20 citations · 101 across the 31 of their papers we have counts for
32 papers
S3C2 Summit 2025-09: Industry Secure Supply Chain Summit
Md Atiqur Rahman, Yasemin Acar, Michel Cucker +5
Today's digital ecosystem relies heavily on software supply chains, which enable developers to reuse code and ship software at scale. However, a single vulnerable component can jeo…
S3C2 Summit 2025-07: Government Secure Supply Chain Summit
Sivana Hamer, Pat Morrison, William Enck +6
Software supply chains, while providing immense economic and software development value, are only as strong as their weakest link. Over the past several years, there has been an ex…
Speed at the Cost of Quality: How Cursor AI Increases Short-Term Velocity and Long-Term Complexity in Open-Source Projects
Hao He, Courtney Miller, Shyam Agarwal +2
Large language models (LLMs) have demonstrated the promise to revolutionize the field of software engineering. Among other things, LLM agents are rapidly gaining momentum in softwa…
FairSense: Long-Term Fairness Analysis of ML-Enabled Systems
Yining She, Sumon Biswas, Christian Kästner +1
Algorithmic fairness of machine learning (ML) models has raised significant concern in the recent years. Many testing, verification, and bias mitigation techniques have been propos…
Beyond the Comfort Zone: Emerging Solutions to Overcome Challenges in Integrating LLMs into Software Products
Nadia Nahar, Christian Kästner, Jenna Butler +3
Large Language Models (LLMs) are increasingly embedded into software products across diverse industries, enhancing user experiences, but at the same time introducing numerous chall…
S3C2 Summit 2024-03: Industry Secure Supply Chain Summit
Greg Tystahl, Yasemin Acar, Michel Cukier +5
Supply chain security has become a very important vector to consider when defending against adversary attacks. Due to this, more and more developers are keen on improving their sup…
S3C2 Summit 2023-06: Government Secure Supply Chain Summit
William Enck, Yasemin Acar, Michel Cukier +3
Recent years have shown increased cyber attacks targeting less secure elements in the software supply chain and causing fatal damage to businesses and organizations. Past well-know…
S3C2 Summit 2023-02: Industry Secure Supply Chain Summit
Trevor Dunlap, Yasemin Acar, Michel Cucker +4
Recent years have shown increased cyber attacks targeting less secure elements in the software supply chain and causing fatal damage to businesses and organizations. Past well-know…
S3C2 Summit 2202-09: Industry Secure Suppy Chain Summit
Mindy Tran, Yasemin Acar, Michel Cucker +4
Recent years have shown increased cyber attacks targeting less secure elements in the software supply chain and causing fatal damage to businesses and organizations. Past well-know…
A Meta-Summary of Challenges in Building Products with ML Components -- Collecting Experiences from 4758+ Practitioners
Nadia Nahar, Haoran Zhang, Grace Lewis +2
Incorporating machine learning (ML) components into software products raises new software-engineering challenges and exacerbates existing challenges. Many researchers have invested…
MLTEing Models: Negotiating, Evaluating, and Documenting Model and System Qualities
Katherine R. Maffey, Kyle Dotterrer, Jennifer Niemann +3
Many organizations seek to ensure that machine learning (ML) and artificial intelligence (AI) systems work as intended in production but currently do not have a cohesive methodolog…
Data Leakage in Notebooks: Static Detection and Better Processes
Chenyang Yang, Rachel A Brower-Sinning, Grace A. Lewis +1
Data science pipelines to train and evaluate models with machine learning may contain bugs just like any other code. Leakage between training and test data can lead to overestimati…
Collaboration Challenges in Building ML-Enabled Systems: Communication, Documentation, Engineering, and Process
Nadia Nahar, Shurui Zhou, Grace Lewis +1
The introduction of machine learning (ML) components in software projects has created the need for software engineers to collaborate with data scientists and other specialists. Whi…
Feature Interactions on Steroids: On the Composition of ML Models
Christian Kästner, Eunsuk Kang, Sven Apel
The lack of specifications is a key difference between traditional software engineering and machine learning. We discuss how it drastically impacts how we think about divide-and-co…
Containing Malicious Package Updates in npm with a Lightweight Permission System
Gabriel Ferreira, Limin Jia, Joshua Sunshine +1
The large amount of third-party packages available in fast-moving software ecosystems, such as Node.js/npm, enables attackers to compromise applications by pushing malicious update…
Understanding the Nature of System-Related Issues in Machine Learning Frameworks: An Exploratory Study
Yang Ren, Gregory Gay, Christian Kästner +1
Modern systems are built using development frameworks. These frameworks have a major impact on how the resulting system executes, how configurations are managed, how it is tested,…
Efficiently Finding Higher-Order Mutants
Chu-Pan Wong, Jens Meinicke, Leo Chen +3
Higher-order mutation has the potential for improving major drawbacks of traditional first-order mutation, such as by simulating more realistic faults or improving test optimizatio…
Teaching Software Engineering for AI-Enabled Systems
Christian Kästner, Eunsuk Kang
Software engineers have significant expertise to offer when building intelligent systems, drawing on decades of experience and methods for building systems that are scalable, respo…
How Do Code Changes Evolve in Different Platforms? A Mining-based Investigation
Markos Viggiato, Johnatan Oliveira, Eduardo Figueiredo +2
Code changes are performed differently in the mobile and non-mobile platforms. Prior work has investigated the differences in specific platforms. However, we still lack a deeper un…
Design Dimensions for Software Certification: A Grounded Analysis
Gabriel Ferreira, Christian Kästner, Joshua Sunshine +2
In many domains, software systems cannot be deployed until authorities judge them fit for use in an intended operating environment. Certification standards and processes have been…
ConfigCrusher: Towards White-Box Performance Analysis for Configurable Systems
Miguel Velez, Pooyan Jamshidi, Florian Sattler +3
Stakeholders of configurable systems are often interested in knowing how configuration options influence the performance of a system to facilitate, for example, the debugging and o…
Machine Learning Meets Quantitative Planning: Enabling Self-Adaptation in Autonomous Robots
Pooyan Jamshidi, Javier Cámara, Bradley Schmerl +2
Modern cyber-physical systems (e.g., robotics systems) are typically composed of physical and software components, the characteristics of which are likely to change over time. Assu…
Faster Variational Execution with Transparent Bytecode Transformation
Chu-Pan Wong, Jens Meinicke, Lukas Lazarek +1
Variational execution is a novel dynamic analysis technique for exploring highly configurable systems and accurately tracking information flow. It is able to efficiently analyze ma…
Understanding Differences among Executions with Variational Traces
Jens Meinicke, Chu-Pan Wong, Christian Kästner +1
One of the main challenges of debugging is to understand why the program fails for certain inputs but succeeds for others. This becomes especially difficult if the fault is caused…