arXiv subjects

Moumita Asad

Publications and source records attributed to Moumita Asad.

5 recordsLinked to original sources

arXiv2025

Repairing Responsive Layout Failures Using Retrieval Augmented Generation

Responsive websites frequently experience distorted layouts at specific screen sizes, called Responsive Layout Failures (RLFs). Manually repairing these RLFs involves tedious trial-and-error adjustments of HTML elements and CSS properties. In this study, an automated repair approach, leveraging LLM combined with domain-specific knowledge is proposed. The approach is named ReDeFix, a Retrieval-Augmented Generation (RAG)-based solution that utilizes Stack Overflow (SO) discussions to guide LLM on CSS repairs. By augmenting relevant SO knowledge with RLF-specific contexts, ReDeFix creates a prompt that is sent to the LLM to generate CSS patches. Evaluation demonstrates that our approach achieves an 88\% accuracy in repairing RLFs. Furthermore, a study from software engineers reveals that generated repairs produce visually correct layouts while maintaining aesthetics.

cs.SE↗

arXiv2025

Towards Explorative IRBL: Combining Semantic Retrieval with LLM-driven Iterative Code Exploration

Information Retrieval-based Bug Localization (IRBL) aims to identify buggy source files for a given bug report. Traditional and deep learning-based IRBL techniques often suffer from vocabulary mismatch and dependence on project-specific metadata. In contrast, recent Large Language Model (LLM)-based approaches struggle to provide appropriate context to the model: they either restrict analysis to a fixed set of candidate files, overwhelm the model with repository-wide information, or rely on explicit bug report cues to guide context collection. To address these issues, we propose GenLoc, a technique that combines semantic retrieval with LLM-driven code-exploration functions to iteratively analyze the code base and identify buggy files. We evaluate GenLoc on three complementary benchmarks, including large-scale and recent Java datasets as well as the Python based SWE-bench Lite dataset. Results demonstrate that GenLoc substantially outperforms traditional IRBL, deep learning-based approaches and recent LLM-based methods, while also localizing bugs that other techniques fail to detect.

cs.SE↗

arXiv2024

Impact of Fourth Industrial Revolution (4IR) on Small and Medium Enterprises (SMEs) and Employment in Bangladesh: Opportunities and Challenges

The Fourth Industrial Revolution (4IR) is transforming industries and economies worldwide, presenting both opportunities and challenges for Small and Medium Enterprises (SMEs) and employment. This study qualitatively explores the impact of 4IR on the SME sector in Bangladesh. Initially, secondary data sources are reviewed to establish the context and to prepare the questionnaire for primary data collection. Then, the primary data is collected through Key Informant Interviews and Focus Group Discussions with different stakeholders including SME owners, association representatives, and government officials. The study reveals that while most of the participants have only a superficially awareness of 4IR, they view it as a blessing for the SME sector. Despite being in early adoption stages in Bangladesh, SMEs anticipate numerous benefits including enhanced customer experiences, reduced production times, improved quality, etc. Regarding employment, most participants believe that adopting 4IR in the SME sector of Bangladesh will create new job opportunities. However, participants express concern about challenges during the transition to 4IR, including a lack of technical knowledge, financial constraints, inadequate training, safety and security issues, etc. To fully harness 4IR's potential benefits for SMEs in Bangladesh, several key recommendations emerge that include analyzing of the current SME landscape, establishing a collaborative information sharing platform, organizing effective training and workshops, promoting resource sharing, encouraging local innovation, attracting foreign clients, ensuring proper policy implementation and fostering collaboration among government, associations, and academia. By addressing these challenges and implementing the recommended strategies, Bangladesh can effectively embrace the transformative benefits of 4IR, simultaneously improving its SME sector.

cs.CY↗

arXiv2022

Traffic Congestion Prediction Using Machine Learning Techniques

The prediction of traffic congestion can serve a crucial role in making future decisions. Although many studies have been conducted regarding congestion, most of these could not cover all the important factors (e.g., weather conditions). We proposed a prediction model for traffic congestion that can predict congestion based on day, time and several weather data (e.g., temperature, humidity). To evaluate our model, it has been tested against the traffic data of New Delhi. With this model, congestion of a road can be predicted one week ahead with an average RMSE of 1.12. Therefore, this model can be used to take preventive measure beforehand.

cs.LG↗

arXiv2020

Impact on the Productivity of Remotely Working IT Professionals of Bangladesh during the Coronavirus Disease 2019

Similar to the rest of the world, the recent pandemic situation has forced the IT professionals of Bangladesh to adopt remote work. The aim of this study is to find out whether remote work can be continued even after the lockdown is lifted. As work from home may change various productivity related aspects of the employees, i.e., team dynamics and company dynamics, it is necessary to understand the nature of the change during WFH. Conducting a survey, we asked the IT professionals of Bangladesh how they perceive their level of productivity during WFH and how the factors related to productivity have changed. We analyzed the change and identified the areas affected by WFH. We discovered that resource and workspace related issues, emotional well-being of the employees have been hampered the most during WFH. We believe that the findings from this study will help to decide how to resolve those issues and will help to understand whether WFH can be continued even after the lockdown is lifted.

cs.CY↗