophan M. Rochester Inst Technol Comp & Informat Sci Rochester NY 14623 USA Rochester Inst Technol Comp Engn Rochester NY 14623 USA Rochester Inst Technol Comp Sci Rochester NY 14623 USA

ISBN: (数字)9783319575292

ISBN: (纸本)9783319575292;9783319575285

Q&A forums pool massive amounts of crowd expertise from a broad spectrum of geographical, cultural, and disciplinary knowledge toward specific, user-posed questions. Existing studies on these forums focus on how to route questions to the best answerers based on content or predict whether a question will be answered, but few of them investigated the inherent knowledge sharing relationship among users. We study knowledge sharing among users of stackoverflow, a popular Q&A forum, where the knowledge sharing process is related to the time elapsed since a question was posted, the reputation of the questioner, and the content of the posted text. Taking these factors into consideration, the paper proposes time-based information sharing model (TISM), where the likelihood a user will share or provide knowledge to another is modeled as a continuous function of time, reputation, and post length. With the resulting knowledge sharing network learned by TISM, we are able to predict for a given question the number of responses over time, who will answer the question and who will provide the accepted answer. Our experiments show that predictions using TISM outperform NetRate, query likelihood language, random forest, and linear regression models.

关键词： stackoverflow Knowledge sharing Question answering

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Comparing Foraging Behavior Across Code Hosting and Q&A Platforms through a Gender Lens

Comparing Foraging Behavior Across Code Hosting and Q&A Plat...

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IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)

作者： Leon, Shahnewaz Tamanna, Mahzabin Kuttal, Sandeep Kaur NC State Univ Dept Comp Sci Raleigh NC 27695 USA

ISBN: (纸本)9798350329469

This study compares the information foraging behavior of developers on two prominent platforms, stackoverflow and GitHub, which are widely used for code hosting and question and answer purposes. Understanding how developers seek and retrieve information is crucial for designing effective interfaces. In a gender and expertise-balanced study involving 12 developers, we utilized Information Foraging Theory to analyze their foraging behavior. Our findings revealed contrasting patterns, with women spending 30% more time and utilizing 21.24% more cues on GitHub, while men utilized 55% more time and 19.7% more cues on stackoverflow. These insights have significant implications for optimizing website design and information presentation to enhance the efficiency and effectiveness of developers' information-seeking processes.

关键词： Information Foraging Theory GitHub stackoverflow Gender Qualitative Analysis

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Evaluating bug severity using crowd-based knowledge: An exploratory study 15

Evaluating bug severity using crowd-based knowledge: An expl...

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7th Asia-Pacific Symposium on Internetware, Internetware 2015

作者： Zhang, Yang Yin, Gang Wang, Tao Yu, Yue Wang, Huaimin Key Lab. of Parallel and Distributed Computing College of Computer National University of Defense Technology Changsha410073 China

ISBN: (纸本)9781450336413

In bug tracking system, the high volume of incoming bug reports poses a serious challenge to project managers. Triaging these bug reports manually consumes time and resources which leads to delaying the resolution of important bugs. StackOverow is the most popular crowdsourcing Q&A community with plenty of bug-related posts. In this paper, we explore the correlation between bug severity and the crowd attributes of linked posts. Two typical types of projects' bug repositories are studied here, e.g. Mozilla (user-centric project) and Eclipse (developer-centric project). Our results show that the bug severity is consistent with the crowd- based knowledge both in Mozilla and Eclipse, i.e. the linked posts of severe bugs have higher score etc. in StackOverow than non-severe bugs. This interesting phenomenon inspires us that we can optimize the existing evaluation methods of bug severity by incorporating the crowd-based knowledge from a third-party in future. © 2015 ACM.

关键词： stackoverflow crowd-based knowledge Bugzilla Bug severity

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Effects of Personality Traits and Emotional Factors in Pull Request Acceptance.

Effects of Personality Traits and Emotional Factors in Pull ...

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作者： Iyer, Rahul University of Waterloo

学位级别：硕士

Social interactions in the form of discussion are an indispensable part of collaborative software development. The discussions are essential for developers to share their views and to form a strong relationship with other teammates. These discussions invoke both positive and negative emotions such as joy, love, aggression, and disgust. Additionally, developers also exhibit hidden behaviours that dictate their personality. Some developers can be supportive and open to new ideas, whereas others can be conservative. Past research has shown that the personality of the developers has a significant role in determining the success of the task they collaboratively perform. Additionally, previous research has also shown that in online collaborative environments, the developers use signals from comments such as rudeness to determine if they are compatible to work together. Most of these studies use traditional small-scale surveys for their experiments. The transparent nature of online collaborative environments makes it easier to conduct empirical experiments by mining pull request comments. In this thesis, first, we investigate the effect of different personality traits on pull request acceptance. The results of this experiment will provide us with a valuable understanding of the personality traits of developers and help us develop tools to assist developers. We follow it with a second experiment to understand the influence of different emotional factors on pull request decisions. The emotion expressed by a developer on their teammates can be influenced by social statuses, such as the number of followers. Moreover, the teammate's team status, such as team member or outside contributor too, can influence the emotional effect. To understand moderation, we investigate different interaction effects. We start the experiment by replicating Tsay et al.'s work that examined the influence of social factors (e.g., `social distance') and technical factors (e.g., test file inclusion) fo

关键词： pull request github developer personality emotions language model stackoverflow open source

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Secure Coding Practices in Java: Challenges and Vulnerabilities 18

Secure Coding Practices in Java: Challenges and Vulnerabilit...

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40th ACM/IEEE International Conference on Software Engineering (ICSE)

作者： Meng, Na Nagy, Stefan Yao, Danfeng (Daphne) Zhuang, Wenjie Argoty, Gustavo Arango Virginia Tech Dept Comp Sci Blacksburg VA 24061 USA

ISBN: (纸本)9781450356381

The Java platform and its third-party libraries provide useful features to facilitate secure coding. However, misusing them can cost developers time and effort, as well as introduce security vulnerabilities in software. We conducted an empirical study on stackoverflow posts, aiming to understand developers' concerns on Java secure coding, their programming obstacles, and insecure coding practices. We observed a wide adoption of the authentication and authorization features provided by Spring Security-a third-party framework designed to secure enterprise applications. We found that programming challenges are usually related to APIs or libraries, including the complicated cross-language data handling of cryptography APIs, and the complex Java-based or XML-based approaches to configure Spring Security. In addition, we reported multiple security vulnerabilities in the suggested code of accepted answers on the stackoverflow forum. The vulnerabilities included disabling the default protection against Cross-Site Request Forgery (CSRF) attacks, breaking SSL/TLS security through bypassing certificate validation, and using insecure cryptographic hash functions. Our findings reveal the insufficiency of secure coding assistance and documentation, as well as the huge gap between security theory and coding practices.

关键词： Secure coding Spring Security CSRF SSL/TLS certificate validation cryptographic hash functions authentication authorization stackoverflow cryptography

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An empirical study of COVID-19 related posts on Stack Overflow: Topics and technologies

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JOURNAL OF SYSTEMS AND SOFTWARE 2021年 182卷 111089-111089页

作者： Georgiou, Konstantinos Mittas, Nikolaos Chatzigeorgiou, Alexandros Angelis, Lefteris Aristotle Univ Thessaloniki Sch Informat Thessaloniki Greece Int Hellen Univ Dept Chem Kavala Greece Univ Macedonia Dept Appl Informat Thessaloniki Greece

The COVID-19 outbreak, also known as the coronavirus pandemic, has left its mark on every aspect of our lives and at the time of this writing is still an ongoing battle. Beyond the immediate global wide health response, the pandemic has triggered a significant number of IT initiatives to track, visualize, analyze and potentially mitigate the phenomenon. For individuals or organizations interested in developing COVID-19 related software, knowledge-sharing communities such as Stack Overflow proved to be an effective source of information for tackling commonly encountered problems. As an additional contribution to the investigation of this unprecedented health crisis and to assess how fast and how well the community of developers has responded, we performed a study on COVID-19 related posts in Stack Overflow. In particular, we profiled relevant questions based on key post features and their evolution, identified the most prominent technologies adopted for developing COVID-19 software and their interrelations and focused on the most persevering problems faced by developers. For the analysis of posts we employed descriptive statistics, Association Rule Graphs, Survival Analysis and Latent Dirichlet Allocation. The results reveal that the response of the developers' community to the pandemic was immediate and that the interest of developers on COVID-19 related challenges was sustained after its initial peak. In terms of the problems addressed, the results show a clear focus on COVID-19 data collection, analysis and visualization from/to the web, in line with the general needs for monitoring the pandemic. (C) 2021 Elsevier Inc. All rights reserved.

关键词： COVID-19 Pandemic stackoverflow Knowledge-sharing

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