Rationale in Development Chat Messages: An Exploratory Study

Chat messages of development teams play an increasingly significant role in software development, having replaced emails in some cases. Chat messages contain information about discussed issues, considered alternatives and argumentation leading to the decisions made during software development. These elements, defined as rationale, are invaluable during software evolution for documenting and reusing development knowledge. Rationale is also essential for coping with changes and for effective maintenance of the software system. However, exploiting the rationale hidden in the chat messages is challenging due to the high volume of unstructured messages covering a wide range of topics. This work presents the results of an exploratory study examining the frequency of rationale in chat messages, the completeness of the available rationale and the potential of automatic techniques for rationale extraction. For this purpose, we apply content analysis and machine learning techniques on more than 8,700 chat messages from three software development projects. Our results show that chat messages are a rich source of rationale and that machine learning is a promising technique for detecting rationale and identifying different rationale elements.Comment: 11 pages, 6 figures. The 14th International Conference on Mining Software Repositories (MSR'17

Digital Deception in the Online Dating Space: A Study of Tinder

As technology continues to impart its worldview, the role of communication in the navigation of dating in online spaces has also evolved. This study examines the relationship between communication and digital deception within a selected population of Tinder users. Tinder is a geo-social, location-aware dating application that is used by millions of people around the world. There are three fundamentally specific objectives of this research, which include: first, examining the ways in which dating apps increase the possibility of digital deception; second, exploring ways in which Tinder\u27s design and functionality contribute to the occurrence of digital deception; and finally, identifying and examining the impacts of online deception, particularly in the context of dating apps, on human communication and relationship formation. To obtain first-hand perceptions of online representation and digital deception on Tinder (and as with other online social platforms), 51 Tinder users from Nigeria and Canada were surveyed through their responses to a questionnaire distributed on June 20 and July 11, 2023. The findings of this study suggest that the use of dating apps among youths has increased, leading to prevalent lying and distrust. In the context of using Tinder among the sampled population, Tinder\u27s design, functionality, and online communication in general facilitate and contribute to instances of digital deception, as its affordances only give room to do little, hence, there is often an attempt to ‘put best foot forward’ and the tendency of lying becomes imminent. Appearance influences deception, but some still trust online dating for meaningful connections; platforms should promote honesty

Chat more and contribute better: An empirical study of a knowledge-sharing community

We analyze whether an informal second channel for communication can improve the efficiency of knowledge transfer in an electronic network of practice. We explore this question by analyzing the effect of chat rooms in the well-known Q&A forum Stack Overflow. We identify the causal effect using a difference-in-differences approach, which exploits a feed functionality that non-selectively pushed all questions from the Q&A into the relevant chat rooms. We report two main findings: First, chat rooms reduced the time until a question in the main Q&A received a satisfactory answer. Second, chat rooms disproportionately benefited new users who asked low-quality questions. Our study has clear managerial implications: A second channel for communication can complement the main channel in online communities to enhance both efficiency and inclusion

Using Crowd-Based Software Repositories to Better Understand Developer-User Interactions

Software development is a complex process. To serve the final software product to the end user, developers need to rely on a variety of software artifacts throughout the development process. The term software repository used to denote only containers of source code such as version control systems; more recent usage has generalized the concept to include a plethora of software development artifact kinds and their related meta-data. Broadly speaking, software repositories include version control systems, technical documentation, issue trackers, question and answer sites, distribution information, etc. The software repositories can be based on a specific project (e.g., bug tracker for Firefox), or be crowd-sourced (e.g., questions and answers on technical Q&A websites). Crowd-based software artifacts are created as by-products of developer-user interactions which are sometimes referred to as communication channels. In this thesis, we investigate three distinct crowd-based software repositories that follow different models of developer-user interactions. We believe through a better understanding of the crowd-based software repositories, we can identify challenges in software development and provide insights to improve the software development process. In our first study, we investigate Stack Overflow. It is the largest collection of programming related questions and answers. On Stack Overflow, developers interact with other developers to create crowd-sourced knowledge in the form of questions and answers. The results of the interactions (i.e., the question threads) become valuable information to the entire developer community. Prior research on Stack Overflow tacitly assume that questions receives answers directly on the platform and no need of interaction is required during the process. Meanwhile, the platform allows attaching comments to questions which forms discussions of the question. Our study found that question discussions occur for 59.2% of questions on Stack Overflow. For discussed and solved questions on Stack Overflow, 80.6% of the questions have the discussion begin before the accepted answer is submitted. The results of our study show the importance and nuances of interactions in technical Q&A. We then study dotfiles, a set of publicly shared user-specific configuration files for software tools. There is a culture of sharing dotfiles within the developer community, where the idea is to learn from other developers’ dotfiles and share your variants. The interaction of dotfiles sharing can be viewed as developers sources information from other developers, adapt the information to their own needs, and share their adaptations back to the community. Our study on dotfiles suggests that is a common practice among developers to share dotfiles where 25.8% of the most stared users on GitHub have a dotfiles repository. We provide a taxonomy of the commonly tracked dotfiles and a qualitative study on the commits in dotfiles repositories. We also leveraged the state-of-the-art time-series clustering technique (K-shape) to identify code churn pattern for dotfile edits. This study is the first step towards understanding the practices of maintaining and sharing dotfiles. Finally, we study app stores, the platforms that distribute software products and contain many non-technical attributes (e.g., ratings and reviews) of software products. Three major stakeholders interacts with each other in app stores: the app store owner who governs the operation of the app store; developers who publish applications on the app store; and users who browse and download applications in the app store. App stores often provide means of interaction between all three actors (e.g., app reviews, store policy) and sometimes interactions with in the same actor (e.g., developer forum). We surveyed existing app stores to extract key features from app store operation. We then labeled a representative set of app store collected by web queries. K-means is applied to the labeled app stores to detect natural groupings of app stores. We observed a diverse set of app stores through the process. Instead of a single model that describes all app stores, fundamentally, our observations show that app stores operates differently. This study provide insights in understanding how app stores can affect software development. In summary, we investigated software repositories containing software artifacts created from different developer-user interactions. These software repositories are essential for software development in providing referencing information (i.e., Stack Overflow), improving development productivity (i.e., dotfiles), and help distributing the software products to end users (i.e., app stores)