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Abbas Heydarnoori

Publications and source records attributed to Abbas Heydarnoori.

22 records · Page 2Linked to original sources

Improving Quality of a Post's Set of Answers in Stack Overflow

Community Question Answering platforms such as Stack Overflow help a wide range of users solve their challenges online. As the popularity of these communities has grown over the years, both the number of members and posts have escalated. Also, due to the diverse backgrounds, skills, expertise, and viewpoints of users, each question may obtain more than one answers. Therefore, the focus has changed toward producing posts that have a set of answers more valuable for the community as a whole, not just one accepted-answer aimed at satisfying only the question-asker. Same as every universal community, a large number of low-quality posts on Stack Overflow require improvement. We call these posts deficient and define them as posts with questions that either have no answer yet or can be improved by other ones. In this paper, we propose an approach to automate the identification process of such posts and boost their set of answers, utilizing the help of related experts. With the help of 60 participants, we trained a classification model to identify deficient posts by investigating the relationship between characteristics of 3075 questions posted on Stack Overflow and their need for better answers set. Then, we developed an Eclipse plugin named SOPI and integrated the prediction model in the plugin to link these deficient posts to related developers and help them improve the answer set. We evaluated both the functionality of our plugin and the impact of answers submitted to Stack Overflow with the help of 10 and 15 expert industrial developers, respectively. Our results indicate that decision trees, specifically J48, predicts a deficient question better than the other methods with 0.945 precision and 0.903 recall. We conclude that not only our plugin helps programmers contribute more easily to Stack Overflow, but also it improves the quality of answers.

cs.SE↗

An Analysis of Python's Topics, Trends, and Technologies Through Mining Stack Overflow Discussions

Python is a popular, widely used, and general-purpose programming language. In spite of its ever-growing community, researchers have not performed much analysis on Python's topics, trends, and technologies which provides insights for developers about Python community trends and main issues. In this article, we examine the main topics related to this language being discussed by developers on one of the most popular Q\&A websites, Stack Overflow, as well as temporal trends through mining 2461876 posts. To be more useful for the software engineers, we study what Python provides as the alternative to popular technologies offered by common programming languages like Java. Our results indicate that discussions about Python standard features, web programming, and scientific programming. Programming in areas such as mathematics, data science, statistics, machine learning, natural language processing (NLP), and so forth. are the most popular areas in the Python community. At the same time, areas related to scientific programming are steadily receiving more attention from the Python developers.

cs.SE↗

Generating Code Summaries Using the Power of the Crowd

One of the first steps to perform most of the software maintenance activities, such as updating features or fixing bugs, is to have a relatively good understanding of the program's source code which is often written by other developers. A code summary is a description about a program's entities (e.g., its methods) which helps developers have a better comprehension of the code in a shorter period of time. However, generating code summaries can be a challenging task. To mitigate this problem, in this article, we introduce CrowdSummarizer, a code summarization platform that benefits from the concepts of crowdsourcing, gamification, and natural language processing to automatically generate a high level summary for the methods of a Java program. We have implemented CrowdSummarizer as an Eclipse plugin together with a web-based code summarization game that can be played by the crowd. The results of two empirical studies that evaluate the applicability of the approach and the quality of generated summaries indicate that CrowdSummarizer is effective in generating quality results.

cs.SE↗

Migrating to Cloud-Native Architectures Using Microservices: An Experience Report

Migration to the cloud has been a popular topic in industry and academia in recent years. Despite many benefits that the cloud presents, such as high availability and scalability, most of the on-premise application architectures are not ready to fully exploit the benefits of this environment, and adapting them to this environment is a non-trivial task. Microservices have appeared recently as novel architectural styles that are native to the cloud. These cloud-native architectures can facilitate migrating on-premise architectures to fully benefit from the cloud environments because non-functional attributes, like scalability, are inherent in this style. The existing approaches on cloud migration does not mostly consider cloud-native architectures as their first-class citizens. As a result, the final product may not meet its primary drivers for migration. In this paper, we intend to report our experience and lessons learned in an ongoing project on migrating a monolithic on-premise software architecture to microservices. We concluded that microservices is not a one-fit-all solution as it introduces new complexities to the system, and many factors, such as distribution complexities, should be considered before adopting this style. However, if adopted in a context that needs high flexibility in terms of scalability and availability, it can deliver its promised benefits.

cs.SE↗