Research

We conducted a survey to analyze the trend of online food ordering, seeking to unravel the habits and attitudes of individuals in this ever-evolving landscape. As technology continues to redefine the way we interact with food services, this study becomes a crucial exploration of the preferences and behaviors surrounding online food acquisition. The survey, designed with meticulous objectives, encompasses a broad spectrum of inquiries, ranging from the frequency and types of food ordered to the level of scrutiny exercised during the process. Furthermore, it probes the influence of online food ordering on overall food consumption and delves into the perceived advantages and disadvantages of this modern convenience. The goal is to provide a nuanced and comprehensive understanding of the multifaceted dynamics of online food ordering, shedding light on its impact on the choices and experiences of individual consumers. The subsequent report promises to offer valuable insights into this prevalent trend, contributing to our collective understanding of the evolving relationship between technology and food consumption.

Detailed Report : Insights into Online Food Ordering: A Comprehensive Analysis of Qualitative and Statistical Survey Results (studylib.net)

Short  Report : Survey on Ordering and Eating Food Using Online Food Delivery Applications – IJFMR

This study addresses a critical aspect of software development, focusing on the assessment of software engineering effort, schedule, and expected defects—a concern shared by Project Managers, Customers, Developers, and Systems Analysts. The research underscores the significance of accurate estimation during the early stages of the software development life cycle to prevent schedule and cost overruns. What sets this study apart is its exploration of various estimation models, including Work Break Down Structure, Parametric Estimation, and size-based models, revealing that many existing models fail to converge to actual values and often provide estimates limited to the coding phase. The study recognizes the volatility of requirements, varying complexities, and the impact of defects during different project phases. Notably, the paper introduces simulation models for expected software development effort, demonstrating that a single-point estimate or a range is insufficient due to the considerable variation in expected effort. This research provides unique insights into the complexities of software development estimation, offering valuable considerations for stakeholders aiming to enhance project planning and execution.

Report: 10.13140/RG.2.2.13226.59846

Presented at the 2023 ISBSG IT Confidence Conference on November 10th, the discussion focused on the application of big data in software engineering estimation. Big data, encompassing large and intricate datasets, was highlighted for its potential to significantly enhance estimate accuracy. By identifying patterns and trends, it aids in predicting the effort required for software projects, drawing on historical data from similar endeavors. The presentation emphasized the invaluable role of big data in risk identification, shedding light on factors influencing project effort, such as changing requirements or software complexity. While acknowledging challenges in collecting, storing, and analyzing big data, particularly due to varied sources and formats, the overall sentiment conveyed the potential for big data to improve estimation accuracy, efficiency, and transparency as it becomes more accessible and affordable. The provided pros and cons offer a concise evaluation of the benefits and challenges associated with integrating big data into software engineering estimation practices.

Link to view the ppt : BIG Data for Software Engineering Estimation – ISBSG

Youtube Video : (1) Big Data for Software Engineering Estimation: Pros and Cons – YouTube