arXiv subjects

Teerath Das

Publications and source records attributed to Teerath Das.

6 recordsLinked to original sources

arXiv2025

A Systematic Mapping Study on Risks and Vulnerabilities in Software Containers

Software containers are widely adopted for developing and deploying software applications. Despite their popularity, major security concerns arise during container development and deployment. Software Engineering (SE) research literature reveals a lack of reviewed, aggregated, and organized knowledge of risks, vulnerabilities, security practices, and tools in container-based systems development and deployment. Therefore, we conducted a Systematic Mapping Study (SMS) based on 129 selected primary studies to explore and organize existing knowledge on security issues in software container systems. Data from the primary studies enabled us to identify critical risks and vulnerabilities across the container life-cycle and categorize them using a novel taxonomy. Additionally, the findings highlight the causes and implications and provide a list of mitigation techniques to overcome these risks and vulnerabilities. Furthermore, we provide an aggregation of security practices and tools that can help support and improve the overall security of container systems. This study offers critical insights into the current landscape of security issues within software container systems. Our analysis highlights the need for future SE research to focus on security enhancement practices that strengthen container systems and develop effective mitigation strategies to comprehensively address existing risks and vulnerabilities.

cs.SE↗

arXiv2025

Runtime Composition in Dynamic System of Systems: A Systematic Review of Challenges, Solutions, Tools, and Evaluation Methods

Context: Modern Systems of Systems (SoSs) increasingly operate in dynamic environments (e.g., smart cities, autonomous vehicles) where runtime composition -- the on-the-fly discovery, integration, and coordination of constituent systems (CSs)--is crucial for adaptability. Despite growing interest, the literature lacks a cohesive synthesis of runtime composition in dynamic SoSs. Objective: This study synthesizes research on runtime composition in dynamic SoSs and identifies core challenges, solution strategies, supporting tools, and evaluation methods. Methods: We conducted a Systematic Literature Review (SLR), screening 1,774 studies published between 2019 and 2024 and selecting 80 primary studies for thematic analysis (TA). Results: Challenges fall into four categories: modeling and analysis, resilient operations, system orchestration, and heterogeneity of CSs. Solutions span seven areas: co-simulation and digital twins, semantic ontologies, integration frameworks, adaptive architectures, middleware, formal methods, and AI-driven resilience. Service-oriented frameworks for composition and integration dominate tooling, while simulation platforms support evaluation. Interoperability across tools, limited cross-toolchain workflows, and the absence of standardized benchmarks remain key gaps. Evaluation approaches include simulation-based, implementation-driven, and human-centered studies, which have been applied in domains such as smart cities, healthcare, defense, and industrial automation. Conclusions: The synthesis reveals tensions, including autonomy versus coordination, the modeling-reality gap, and socio-technical integration. It calls for standardized evaluation metrics, scalable decentralized architectures, and cross-domain frameworks. The analysis aims to guide researchers and practitioners in developing and implementing dynamically composable SoSs.

cs.SE↗

arXiv2025

Towards Shift-Up: A Framework and a Prestudy on High-Value Activities in GenAI Native Software Development

Generative AI (GenAI) has significantly influenced software engineering. Associated tools have created a shift in software engineering, where specialized agents, based on user-provided prompts, are replacing human developers. In this paper, we propose a framework for GenAI native development that we call \textit{shift-up}, which helps software teams focus on high-value work while being supported by GenAI. Furthermore, we also present a preliminary study testing these ideas with current GenAI tools. Towards the end of the paper, we propose future research goals to study shift-up in more detail.

cs.SE↗

arXiv2025

Containers as the Quantum Leap in Software Development

The goal of the project QLEAP (2022-24), funded by Business Finland and participating organizations, was to study using containers as elements of architecture design. Such systems include containerized AI systems, using containers in a hybrid setup (public/hybrid/private clouds), and related security concerns. The consortium consists of four companies that represent different concerns over using containers (Bittium, M-Files, Solita/ADE Insights, Vaadin) and one research organization (University of Jyv\"askyl\"a). In addition, it has received support from two Veturi companies - Nokia and Tietoevry - who have also participated in steering the project. Moreover, the SW4E ecosystem has participated in the project. This document gathers the key lessons learned from the project.

cs.SE↗

arXiv2023

Issues and Their Causes in WebAssembly Applications: An Empirical Study

WebAssembly (Wasm) is a binary instruction format designed for secure and efficient execution within sandboxed environments -- predominantly web apps and browsers -- to facilitate performance, security, and flexibility of web programming languages. In recent years, Wasm has gained significant attention from the academic research community and industrial development projects to engineer high-performance web applications. Despite the offered benefits, developers encounter a multitude of issues rooted in Wasm (e.g., faults, errors, failures) and are often unaware of their root causes that impact the development of web applications. To this end, we conducted an empirical study that mines and documents practitioners' knowledge expressed as 385 issues from 12 open-source Wasm projects deployed on GitHub and 354 question-answer posts via Stack Overflow. Overall, we identified 120 types of issues, which were categorized into 19 subcategories and 9 categories to create a taxonomical classification of issues encountered in Wasm-based applications. Furthermore, root cause analysis of the issues helped us identify 278 types of causes, which have been categorized into 29 subcategories and 10 categories as a taxonomy of causes. Our study led to first-of-its-kind taxonomies of the issues faced by developers and their underlying causes in Wasm-based applications. The issue-cause taxonomies -- identified from GitHub and SO, offering empirically derived guidelines -- can guide researchers and practitioners to design, develop, and refactor Wasm-based applications.

cs.SE↗

arXiv2023

ChatGPT as a Software Development Bot: A Project-based Study

Artificial Intelligence has demonstrated its significance in software engineering through notable improvements in productivity, accuracy, collaboration, and learning outcomes. This study examines the impact of generative AI tools, specifically ChatGPT, on the software development experiences of undergraduate students. Over a three-month project with seven students, ChatGPT was used as a support tool. The research focused on assessing ChatGPT's effectiveness, benefits, limitations, and its influence on learning. Results showed that ChatGPT significantly addresses skill gaps in software development education, enhancing efficiency, accuracy, and collaboration. It also improved participants' fundamental understanding and soft skills. The study highlights the importance of incorporating AI tools like ChatGPT in education to bridge skill gaps and increase productivity, but stresses the need for a balanced approach to technology use. Future research should focus on optimizing ChatGPT's application in various development contexts to maximize learning and address specific challenges.

cs.SE↗