most citedAI-powered Code Review with LLMs: Early Results

6 citations · 12 across the 4 of their papers we have counts for

collaborators

6 papers

cs.SE2024★ 1 cited

6GSoft: Software for Edge-to-Cloud Continuum

Muhammad Azeem Akbar, Matteo Esposito, Sami Hyrynsalmi +17

In the era of 6G, developing and managing software requires cutting-edge software engineering (SE) theories and practices tailored for such complexity across a vast number of conne…

cs.SE2024★ 2 cited

Experimenting with Multi-Agent Software Development: Towards a Unified Platform

Malik Abdul Sami, Muhammad Waseem, Zeeshan Rasheed +3

Large language models are redefining software engineering by implementing AI-powered techniques throughout the whole software development process, including requirement gathering,…

cs.SE2024★ 6 cited

AI-powered Code Review with LLMs: Early Results

Zeeshan Rasheed, Malik Abdul Sami, Muhammad Waseem +5

In this paper, we present a novel approach to improving software quality and efficiency through a Large Language Model (LLM)-based model designed to review code and identify potent…

cs.SE2024★ 3 cited

Large Language Model Evaluation Via Multi AI Agents: Preliminary results

Zeeshan Rasheed, Muhammad Waseem, Kari Systä +1

As Large Language Models (LLMs) have become integral to both research and daily operations, rigorous evaluation is crucial. This assessment is important not only for individual tas…

cs.SE2019

A Decomposition and Metric-Based Evaluation Framework for Microservices

Davide Taibi, Kari Systä

Migrating from monolithic systems into microservice is a very complex task. Companies are commonly decomposing the monolithic system manually, analyzing dependencies of the monolit…

cs.SE2019

An Empirical Study on Technical Debt in a Finnish SME

Valentina Lenarduzzi, Teemu Orava, Nyyti Saarimäki +2

Objective. In this work, we report the experience of a Finnish SME in managing Technical Debt (TD), investigating the most common types of TD they faced in the past, their causes,…