ICSE 2024
Fri 12 - Sun 21 April 2024 Lisbon, Portugal

Accepted Papers

Title
ACAV: A Framework for Automatic Causality Analysis in Autonomous Vehicle Accident Recordings
Research Track
Pre-print
A Comprehensive Study of Learning-based Android Malware Detectors under Challenging Environments
Research Track
A First Look at the Inheritance-Induced Redundant Test Execution
Research Track
A Framework For Inferring Properties of User-Defined Functions
Research Track
A Large-Scale Survey on the Usability of AI Programming Assistants: Successes and Challenges
Research Track
Analyzing and Debugging Normative Requirements via Satisfiability CheckingACM SIGSOFT Distinguished Paper Award
Research Track
An Empirical Study of Data Disruption by Ransomware Attacks
Research Track
An Empirical Study on Low GPU Utilization of Deep Learning Jobs
Research Track
An Empirical Study on Noisy Label Learning for Program Understanding
Research Track
An Empirical Study on Oculus Virtual Reality Applications: Security and Privacy Perspectives
Research Track
An Exploratory Investigation of Log Anomalies in Unmanned Aerial Vehicles
Research Track
Are Prompt Engineering and TODO Comments Friends or Foes? An Evaluation on GitHub Copilot
Research Track
Are We There Yet? Unraveling the State-of-the-Art Smart Contract Fuzzers
Research Track
Are Your Requests Your True Needs? Checking Excessive Data Collection in VPA App
Research Track
A Study on the Pythonic Functional Constructs' Understandability
Research Track
Pre-print
A Theory of Scientific Programming Efficacy
Research Track
Attention! Your Copied Data is Under Monitoring: A Systematic Study of Clipboard Usage in Android AppsACM SIGSOFT Distinguished Paper Award
Research Track
A User-centered Security Evaluation of Copilot
Research Track
Automated Program Repair, What Is It Good For? Not Absolutely Nothing!
Research Track
Pre-print
Automatically Detecting Reflow Accessibility Issues in Responsive Web Pages
Research Track
Automatic Semantic Augmentation of Language Model Prompts (for Code Summarization)
Research Track
DOI Pre-print
Barriers for Students During Code Change Comprehension
Research Track
BinaryAI: Binary Software Composition Analysis via Intelligent Binary Source Code Matching
Research Track
BinAug: Enhancing Binary Similarity Analysis with Low-Cost Input Repairing
Research Track
Block-based Programming for Two-Armed Robots: A Comparative Study
Research Track
DOI Pre-print Media Attached
BOMs Away! Inside the Minds of Stakeholders: A Comprehensive Study of Bills of Materials for Software Systems
Research Track
Pre-print
Breaking the Flow: A Study of Interruptions During Software Engineering ActivitiesACM SIGSOFT Distinguished Paper Award
Research Track
Causal Relationships and Programming Outcomes: A Transcranial Magnetic Stimulation ExperimentACM SIGSOFT Distinguished Paper Award
Research Track
CERT: Finding Performance Issues in Database Systems Through the Lens of Cardinality Estimation
Research Track
Pre-print
Characterizing Software Maintenance Meetings: Information Shared, Discussion Outcomes, and Information Captured
Research Track
ChatGPT Incorrectness Detection in Software Reviews
Research Track
ChatGPT-Resistant Screening Instrument for Identifying Non-Programmers
Research Track
CIT4DNN: Generating Diverse and Rare Inputs for Neural Networks Using Latent Space Combinatorial Testing
Research Track
Cneps: A Precise Approach for Examining Dependencies among Third-Party C/C++ Open-Source Components
Research Track
Coca: Improving and Explaining Graph Neural Network-Based Vulnerability Detection Systems
Research Track
Co-Creation in Fully Remote Software Teams
Research Track
CoderEval: A Benchmark of Pragmatic Code Generation with Generative Pre-trained Models
Research Track
Code Search is All You Need? Improving Code Suggestions with Code SearchACM SIGSOFT Distinguished Paper Award
Research Track
Combining Structured Static Code Information and Dynamic Symbolic Traces for Software Vulnerability Prediction
Research Track
Compiler-directed Migrating API Callsite of Client Code
Research Track
Comprehensive Semantic Repair of Obsolete GUI Test Scripts for Mobile Applications
Research Track
Concrete Constraint Guided Symbolic Execution
Research Track
Constraint Based Program Repair for Persistent Memory Bugs
Research Track
Context-Aware Name Recommendation for Field Renaming
Research Track
CrashTranslator: Automatically Reproducing Mobile Application Crashes Directly from Stack Trace
Research Track
Cross-Inlining Binary Function Similarity Detection
Research Track
DOI Pre-print
Crossover in Parametric Fuzzing
Research Track
CSChecker: Revisiting GDPR and CCPA Compliance of Cookie Banners on the Web
Research Track
Curiosity-Driven Testing for Sequential Decision-Making Process
Research Track
Data-Driven Evidence-Based Syntactic Sugar Design
Research Track
Dataflow Analysis-Inspired Deep Learning for Efficient Vulnerability Detection
Research Track
Pre-print
Deep Combination of CDCL(T) and Local Search for Satisfiability Modulo Non-Linear Integer Arithmetic Theory
Research Track
Deep Learning or Classical Machine Learning? An Empirical Study on Log-Based Anomaly Detection
Research Track
DeepLSH: Deep Locality-Sensitive Hash Learning for Fast and Efficient Near-Duplicate Crash Report Detection
Research Track
Deeply Reinforcing Android GUI Testing with Deep Reinforcement Learning
Research Track
DeepSample: DNN sampling-based testing for operational accuracy assessment
Research Track
DEMISTIFY: Identifying On-device Machine Learning Models Stealing and Reuse Vulnerabilities in Mobile Apps
Research Track
Demystifying and Detecting Misuses of Deep Learning APIs
Research Track
Demystifying Compiler Unstable Feature Usage and Impacts in the Rust Ecosystem
Research Track
DOI Pre-print Media Attached
Detecting Automatic Software Plagiarism via Token Sequence Normalization
Research Track
DOI Pre-print
Detecting Logic Bugs in Graph Database Management Systems via Injective and Surjective Graph Pattern Transformation
Research Track
Development in times of hype: How freelancers explore Generative AI?
Research Track
DivLog: Log Parsing with Prompt Enhanced In-Context Learning
Research Track
Do Automatic Test Generation Tools Generate Flaky Tests?
Research Track
Pre-print
DocFlow: Extracting Taint Specifications from Software Documentation
Research Track
Domain Knowledge Matters: Improving Prompts with Fix Templates for Repairing Python Type Errors
Research Track
DSFM: Enhancing Functional Code Clone Detection with Deep Subtree Interactions
Research Track
ECFuzz: Effective Configuration Fuzzing for Large-Scale Systems
Research Track
DOI
EDEFuzz: A Web API Fuzzer for Excessive Data ExposuresACM SIGSOFT Distinguished Paper Award
Research Track
Efficiently Trimming the Fat: Streamlining Software Dependencies with Java Reflection and Dependency Analysis
Research Track
EGFE: End-to-end Grouping of Fragmented Elements in UI Designs with Multimodal Learning
Research Track
Empirical Analysis of Vulnerabilities Life Cycle in Golang Ecosystem
Research Track
Empirical Study of the Docker Smells Impact on the Image Size
Research Track
Enabling Runtime Verification of Causal Discovery Algorithms with Automated Conditional Independence Reasoning
Research Track
Enhancing Exploratory Testing by Large Language Model and Knowledge Graph
Research Track
Evaluating Code Summarization Techniques: A New Metric and an Empirical Characterization
Research Track
Evaluating Large Language Models in Class-Level Code Generation
Research Track
Pre-print
Exploiting Library Vulnerability via Migration Based Automating Test Generation
Research Track
Exploring Experiences with Automated Program Repair in Practice
Research Track
Exploring the Potential of ChatGPT in Automated Code Refinement: An Empirical Study
Research Track
Extrapolating Coverage Rate in Greybox Fuzzing
Research Track
FAIR: Flow Type-Aware Pre-Training of Compiler Intermediate RepresentationsACM SIGSOFT Distinguished Paper Award
Research Track
Fairness Improvement with Multiple Protected Attributes: How Far Are We?
Research Track
Pre-print
Fast Deterministic Black-box Context-free Grammar Inference
Research Track
Pre-print Media Attached
Finding XPath Bugs in XML Document Processors via Differential Testing
Research Track
Fine-grained, accurate and scalable source differencing
Research Track
Fine-SE: Integrating Semantic Features and Expert Features for Software Effort Estimation
Research Track
FlakeSync: Automatically Repairing Async Flaky Tests
Research Track
FlashSyn: Flash Loan Attack Synthesis via Counter Example Driven Approximation
Research Track
Fuzz4All: Universal Fuzzing with Large Language Models
Research Track
Pre-print
FuzzInMem: Fuzzing Programs via In-memory Structures
Research Track
FuzzSlice: Pruning False Positives in Static Analysis Warnings through Function-Level Fuzzing
Research Track
DOI Pre-print
GenderMag Improves Discoverability in the Field, Especially for WomenACM SIGSOFT Distinguished Paper Award
Research Track
Generating REST API Specifications through Static Analysis
Research Track
GPTScan: Detecting Logic Vulnerabilities in Smart Contracts by Combining GPT with Program Analysis
Research Track
GrammarT5: Grammar-Integrated Pretrained Encoder-Decoder Neural Model for Code
Research Track
Hard to Read and Understand Pythonic Idioms? DeIdiom and Explain Them in Non-Idiomatic Equivalent CodeACM SIGSOFT Distinguished Paper Award
Research Track
High Expectations: An Observational Study of Programming and Cannabis Intoxication
Research Track
How Are Paid and Volunteer Open Source Developers Different? A Study of the Rust Project
Research Track
Pre-print
How do Developers Talk about GitHub Actions? Evidence from Online Software Development Community
Research Track
How Far Are We? The Triumphs and Trials of Generative AI in Learning Software Engineering
Research Track
How to Support ML End-User Programmers through a Conversational Agent
Research Track
Hypertesting of Programs: Theoretical Foundation and Automated Test Generation
Research Track
Pre-print
Identifying Affected Libraries and Their Ecosystems for Open Source Software Vulnerabilities
Research Track
Improving Smart Contract Security with Contrastive Learning-based Vulnerability Detection
Research Track
Improving Testing Behavior by Gamifying IntelliJ
Research Track
Pre-print
Inferring Data Preconditions from Deep Learning Models for Trustworthy Prediction in Deployment
Research Track
Investigating White-Box Attacks for On-Device Models
Research Track
Is unsafe an Achilles' Heel? A Comprehensive Study of Safety Requirements in Unsafe Rust Programming
Research Track
“I tend to view ads almost like a pestilence”: On the Accessibility Implications of Mobile Ads for Blind Users
Research Track
ITER: Iterative Neural Repair for Multi-Location Patches
Research Track
It's Not a Feature, It's a Bug: Fault-Tolerant Model Mining from Noisy Data
Research Track
JLeaks: A Featured Resource Leak Repository Collected From Hundreds of Open-Source Java Projects
Research Track
Kind Controllers and Fast Heuristics for Non-Well-Separated GR(1) Specifications
Research Track
Knowledge Graph Driven Inference Testing for Question Answering Software
Research Track
KnowLog: Knowledge Enhanced Pre-trained Language Model for Log Understanding
Research Track
Language Models for Code Completion: A Practical Evaluation
Research Track
Large Language Models are Edge-Case Generators: Crafting Unusual Programs for Fuzzing Deep Learning Libraries
Research Track
Large Language Models are Few-Shot Summarizers: Multi-Intent Comment Generation via In-Context Learning
Research Track
Pre-print
Large Language Models for Test-Free Fault Localization
Research Track
Learning and Repair of Deep Reinforcement Learning Policies from Fuzz-Testing Data
Research Track
Learning-based Widget Matching for Migrating GUI Test Cases
Research Track
Learning in the Wild: Towards Leveraging Unlabeled Data for Effectively Tuning Pre-trained Code Models
Research Track
Less is More? An Empirical Study on Configuration Issues in Python PyPI Ecosystem
Research Track
LibAlchemy: A Two-Layer Persistent Summary Design for Taming Third-Party Libraries in Static Bug-Finding Systems
Research Track
LibvDiff: Library Version Difference Guided OSS Version Identification in Binaries
Research Track
LLMParser: An Exploratory Study on Using Large Language Models for Log Parsing
Research Track
LogShrink: Effective Log Compression by Leveraging Commonality and Variability of Log Data
Research Track
Pre-print
Lost in Translation: A Study of Bugs Introduced by Large Language Models while Translating Code
Research Track
DOI Pre-print Media Attached
Machine Learning is All You Need: A Simple Token-based Approach for Effective Code Clone Detection
Research Track
MAFT: Efficient Model-Agnostic Fairness Testing for Deep Neural Networks via Zero-Order Gradient Search
Research Track
Make LLM a Testing Expert: Bringing Human-like Interaction to Mobile GUI Testing via Functionality-aware Decisions
Research Track
MalCertain: Enhancing Deep Neural Network Based Android Malware Detection by Tackling Prediction Uncertainty
Research Track
MalwareTotal: Multi-Faceted and Sequence-Aware Bypass Tactics against Static Malware Detection
Research Track
Marco: A Stochastic Asynchronous Concolic Explorer
Research Track
Pre-print
MetaLog: Generalizable Cross-System Anomaly Detection from Logs with Meta-Learning
Research Track
MiniMon: Minimizing Android Applications with Intelligent Monitoring-Based Debloating
Research Track
Mining Pull Requests to Detect Process Anomalies in Open Source Software Development
Research Track
Modularizing while Training: a New Paradigm for Modularizing DNN ModelsACM SIGSOFT Distinguished Paper Award
Research Track
Pre-print
ModuleGuard: Understanding and Detecting Module Conflicts in Python Ecosystem
Research Track
MotorEase: Automated Detection of Motor Impairment Accessibility Issues in Mobile App UIs
Research Track
Mozi: Discovering DBMS Bugs via Configuration-Based Equivalent Transformation
Research Track
MultiTest: Physical-Aware Object Insertion for Testing Multi-sensor Fusion Perception Systems
Research Track
Pre-print
MUT: Human-in-the-Loop Unit Test Migration
Research Track
“My GitHub Sponsors profile is live!” Investigating the Impact of Twitter/X Mentions on GitHub Sponsors
Research Track
Pre-print Media Attached
Novelty Begets Popularity, But Curbs Participation - A Macroscopic View of the Python Open-Source Ecosystem
Research Track
Pre-print
NuzzleBug: Debugging Block-Based Programs in Scratch
Research Track
Pre-print
Object Graph Programming
Research Track
On Calibration of Pre-trained Code models
Research Track
On Extracting Specialized Code Abilities from Large Language Models: A Feasibility Study
Research Track
On the Effectiveness of Function-Level Vulnerability Detectors for Inter-Procedural Vulnerabilities
Research Track
Pre-print
On the Helpfulness of Answering Developer Questions on Discord with Similar Conversations and Posts from the Past
Research Track
On Using GUI Interaction Data to Improve Text Retrieval-based Bug Localization
Research Track
Optimistic Prediction of Synchronization-Reversal Data Races
Research Track
Out of Context: How important is Local Context in Neural Program Repair?
Research Track
Out of Sight, Out of Mind: Better Automatic Vulnerability Repair by Broadening Input Ranges and Sources
Research Track
PonziGuard: Detecting Ponzi Schemes on Ethereum with Contract Runtime Behavior Graph (CRBG)
Research Track
PPT4J: Patch Presence Test for Java Binaries
Research Track
Practical Non-Intrusive GUI Exploration Testing with Visual-based Robotic Arms
Research Track
Practical Program Repair via Preference-based Ensemble Strategy
Research Track
Precise Sparse Abstract Execution via Cross-Domain Interaction
Research Track
Predicting open source contributor turnover from value-related discussions: An analysis of GitHub issues
Research Track
Predicting Performance and Accuracy of Mixed-Precision Programs for Precision Tuning
Research Track
Pre-training by Predicting Program Dependencies for Vulnerability Analysis Tasks
Research Track
PrettySmart: Detecting Permission Re-delegation Vulnerability for Token Behaviors in Smart Contracts
Research Track
Prism: Decomposing Program Semantics for Code Clone Detection through Compilation
Research Track
Programming Assistant for Exception Handling with CodeBERT
Research Track
Prompting Is All Your Need: Automated Android Bug Replay with Large Language Models
Research Track
Property-Based Testing in PracticeACM SIGSOFT Distinguished Paper Award
Research Track
PS3: Precise Patch Presence Test based on Semantic Symbolic Signature
Research Track
PyAnalyzer: An Effective and Practical Approach for Dependency Extraction from Python Code
Research Track
PyTy: Repairing Static Type Errors in Python
Research Track
DOI Pre-print
Raisin: Identifying Rare Sensitive Functions for Bug Detection
Research Track
ReClues: Representing and indexing failures in parallel debugging with program variables
Research Track
Recovering Trace Links Between Software Documentation And Code
Research Track
Link to publication DOI Pre-print
REDriver: Runtime Enforcement for Autonomous Vehicles
Research Track
Pre-print
ReFAIR: Toward a Context-Aware Recommender for Fairness Requirements Engineering
Research Track
Reorder Pointer Flow in Sound Concurrency Bug Prediction
Research Track
Resource Usage and Optimization Opportunities in Workflows of GitHub Actions
Research Track
Pre-print
Revealing Hidden Threats: An Empirical Study of Library Misuse in Smart Contracts
Research Track
Revisiting Android App Categorization
Research Track
Ripples of a Mutation — An Empirical Study of Propagation Effects in Mutation Testing
Research Track
RogueOne: Detecting Rogue Updates via Differential Data-flow Analysis Using Trust Domains
Research Track
ROSInfer: Statically Inferring Behavioral Component Models for ROS-based Robotics Systems
Research Track
RPG: Rust Library Fuzzing with Pool-based Fuzz Target Generation and Generic Support
Research Track
DOI Pre-print
RUNNER: Responsible UNfair NEuron Repair for Enhancing Deep Neural Network Fairness
Research Track
Rust-lancet: Automated Ownership-Rule-Violation Fixing with Behavior Preservation
Research Track
S3C: Spatial Semantic Scene Coverage for Autonomous Vehicles
Research Track
Pre-print
Safeguarding DeFi Smart Contracts against Oracle DeviationsACM SIGSOFT Distinguished Paper Award
Research Track
Scalable Relational Analysis via Relational Bound Propagation
Research Track
Scaling Code Pattern Inference with Interactive What-If Analysis
Research Track
SCTrans: Constructing a Large Public Scenario Dataset for Simulation Testing of Autonomous Driving Systems
Research Track
SCVHunter: Smart Contract Vulnerability Detection Based on Heterogeneous Graph Attention Network
Research Track
Sedar: Obtaining High-Quality Seeds for DBMS Fuzzing via Cross-DBMS SQL Transfer
Research Track
Semantic Analysis of Macro Usage for Portability
Research Track
DOI Pre-print
Semantic-Enhanced Static Vulnerability Detection in Baseband FirmwareACM SIGSOFT Distinguished Paper Award
Research Track
Semantic GUI Scene Learning and Video Alignment for Detecting Duplicate Video-based Bug Reports
Research Track
Shedding Light on Software Engineering-specific Metaphors and Idioms
Research Track
Pre-print
Smart Contract and DeFi Security Tools: Do They Meet the Needs of Practitioners?
Research Track
SpecBCFuzz: Fuzzing LTL Solvers with Boundary Conditions
Research Track
Streamlining Java Programming: Uncovering Well-Formed Idioms with IdioMine
Research Track
Strengthening Supply Chain Security with Fine-grained Safe Patch Identification
Research Track
Supporting Web-based API Searches in the IDE Using Signatures
Research Track
Symbol-Specific Sparsification of Interprocedural Distributive Environment Problems
Research Track
Pre-print
Tensor-Aware Energy Accounting
Research Track
Testing Graph Database Systems via Equivalent Query Rewriting
Research Track
Testing the Limits: Unusual Text Inputs Generation for Mobile App Crash Detection with Large Language Model
Research Track
The Classics Never Go Out of Style: An Empirical Study of Downgrades from the Bazel Build Technology
Research Track
Pre-print
Toward Automatically Completing GitHub Workflows
Research Track
Pre-print
Toward Improved Deep Learning-based Vulnerability Detection
Research Track
Towards Causal Deep Learning for Vulnerability Detection
Research Track
Towards Finding Accounting Errors in Smart ContractsACM SIGSOFT Distinguished Paper Award
Research Track
Towards More Practical Automation of Vulnerability Assessment
Research Track
Towards Reliable AI: Adequacy Metrics for Ensuring the Quality of System-level Testing of Autonomous Vehicles
Research Track
Trace-based Multi-Dimensional Root Cause Localization of Performance Issues in Microservice Systems
Research Track
TRACED: Execution-aware Pre-training for Source Code
Research Track
Traces of Memorisation in Large Language Models for Code
Research Track
Pre-print
Translation Validation for JIT Compiler in the V8 JavaScript Engine
Research Track
TRIAD: Automated Traceability Recovery based on Biterm-enhanced Deduction of Transitive Links among Artifacts
Research Track
Pre-print
Uncovering the Causes of Emotions in Software Developer Communication Using Zero-shot LLMs
Research Track
Pre-print
Uncover the Premeditated Attacks: Detecting Exploitable Reentrancy Vulnerabilities by Identifying Attacker Contracts
Research Track
Understanding Transaction Bugs in Database Systems
Research Track
UniLog: Automatic Logging via LLM and In-Context Learning
Research Track
Unraveling the Drivers of Sense of Belonging in Software Delivery Teams: Insights from a Large-Scale Survey
Research Track
Unveiling Memorization in Code Models
Research Track
Unveiling the Life Cycle of User Feedback: Best Practices from Software Practitioners
Research Track
Using an LLM to Help With Code Understanding
Research Track
VeRe: Verification Guided Synthesis for Repairing Deep Neural Networks
Research Track
Verifying Declarative Smart Contracts
Research Track
VGX: Large-Scale Sample Generation for Boosting Learning-Based Software Vulnerability Analyses
Research Track
When Contracts Meets Crypto: Exploring Developers' Struggles with Ethereum Cryptographic APIs
Research Track
When Neural Code Completion Models Size up the Situation: Attaining Cheaper and Faster Completion through Dynamic Model Inference
Research Track
Where is it? Tracing the Vulnerability-relevant Files from Vulnerability Reports
Research Track
Xpert: Empowering Incident Management with Query Recommendations via Large Language Models
Research Track

Call for papers

The International Conference on Software Engineering (ICSE) is the premier forum for presenting and discussing the most recent and significant technical research contributions in the field of Software Engineering. In the research track, we invite high-quality submissions of technical research papers describing original and unpublished results of software engineering research.

Please note the following important changes for 2024:

  1. In 2024, ICSE will follow a dual deadline structure for submission of papers. In other words, submissions will occur in two cycles. This is the most important change. Please refer to the section on Dual Submission Cycles in the following for the information.

  2. For each paper submitted to Research track in ICSE 2024, authors will need to choose one of seven focus areas. Please see the section on Research Areas in the following.

Research Areas

ICSE welcomes submissions addressing topics across the full spectrum of Software Engineering, being inclusive of quantitative, qualitative, and mixed-methods research. Topics of interest include the following and are grouped into the following seven research areas.

Each submission will need to indicate one of these seven areas as the chosen area. Optionally, the authors can consider adding an additional area. A paper may be moved from the chosen area(s) to another focus area at the discretion of the program chairs. Program chairs will ultimately assign a paper to an area chair, considering the authors’ selection, the paper’s content, and other factors such as (if applicable) possible conflicts of interest.

AI and software engineering, Auto-coding

  • SE for Machine learning systems
  • Machine learning for SE tasks
  • Recommender systems
  • Autonomic systems and self-healing systems
  • Program synthesis
  • Program repair
  • AI for DevOps
  • Code generation from machine learning models

Analytics

  • Mining software repositories, communication platforms, and novel software engineering data sources
  • Apps and app store analysis
  • Software ecosystems
  • Configuration management
  • Software visualization
  • Data-driven user experience understanding and improvement
  • Data driven decision making in software engineering

Dependability and Security

  • Formal methods
  • Model Checking
  • Reliability and Safety
  • Vulnerability detection to enhance software security
  • System design to enhance software security
  • Privacy, Robustness, Fairness: Checking and Enforcement
  • Embedded and cyber-physical systems: modeling and validation

Evolution

  • Evolution and maintenance
  • API design and evolution
  • Release engineering and DevOps
  • Software reuse
  • Refactoring and program differencing
  • Program comprehension
  • Reverse engineering
  • Environments and software development tools
  • Traceability to understand evolution

Human and Social aspects

  • Human and organizational aspects of software engineering
  • Interaction in programming environments and software engineering tools
  • Distributed and collaborative software engineering
  • Agile methods and software processes
  • Software economics
  • Community-based software engineering (e.g., open source, crowdsourcing)
  • Ethics in software engineering
  • Green and sustainable technologies
  • Research on diversity, inclusion and social issues in software engineering

Requirements and modeling

  • Requirements Engineering (incl. non-functional requirements)
  • Design for quality, including privacy and security by design
  • Feedback, user and requirements management
  • Modelling and Model-Driven Engineering
  • Software Architecture and Design
  • Variability and product lines
  • Systems and software traceability
  • Software services and cloud-based systems

Testing and analysis

  • Software testing
  • Program analysis
  • Debugging and fault localization
  • Programming languages: developer-centric issues
  • Automated test generation techniques such as search and symbolic execution
  • Testing and analysis of non-functional properties
  • GUI testing
  • Mobile application testing

Scope

Since the authors will choose an area for their submission, the scope of each area becomes important. Some submissions may relate to multiple areas. In such cases, the authors should choose the area for which their paper brings the maximum new insights. Moreover, authors also have the choice of indicating an alternate area for each paper.

Similarly, for certain papers. authors may have a question whether it belongs to any area, or it is simply out of scope. For such cases, we recommend the authors to judge whether their paper brings new insights for software engineering. As an example, a formal methods paper with a focus on hardware verification may be deemed out of scope for ICSE. In general, papers which only peripherally concern software engineering and do not give new insights from the software engineering perspective would be less relevant to ICSE. Our goal is however to be descriptive, rather than prescriptive, to enable authors to make their own decisions about relevance.

Dual Submission Cycles – New for ICSE 2024

Since ICSE 2024 will have a different timeline from previous ICSEs, we request authors to kindly take note of the dates. The dates for the two submission cycles are as follows

First submission cycle

  • Submission: March 29, 2023
  • Notification: June 2, 2023
  • Revision due: July 10, 2023
  • Final Decisions: August 24, 2023
  • Camera-ready: Sept 15, 2023

Second submission cycle

  • Submission: August 1, 2023
  • Notification: October 10, 2023
  • Revision due: Nov 17, 2023
  • Final Decisions: Dec 15, 2023
  • Camera ready: Jan 12, 2024

Papers accepted for the first submission cycle of ICSE 24 will be available in the ACM and IEEE Digital Libraries after the camera-ready deadline of September 15 2023. Once papers have been reviewed, authors will be able to see the full reviews, including the reviewer scores. There is no rebuttal phase for either cycle.

Review Criteria

Each paper submitted to the Research Track will be evaluated based on the following criteria:

i) Novelty: The novelty and innovativeness of contributed solutions, problem formulations, methodologies, theories and/or evaluations, i.e., the extent to which the paper is sufficiently original with respect to state-of-the-art.

ii) Rigor: The soundness, clarity and depth of a technical or theoretical contribution, and the level of thoroughness and completeness of an evaluation.

iii) Relevance: The significance and/or potential impact of the research to the field of software engineering.

iv) Verifiability and Transparency: The extent to which the paper includes sufficient information to understand how an innovation works; to understand how data was obtained, analyzed, and interpreted; and how the paper supports independent verification or replication of the paper’s claimed contributions. Any artifacts attached to or linked from the paper may be checked by one reviewer.

v) Presentation: The clarity of the exposition in the paper.

Reviewers will carefully consider all of the above criteria during the review process, and authors should take great care in clearly addressing them all. The paper should clearly explain and justify the claimed contributions. Each paper will be handled by an area chair who will ensure reviewing consistency among papers submitted within that area.

The outcome of each paper will be one of the following Accept, Conditional Accept, Revision, Reject. Note that papers which are Accepted straight-away may still involve changes by authors in the camera-ready version, but these changes will not be checked any further by PC. We now elaborate the Conditional Accept and the Revision outcomes in the following.

Conditional Accept

Authors of papers receiving a Conditional Accept decision are expected to submit the revised papers with changes marked in a different color, such as using LaTeXdiff. The authors also need to submit an “Author Response” document capturing the authors’ response to each reviewer comment and how those comments were addressed in the revision. This is similar to the “Summary of Changes and Response” document that is typically submitted by authors for a journal paper major revision. The reviewers will check the revised paper against the original paper and the suggested changes. Conditional Accepts will be checked by only one member of the Program Committee, and this will be done in one pass. We expect all papers receiving Conditional Accept to be accepted, even though this is not guaranteed.

Revisions

Papers submitted can go through revisions in response to specific revision requests made by the reviewers. Authors of papers receiving a Revision decision are expected to submit the revised papers with changes marked in a different color, such as using LaTeXdiff. The authors also need to submit an “Author Response” document capturing the authors’ response to each reviewer comment and how those comments were addressed in the revision. This is similar to the “Summary of Changes and Response” document that is typically submitted by authors for a journal paper major revision. Authors may use the revision opportunity to revise and improve the paper, but should not use this to submit a substantially different paper. The reviewers will check the revised paper against the original paper and the suggested changes. Revised papers will be examined by the same set of reviewers. An unsatisfactory revised paper will be rejected.

Re-submissions of rejected papers

Authors of papers which receive a REJECT decision in the first submission cycle are strongly discouraged from re-submitting it to the second submission cycle. However, in exceptional cases where the authors feel that the reviewers misunderstood their paper, authors can re-submit their paper to the second submission cycle with a “Clarifications and Summary of Improvements” document stating how they have changed the paper. They should also include the past reviews as part of this document, for completeness. These papers will be treated as new submissions which may or may not get the same set of reviewers at the discretion of the PC chairs. Authors who try to bypass this guideline (e.g., by changing the paper title without significantly changing paper content, or by making small changes to the paper content) will have their papers desk-rejected by the PC chairs without further consideration. Papers rejected from the first or second submission cycle of ICSE2024 can be submitted to ICSE2025 without any restrictions.

Submission Process

All authors should use the official “ACM Primary Article Template”, as can be obtained from the ACM Proceedings Template page. LaTeX users should use the sigconf option, as well as the review (to produce line numbers for easy reference by the reviewers) and anonymous (omitting author names) options. To that end, the following LaTeX code can be placed at the start of the LaTeX document:

\documentclass[sigconf,review,anonymous]{acmart}

\acmConference[ICSE 2024]{46th International Conference on Software Engineering}{April 2024}{Lisbon, Portugal}

  • All submissions must not exceed 10 pages for the main text, inclusive of all figures, tables, appendices, etc. Two more pages containing only references are permitted. All submissions must be in PDF. Accepted papers will be allowed one extra page for the main text of the camera-ready version.
  • Submissions must strictly conform to the ACM conference proceedings formatting instructions specified above. Alterations of spacing, font size, and other changes that deviate from the instructions may result in desk rejection without further review.
  • By submitting to the ICSE Research Track, authors acknowledge that they are aware of and agree to be bound by the ACM Policy and Procedures on Plagiarism and the IEEE Plagiarism FAQ. Papers submitted to ICSE 2024 must not have been published elsewhere and must not be under review or submitted for review elsewhere whilst under consideration for ICSE 2024. Contravention of this concurrent submission policy will be deemed a serious breach of scientific ethics, and appropriate action will be taken in all such cases. To check for double submission and plagiarism issues, the chairs reserve the right to (1) share the list of submissions with the PC Chairs of other conferences with overlapping review periods and (2) use external plagiarism detection software, under contract to the ACM or IEEE, to detect violations of these policies.
  • By submitting your article to an ACM Publication, you are hereby acknowledging that you and your co-authors are subject to all ACM Publications Policies, including ACM's new Publications Policy on Research Involving Human Participants and Subjects. Alleged violations of this policy or any ACM Publications Policy will be investigated by ACM and may result in a full retraction of your paper, in addition to other potential penalties, as per ACM Publications Policy.
  • Please ensure that you and your co-authors obtain an ORCID ID, so you can complete the publishing process for your accepted paper. ACM has been involved in ORCID from the start and we have recently made a commitment to collect ORCID IDs from all of our published authors. The collection process has started and will roll out as a requirement throughout 2022. We are committed to improve author discoverability, ensure proper attribution and contribute to ongoing community efforts around name normalization; your ORCID ID will help in these efforts.
  • The ICSE 2024 Research Track will employ a double-anonymous review process. Thus, no submission may reveal its authors’ identities. The authors must make every effort to honor the double-anonymous review process. In particular:
    • Authors’ names must be omitted from the submission.
    • All references to the author’s prior work should be in the third person.
    • While authors have the right to upload preprints on ArXiV or similar sites, they must avoid specifying that the manuscript was submitted to ICSE 2024.
    • During review, authors should not publicly use the submission title. They should thus use a different paper title for any pre-print in arxiv or similar websites.
  • Further advice, guidance, and explanation about the double-anonymous review process can be found in the Q&A page from prior ICSEs.
  • By submitting to the ICSE Research Track, authors acknowledge that they conform to the authorship policy of the ACM, and the authorship policy of the IEEE.

Submissions to the Technical Track that meet the above requirements can be made via the Research Track submission site by the submission deadline. Any submission that does not comply with these requirements may be desk rejected without further review.

Submission site (second cycle August 2023): https://icse2024.hotcrp.com/

We encourage the authors to upload their paper info early (and can submit the PDF later) to properly enter conflicts for double-anonymous reviewing. It is the sole responsibility of the authors to ensure that the formatting guidelines, double anonymous guidelines, and any other submission guidelines are met at the time of paper submission.

Open Science Policy

The research track of ICSE 2024 is governed by the ICSE 2024 Open Science policies. The guiding principle is that all research results should be accessible to the public and, if possible, empirical studies should be reproducible. In particular, we actively support the adoption of open artifact and open source principles. We encourage all contributing authors to disclose (anonymized and curated) data/artifacts to increase reproducibility and replicability. Note that sharing research artifacts is not mandatory for submission or acceptance. However, sharing is expected to be the default, and non-sharing needs to be justified. We recognize that reproducibility or replicability is not a goal in qualitative research and that, similar to industrial studies, qualitative studies often face challenges in sharing research data. For guidelines on how to report qualitative research to ensure the assessment of the reliability and credibility of research results, see this previously curated Q&A page.

Upon submission to the research track, authors are asked

  • to make their artifact available to the program committee (via upload of supplemental material or a link to an anonymous repository) – and provide instructions on how to access this data in the paper; or

  • to include in the paper an explanation as to why this is not possible or desirable; and

  • to indicate why they do not intend to make their data or study materials publicly available upon acceptance, if that is the case. The default understanding is that the data and/or other artifacts will be publicly available upon acceptance of a paper.

Withdrawing a Paper

Authors can withdraw their paper at any moment until the final decision has been made, through the paper submission system. Resubmitting the paper to another venue before the final decision has been made without withdrawing from ICSE 2024 first is considered a violation of the concurrent submission policy, and will lead to automatic rejection from ICSE 2024 as well as any other venue adhering to this policy. Such violations may also be reported to appropriate organizations e.g. ACM and IEEE.

Conference Attendance Expectation

If a submission is accepted, at least one author of the paper is required to register for ICSE 2024 and present the paper. We are assuming that the conference will be in-person, and if it is virtual or hybrid, virtual presentations may be possible. These matters will be discussed with authors closer to the date of the conference.