9 citations · 48 across the 29 of their papers we have counts for
32 papers
Where Did the Repair First Go Wrong? Localizing the Origins of Silent Failures in Agentic Vulnerability Repair
Wenji Bai, Muhammad Waseem, Zeeshan Rasheed +2
Localizing where an LLM-based agent first fails to uphold security during a repair can show which stage of its workflow needs an additional safeguard. This is difficult for silent…
Checkpoints Are Not Enough: Trust Calibration in CoSLR, a Human-AI System for Systematic Literature Reviews
MD Aidul Islam, Malik Abdul Sami, Muhammad Waseem +4
Systematic Literature Reviews (SLRs) are essential for evidence-based research but remain time-consuming, requiring researchers to manage large volumes of publications across plann…
When Passing Tests Hides Vulnerabilities: An Empirical Study of Silent Failures in Agentic Systems
Wenji Bai, Muhammad Waseem, Zeeshan Rasheed +2
LLM-based agents for automated code repair have received significant attention in recent years from both research and software engineering practice perspectives. However, limited a…
Agentic Frameworks for Reasoning Tasks: An Empirical Study
Zeeshan Rasheed, Abdul Malik Sami, Muhammad Waseem +3
Recent advances in agentic frameworks have enabled AI agents to perform complex reasoning and decision-making. However, evidence comparing their reasoning performance, efficiency,…
LLM-Based Multi-Agent Systems for Code Generation: A Multi-Vocal Literature Review
Zeeshan Rasheeda, Muhammad Waseema, Kai-Kristian Kemella +2
Large Language Models (LLMs) have enabled multi-agent systems to perform autonomous code generation for complex tasks. Despite the recent growth in research and industrial applicat…
Adopt-an-AI-Researcher: Bootstrapping Industry-Academia Collaboration to Identify and Prioritise Generative AI Use Cases
Malik Abdul Sami, Zeeshan Rasheed, Meri Olenius +4
Organisations want to use generative AI (GenAI), but many do not know where to begin. Researchers understand AI capabilities, while employees understand their organisation's proces…
From Specification to Service: Accelerating API-First Development Using Multi-Agent Systems
Saurabh Chauhan, Zeeshan Rasheed, Malik Abdul Sami +6
This paper presents a system that uses Large Language Models (LLMs)-based agents to automate the API-first development of RESTful microservices. This system helps to create an Open…
VAPU: System for Autonomous Legacy Code Modernization
Valtteri Ala-Salmi, Zeeshan Rasheed, Abdul Malik Sami +5
In this study, we present a solution for the modernization of legacy applications, an area of code generation where LLM-based multi-agent systems are proving essential for complex…
LLM-based Multi-Agent System for Intelligent Refactoring of Haskell Code
Shahbaz Siddeeq, Muhammad Waseem, Zeeshan Rasheed +7
Refactoring is a constant activity in software development and maintenance. Scale and maintain software systems are based on code refactoring. However, this process is still labor…
LLM-Generated Microservice Implementations from RESTful API Definitions
Saurabh Chauhan, Zeeshan Rasheed, Abdul Malik Sami +4
The growing need for scalable, maintainable, and fast-deploying systems has made microservice architecture widely popular in software development. This paper presents a system that…
Distributed Approach to Haskell Based Applications Refactoring with LLMs Based Multi-Agent Systems
Shahbaz Siddeeq, Zeeshan Rasheed, Malik Abdul Sami +6
We present a large language models (LLMs) based multi-agent system to automate the refactoring of Haskell codebases. The multi-agent system consists of specialized agents performin…
Autonomous Legacy Web Application Upgrades Using a Multi-Agent System
Valtteri Ala-Salmi, Zeeshan Rasheed, Abdul Malik Sami +6
The use of Large Language Models (LLMs) for autonomous code generation is gaining attention in emerging technologies. As LLM capabilities expand, they offer new possibilities such…
Large Language Models for Code Generation: The Practitioners Perspective
Zeeshan Rasheed, Muhammad Waseem, Kai Kristian Kemell +5
Large Language Models (LLMs) have emerged as coding assistants, capable of generating source code from natural language prompts. With the increasing adoption of LLMs in software de…
TimeLess: A Vision for the Next Generation of Software Development
Zeeshan Rasheed, Malik Abdul Sami, Jussi Rasku +16
Present-day software development faces three major challenges: complexity, time consumption, and high costs. Developing large software systems often requires battalions of teams an…
A System for Critical Facility and Resource Optimization in Disaster Management and Planning
Emmanuel Tung, Ali Mostafavi, Maoxu Li +3
Disruptions to medical infrastructure during disasters pose significant risks to critically ill patients with advanced chronic kidney disease or end-stage renal disease. To enhance…
Back to Bayesics: Uncovering Human Mobility Distributions and Anomalies with an Integrated Statistical and Neural Framework
Minxuan Duan, Yinlong Qian, Lingyi Zhao +4
Existing methods for anomaly detection often fall short due to their inability to handle the complexity, heterogeneity, and high dimensionality inherent in real-world mobility data…
Uncertainty-aware Human Mobility Modeling and Anomaly Detection
Haomin Wen, Shurui Cao, Zeeshan Rasheed +2
Given the temporal GPS coordinates from a large set of human agents, how can we model their mobility behavior toward effective anomaly (e.g. bad-actor or malicious behavior) detect…
NUMOSIM: A Synthetic Mobility Dataset with Anomaly Detection Benchmarks
Chris Stanford, Suman Adari, Xishun Liao +10
Collecting real-world mobility data is challenging. It is often fraught with privacy concerns, logistical difficulties, and inherent biases. Moreover, accurately annotating anomali…
AI based Multiagent Approach for Requirements Elicitation and Analysis
Malik Abdul Sami, Muhammad Waseem, Zheying Zhang +3
Requirements Engineering (RE) plays a pivotal role in software development, encompassing tasks such as requirements elicitation, analysis, specification, and change management. Des…
A Tool for Test Case Scenarios Generation Using Large Language Models
Abdul Malik Sami, Zeeshan Rasheed, Muhammad Waseem +3
Large Language Models (LLMs) are widely used in Software Engineering (SE) for various tasks, including generating code, designing and documenting software, adding code comments, re…
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,…
Prioritizing Software Requirements Using Large Language Models
Malik Abdul Sami, Zeeshan Rasheed, Muhammad Waseem +3
Large Language Models (LLMs) are revolutionizing Software Engineering (SE) by introducing innovative methods for tasks such as collecting requirements, designing software, generati…
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…
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…