• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 29 matches

• 2023
• 
  Faustino Aguilar, Samuel Grayson, Darko Marinov:
  Reproducing and Improving the BugsInPy Dataset. SCAM 2023: 260-264
• 
  Carolin E. Brandt, Danyao Wang, Andy Zaidman:
  When to Let the Developer Guide: Trade-offs Between Open and Guided Test Amplification. SCAM 2023: 231-241
• 
  Andrew Chen, Yanfu Yan, Denys Poshyvanyk:
  ACER: An AST-based Call Graph Generator Framework. SCAM 2023: 254-259
• 
  Amirhossein Deljouyi, Andy Zaidman:
  Generating Understandable Unit Tests through End-to-End Test Scenario Carving. SCAM 2023: 107-118
• 
  Matteo Esposito, Davide Falessi:
  Uncovering the Hidden Risks: The Importance of Predicting Bugginess in Untouched Methods. SCAM 2023: 277-282
• 
  Matteo Esposito, Sergio Moreschini, Valentina Lenarduzzi, David Hästbacka, Davide Falessi:
  Can We Trust the Default Vulnerabilities Severity? SCAM 2023: 265-270
• 
  Philipp Gnoyke, Sandro Schulze, Jacob Krüger:
  On Developing and Improving Tools for Architecture-Smell Tracking in Java Systems. SCAM 2023: 248-253
• 
  Jiangnan Huang, Bin Lin:
  CIGAR: Contrastive Learning for GitHub Action Recommendation. SCAM 2023: 61-71
• 
  Jonathan Katzy, Maliheh Izadi, Arie van Deursen:
  On the Impact of Language Selection for Training and Evaluating Programming Language Models. SCAM 2023: 271-276
• 
  Mohammed Adib Khan, Morteza Noferesti, Naser Ezzati-Jivan:
  PASD: A Performance Analysis Approach Through the Statistical Debugging of Kernel Events. SCAM 2023: 151-161
• 
  Ali Khatami, Andy Zaidman:
  Quality Assurance Awareness in Open Source Software Projects on GitHub. SCAM 2023: 174-185
• 
  Hongyu Kuang, Feng Yang, Long Zhang, Gaigai Tang, Lin Yang:
  Leveraging User-Defined Identifiers for Counterfactual Data Generation in Source Code Vulnerability Detection. SCAM 2023: 143-150
• 
  Luana Almeida Martins, Heitor A. X. Costa, Márcio Ribeiro, Fabio Palomba, Ivan Machado:
  Automating Test-Specific Refactoring Mining: A Mixed-Method Investigation. SCAM 2023: 13-24
• 
  Ahmad Haji Mohammadkhani, Chakkrit Tantithamthavorn, Hadi Hemmati:
  Explaining Transformer-based Code Models: What Do They Learn? When They Do Not Work? SCAM 2023: 96-106
• 
  João Eduardo Montandon, Luciana Lourdes Silva, Cristiano Politowski, Ghizlane El-Boussaidi, Marco Túlio Valente:
  Unboxing Default Argument Breaking Changes in Scikit Learn. SCAM 2023: 209-219
• 
  Ward Muylaert, Johannes Härtel, Coen De Roover:
  Symbolic Execution to Detect Semantic Merge Conflicts. SCAM 2023: 186-197
• 
  Himesh Nandani, Mootez Saad, Tushar Sharma:
  Calibrating Deep Learning-based Code Smell Detection using Human Feedback. SCAM 2023: 37-48
• 
  Ruben Opdebeeck, Jonas Lesy, Ahmed Zerouali, Coen De Roover:
  The Docker Hub Image Inheritance Network: Construction and Empirical Insights. SCAM 2023: 198-208
• 
  Tao Peng, Shixu Chen, Fei Zhu, Junwei Tang, Junping Liu, Xinrong Hu:
  PTLVD:Program Slicing and Transformer-based Line-level Vulnerability Detection System. SCAM 2023: 162-173
• 
  Oton Pinheiro, Lincoln S. Rocha, Windson Viana:
  How They Relate and Leave: Understanding Atoms of Confusion in Open-Source Java Projects. SCAM 2023: 119-130
• 
  David Reid, Audris Mockus:
  Applying the Universal Version History Concept to Help De-Risk Copy-Based Code Reuse. SCAM 2023: 1-12
• 
  Brittany Reid, Christoph Treude, Markus Wagner:
  Using the TypeScript compiler to fix erroneous Node.js snippets. SCAM 2023: 220-230
• 
  Sandro Schulze, Phillipp Engelke, Jacob Krüger:
  Evolutionary Feature Dependencies: Analyzing Feature Co-Changes in C Systems. SCAM 2023: 84-95
• 
  Md. Saeed Siddik, Cor-Paul Bezemer:
  Do Code Quality and Style Issues Differ Across (Non-)Machine Learning Notebooks? Yes! SCAM 2023: 72-83
• 
  Luke Swearngan, Mark Hills:
  Enabling Go Program Analysis in Rascal. SCAM 2023: 242-247
• 
  Gustavo Vale, Eduardo Fernandes, Eduardo Figueiredo, Sven Apel:
  Behind Developer Contributions on Conflicting Merge Scenarios. SCAM 2023: 25-36
• 
  Johannes Villmow, Viola Campos, Jean Petry, Amine Abbad Andaloussi, Adrian Ulges, Barbara Weber:
  How Well Can Masked Language Models Spot Identifiers That Violate Naming Guidelines? SCAM 2023: 131-142
• 
  Cindy Wauters, Jens Van der Plas, Quentin Stiévenart, Coen De Roover:
  Change Pattern Detection for Optimising Incremental Static Analysis. SCAM 2023: 49-60
• 
  Leon Moonen, Christian D. Newman, Alessandra Gorla:
  23rd IEEE International Working Conference on Source Code Analysis and Manipulation, SCAM 2023, Bogotá, Colombia, October 2-3, 2023. IEEE 2023, ISBN 979-8-3503-0506-7 [contents]