ABSTRACT
Low-code software development (LCSD) is an emerging approach to democratize application development for software practitioners from diverse backgrounds. LCSD platforms promote rapid application development with a drag-and-drop interface and minimal programming by hand. As it is a relatively new paradigm, it is vital to study developers' difficulties when adopting LCSD platforms. Software engineers frequently use the online developer forum Stack Overflow (SO) to seek assistance with technical issues. We observe a growing body of LCSD-related posts in SO. This paper presents an empirical study of around 33K SO posts (questions + accepted answers) containing discussions of 38 popular LCSD platforms. We use Topic Modeling to determine the topics discussed in those posts. Additionally, we examine how these topics are spread across the various phases of the agile software development life cycle (SDLC) and which part of LCSD is the most popular and challenging. Our study offers several interesting findings. First, we find 40 LCSD topics that we group into five categories: Application Customization, Database and File Management, Platform Adoption, Platform Maintenance, and Third-party API Integration. Second, while the Application Customization (30%) and Data Storage (25%) topic categories are the most common, inquiries relating to several other categories (e.g., the Platform Adoption topic category) have gained considerable attention in recent years. Third, all topic categories are evolving rapidly, especially during the Covid-19 pandemic. Fourth, the How-type questions are prevalent in all topics, but the What-type and Why-type (i.e., detail information for clarification) questions are more prevalent in the Platform Adoption and Platform Maintenance category. Fifth, LCSD practitioners find topics related to Platform Query the most popular, while topics related to Message Queue and Library Dependency Management as the most difficult to get accepted answers to. Sixth, the Why-type and What-type questions and Agile Maintenance and Deployment phase are the most challenging among practitioners. The findings of this study have implications for all three LCSD stakeholders: LCSD platform vendors, LCSD developers/practitioners, Researchers, and Educators. Researchers and LCSD platform vendors can collaborate to improve different aspects of LCSD, such as better tutorial-based documentation, testing, and DevOps support.
ABSTRACT
The content quality of shared knowledge in Stack Overflow (SO) is crucial in supporting software developers with their programming problems. Thus, SO allows its users to suggest edits to improve the quality of a post (i.e., question and answer). However, existing research shows that many suggested edits in SO are rejected due to undesired contents/formats or violating edit guidelines. Such a scenario frustrates or demotivates users who would like to conduct good-quality edits. Therefore, our research focuses on assisting SO users by offering them suggestions on how to improve their editing of posts. First, we manually investigate 764 (382 questions + 382 answers) rejected edits by rollbacks and produce a catalog of 19 rejection reasons. Second, we extract 15 texts and user-based features to capture those rejection reasons. Third, we develop four machine learning models using those features. Our best-performing model can predict rejected edits with 69.1% precision, 71.2% recall, 70.1% F1-score, and 69.8% overall accuracy. Fourth, we introduce an online tool named EditEx that works with the SO edit system. EditEx can assist users while editing posts by suggesting the potential causes of rejections. We recruit 20 participants to assess the effectiveness of EditEx. Half of the participants (i.e., treatment group) use EditEx and another half (i.e., control group) use the SO standard edit system to edit posts. According to our experiment, EditEx can support SO standard edit system to prevent 49% of rejected edits, including the commonly rejected ones. However, it can prevent 12% rejections even in free-form regular edits. The treatment group finds the potential rejection reasons identified by EditEx influential. Furthermore, the median workload suggesting edits using EditEx is half compared to the SO edit system.
ABSTRACT
Many software developers started to work from home on a short notice during the early periods of COVID-19. A number of previous papers have studied the wellbeing and productivity of software developers during COVID-19. The studies mainly use surveys based on predefined questionnaires. In this paper, we investigate the problems and joys that software developers experienced during the early months of COVID-19 by analyzing their discussions in online forum devRant, where discussions can be open and not bound by predefined survey questionnaires. The devRant platform is designed for developers to share their joys and frustrations of life. We manually analyze 825 devRant posts between January and April 12, 2020 that developers created to discuss their situation during COVID-19. WHO declared COVID-19 as pandemic on March 11, 2020. As such, our data offers us insights in the early months of COVID-19. We manually label each post along two dimensions: the topics of the discussion and the expressed sentiment polarity (positive, negative, neutral). We observed 19 topics that we group into six categories: Workplace & Professional aspects, Personal & Family well-being, Technical Aspects, Lockdown preparedness, Financial concerns, and Societal and Educational concerns. Around 49% of the discussions are negative and 26% are positive. We find evidence of developers' struggles with lack of documentation to work remotely and with their loneliness while working from home. We find stories of their job loss with little or no savings to fallback to. The analysis of developer discussions in the early months of a pandemic will help various stakeholders (e.g., software companies) make important decision early to alleviate developer problems if such a pandemic or similar emergency situation occurs in near future. Software engineering research can make further efforts to develop automated tools for remote work (e.g., automated documentation).
ABSTRACT
Pancreatic sarcoidosis is one of the variant of systemic sarcoidosis which is extremely rare in literature and opined as an enigma. Hence, its diagnosis is very challenging as its presentation mimics pancreatic carcinoma. In view of a better understanding, we are presenting a case of pancreatic sarcoidosis to emphasize the above. To clearly distinguish sarcoidosis from malignancy, repeated computed tomography scans, Positron emission tomography scans, fine needle aspiration cytology, endoscopic retrograde cholangio-pancreatography supplemented with histology and relevant blood tests proved it to be a pancreatic sarcoidosis then a malignancy. Over the course, concrete evidence was divulged from lymph node biopsy and histology in clinching the diagnosis which later transformed into a malignancy. Therefore, we concluded it is a rare variant of pancreatic sarcoidosis and careful serial investigations include repeated imaging, histology and blood tests are essential to establish and most importantly differentiate the diagnosis. HOW TO CITE THIS ARTICLE: Khangura T, Uddin G, Davies A, Keating J. A Rare Variant of Pancreatic Sarcoidosis: Diagnostic Challenge. Euroasian J Hepato-Gastroenterol 2015;5(2):118-121.
