43 citations · 129 across the 62 of their papers we have counts for
22 papers · 1 filter
DepRepair: LLM-Based Source-Code Repair for Dependency Breaking Changes
Shenghao Yang, Bo Lu, Yaochen Liu +5
Modern software projects depend on numerous third-party libraries, whose updates often introduce breaking changes. Adapting consumer code to such changes remains labor-intensive an…
AgentTether: Graph-Guided Diagnosis and Runtime Intervention for Reliable LLM Agent Operation
Chenyu Zhao, Shenglin Zhang, Wenwei Gu +5
Large language model (LLM) agents are increasingly used for multi-step, stateful tool-use tasks, yet production reliability remains limited. Unlike static software repair, agent re…
Debugging the Debuggers: Failure-Anchored Structured Recovery for Software Engineering Agents
Chenyu Zhao, Shenglin Zhang, Yihang Lin +7
Software engineering agents are increasingly deployed in evaluable engineering environments, yet post-failure recovery remains costly, manual, and ad hoc. Existing systems expose t…
EvidenT: An Evidence-Preserving Framework for Iterative System-Level Package Repair
Chenyu Zhao, Minghua Ma, Shenglin Zhang +5
Frequent toolchain updates and growing ISA diversity have made system-level software package repair increasingly important. Diagnosing and repairing build failures remains challeng…
A Benchmark for Language Models in Real-World System Building
Weilin Jin, Chenyu Zhao, Zeshun Huang +12
During migration across instruction set architectures (ISAs), software package build repair is a critical task for ensuring the reliability of software deployment and the stability…
Continuous Benchmark Generation for Evaluating Enterprise-scale LLM Agents
Divyanshu Saxena, Rishikesh Maurya, Xiaoxuan Ou +7
The rapid adoption of AI agents across domains has made systematic evaluation crucial for ensuring their usefulness and successful production deployment. Evaluation of AI agents ty…
Triage in Software Engineering: A Systematic Review of Research and Practice
Yongxin Zhao, Shenglin Zhang, Yujia Wu +5
As modern software systems continue to grow in complexity, triage has become a fundamental process in system operations and maintenance. Triage aims to efficiently prioritize, assi…
Can Language Models Go Beyond Coding? Assessing the Capability of Language Models to Build Real-World Systems
Chenyu Zhao, Shenglin Zhang, Zeshun Huang +8
Large language models (LLMs) have shown growing potential in software engineering, yet few benchmarks evaluate their ability to repair software during migration across instruction…
eARCO: Efficient Automated Root Cause Analysis with Prompt Optimization
Drishti Goel, Raghav Magazine, Supriyo Ghosh +5
Root cause analysis (RCA) for incidents in large-scale cloud systems is a complex, knowledge-intensive task that often requires significant manual effort from on-call engineers (OC…
Time Warp: The Gap Between Developers' Ideal vs Actual Workweeks in an AI-Driven Era
Sukrit Kumar, Drishti Goel, Thomas Zimmermann +3
Software developers balance a variety of different tasks in a workweek, yet the allocation of time often differs from what they consider ideal. Identifying and addressing these dev…
Building AI Agents for Autonomous Clouds: Challenges and Design Principles
Manish Shetty, Yinfang Chen, Gagan Somashekar +10
The rapid growth in the use of Large Language Models (LLMs) and AI Agents as part of software development and deployment is revolutionizing the information technology landscape. Wh…
Exploring LLM-based Agents for Root Cause Analysis
Devjeet Roy, Xuchao Zhang, Rashi Bhave +4
The growing complexity of cloud based software systems has resulted in incident management becoming an integral part of the software development lifecycle. Root cause analysis (RCA…
Recommending Root-Cause and Mitigation Steps for Cloud Incidents using Large Language Models
Toufique Ahmed, Supriyo Ghosh, Chetan Bansal +3
Incident management for cloud services is a complex process involving several steps and has a huge impact on both service health and developer productivity. On-call engineers requi…
AutoTSG: Learning and Synthesis for Incident Troubleshooting
Manish Shetty, Chetan Bansal, Sai Pramod Upadhyayula +2
Incident management is a key aspect of operating large-scale cloud services. To aid with faster and efficient resolution of incidents, engineering teams document frequent troublesh…
Nalanda: A Socio-Technical Graph for Building Software Analytics Tools at Enterprise Scale
Chandra Maddila, Suhas Shanbhogue, Apoorva Agrawal +6
Software development is information-dense knowledge work that requires collaboration with other developers and awareness of artifacts such as work items, pull requests, and files.…
DeepAnalyze: Learning to Localize Crashes at Scale
Manish Shetty, Chetan Bansal, Suman Nath +4
Crash localization, an important step in debugging crashes, is challenging when dealing with an extremely large number of diverse applications and platforms and underlying root cau…
SoftNER: Mining Knowledge Graphs From Cloud Incidents
Manish Shetty, Chetan Bansal, Sumit Kumar +2
The move from boxed products to services and the widespread adoption of cloud computing has had a huge impact on the software development life cycle and DevOps processes. Particula…
Nudge: Accelerating Overdue Pull Requests Towards Completion
Chandra Maddila, Sai Surya Upadrasta, Chetan Bansal +3
Pull requests are a key part of the collaborative software development and code review process today. However, pull requests can also slow down the software development process whe…
Search4Code: Code Search Intent Classification Using Weak Supervision
Nikitha Rao, Chetan Bansal, Joe Guan
Developers use search for various tasks such as finding code, documentation, debugging information, etc. In particular, web search is heavily used by developers for finding code ex…
Neural Knowledge Extraction From Cloud Service Incidents
Manish Shetty, Chetan Bansal, Sumit Kumar +3
In the last decade, two paradigm shifts have reshaped the software industry - the move from boxed products to services and the widespread adoption of cloud computing. This has had…
An Empirical Study of Software Exceptions in the Field using Search Logs
Foyzul Hassan, Chetan Bansal, Nachiappan Nagappan +2
Software engineers spend a substantial amount of time using Web search to accomplish software engineering tasks. Such search tasks include finding code snippets, API documentation,…
Analyzing Web Search Behavior for Software Engineering Tasks
Nikitha Rao, Chetan Bansal, Thomas Zimmermann +2
Web search plays an integral role in software engineering (SE) to help with various tasks such as finding documentation, debugging, installation, etc. In this work, we present the…