Empirical Software Engineering

Papers
(The TQCC of Empirical Software Engineering is 9. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2022-06-01 to 2026-06-01.)
ArticleCitations
Introduction to the special issue on program comprehension104
TestEvoViz: visualizing genetically-based test coverage evolution88
Consensus task interaction trace recommender to guide developers’ software navigation88
Shaky structures: The wobbly world of causal graphs in software analytics80
Underproduction analysis of open source software71
The human experience of comprehending source code in virtual reality66
Security by documentation? characterizing GitHub SECURITY.md policy and their adoption in Python libraries55
The design space of lockfiles across package managers51
(In)Security of mobile apps in developing countries: a systematic literature review50
Seeing the invisible: test prioritization for object detection system45
Optimal priority assignment for real-time systems: a coevolution-based approach42
Can static analysis tools find more defects?41
Fuzzing-based mutation testing of C/C++ software in cyber-physical systems40
Understanding the characteristics and the role of visual issue reports40
Evaluating software user feedback classifier performance on unseen apps, datasets, and metadata39
An empirical study on the effectiveness of large language models for SATD identification and classification38
More than React: Investigating the Role of Emoji Reaction in GitHub Pull Requests38
Mitigating omitted variable bias in empirical software engineering37
On the adoption and effects of source code reuse on defect proneness and maintenance effort37
Does the first response matter for future contributions? A study of first contributions35
Bugs in machine learning-based systems: a faultload benchmark35
Evaluating few-shot and contrastive learning methods for code clone detection34
A study of documentation for software architecture33
Toward effective secure code reviews: an empirical study of security-related coding weaknesses33
Cross-status communication and project outcomes in OSS development32
The impact of the COVID-19 pandemic on women’s contribution to public code32
Automated test generation for Scratch programs32
Developers’ perception matters: machine learning to detect developer-sensitive smells32
Automatic prediction of rejected edits in Stack Overflow31
The impact of class imbalance techniques on crashing fault residence prediction models30
On the emergence of testing strategies: A socio-technical grounded theory30
Evaluating the impact of flaky simulators on testing autonomous driving systems29
BTLink : automatic link recovery between issues and commits based on pre-trained BERT model29
App review driven collaborative bug finding27
Output format biases in the evaluation of large language models for code translation26
Deep learning techniques to detect cybersecurity attacks: a systematic mapping study26
Maintaining shared understanding of non-functional requirements in small companies using continuous software engineering25
Collaboration failure analysis in cyber-physical system-of-systems using context fuzzy clustering24
Deep learning based identification of inconsistent method names: How far are we?24
Towards cost-benefit evaluation for continuous software engineering activities24
Analyzing and mitigating (with LLMs) the security misconfigurations of Helm charts from Artifact Hub24
What causes exceptions in machine learning applications? Mining machine learning-related stack traces on Stack Overflow24
Testing the past: can we still run tests in past snapshots for Java projects?24
A fine-grained taxonomy of code review feedback in TypeScript projects23
The Influence of Code Comments on the Perceived Helpfulness of Stack Overflow Posts23
Smells in system user interactive tests23
The effect of stereotypes on perceived competence of indigenous software practitioners: a study of dress style in professional photos22
Indentation and reading time: a randomized control trial on the differences between generated indented and non-indented if-statements22
An empirical study of untangling patterns of two-class dependency cycles22
AI support for data scientists: An empirical study on workflow and alternative code recommendations22
A grounded theory of community package maintenance organizations22
An empirical study of the impact of log parsers on the performance of log-based anomaly detection21
A Comprehensive Study of the Lifecycle of Dormant npm Packages21
How far are we with automated machine learning? characterization and challenges of AutoML toolkits21
On combining commit grouping and build skip prediction to reduce redundant continuous integration activity21
An empirical evaluation of a novel domain-specific language – modelling vehicle routing problems with Athos21
A configurable method for benchmarking scalability of cloud-native applications21
JNFuzz-Droid: a lightweight fuzzing and taint analysis framework for native code of Android applications20
Why android app testing falls short: empirical insights from open-source projects and a practitioner survey20
Scalable hierarchical protocol format inference via feature-heuristic message delimiter19
Code reviews in open source projects : how do gender biases affect participation and outcomes?19
How far are app secrets from being stolen? a case study on android19
Static detection of equivalent mutants in real-time model-based mutation testing19
Securing dependencies: A comprehensive study of Dependabot’s impact on vulnerability mitigation19
Understanding practitioners’ reasoning and requirements for efficient tool support in technical debt management18
Advantages and disadvantages of (dedicated) model transformation languages18
Quantifying adoption: A SEM study of quantum software technology in software development18
Real world projects, real faults: evaluating spectrum based fault localization techniques on Python projects18
Experimental comparison of features, analyses, and classifiers for Android malware detection18
A large-scale empirical study of commit message generation: models, datasets and evaluation17
A metrics-based approach for selecting among various refactoring candidates17
The well-being of software engineers: a systematic literature review and a theory17
Lightweight dynamic build batching algorithms for continuous integration17
Patterns of multi-container composition for service orchestration with Docker Compose17
Local software buildability across Java versions16
Systematic Evaluation of Deep Learning Models for Log-based Failure Prediction16
An empirical study on the potential of word embedding techniques in bug report management tasks16
ContractFull: a rapid and comprehensive static analysis tool for Ethereum smart contracts16
Engineering recommender systems for modelling languages: concept, tool and evaluation16
Validation of an analyzability model for quantum software: a family of experiments16
Software product line testing: a systematic literature review15
Language usage analysis for EMF metamodels on GitHub15
Common challenges of deep reinforcement learning applications development: an empirical study15
LineFlowDP: A Deep Learning-Based Two-Phase Approach for Line-Level Defect Prediction15
Enhanced SQL error messages facilitate faster error fixing15
Mastering uncertainty in performance estimations of configurable software systems15
Software testing in the machine learning era15
What kinds of contracts do ML APIs need?15
What really changes when developers intend to improve their source code: a commit-level study of static metric value and static analysis warning changes15
Tools and benchmarks evolve: what is their impact on parameter tuning in SBSE experiments?15
Securing LLM-in-the-loop software for empirical study of risks, mitigations, and utility trade-offs in a safety-critical case15
Test smells 20 years later: detectability, validity, and reliability14
An investigation of online and offline learning models for online Just-in-Time Software Defect Prediction14
Preface to the Special Issue on Security Testing for Complex Software Systems Special Issue 1239 Editorial14
Is GitHub’s Copilot as bad as humans at introducing vulnerabilities in code?14
DRECT: A search-based developer recommendation approach for software crowdsourcing platforms14
OpTrans: enhancing binary code similarity detection with function inlining re-optimization14
On the Investigation of Empirical Contradictions - Aggregated Results of Local Studies on Readability and Comprehensibility of Source Code14
Comparing effectiveness and efficiency of Interactive Application Security Testing (IAST) and Runtime Application Self-Protection (RASP) tools in a large java-based system14
RAG-Driven multiple assertions generation with large language models14
When less is more: on the value of “co-training” for semi-supervised software defect predictors14
Can the configuration of static analyses make resolving security vulnerabilities more effective? - A user study14
Semantic matching in GUI test reuse14
Prioritizing test cases for deep learning-based video classifiers14
Studying the explanations for the automated prediction of bug and non-bug issues using LIME and SHAP13
Measuring SES-related traits relating to technology usage: Two validated surveys13
Which design decisions in AI-enabled mobile applications contribute to greener AI?13
An exploratory study on fine-tuning large language models for secure code generation13
An empirical study of testing practices in open source AI agent frameworks and agentic applications13
Exploring the black box: analysing explainable AI challenges and best practices through stack exchange discussions13
Challenges and practices of deep learning model reengineering: A case study on computer vision13
Program transformation landscapes for automated program modification using Gin13
Classifier or prompt: A case study on legal requirements traceability13
Test schedule generation for acceptance testing of mission-critical satellite systems13
Meta-enhanced code: leveraging structural and functional features for precise cross-modal code search13
Defect prediction using deep learning with Network Portrait Divergence for software evolution13
Toward granular search-based automatic unit test case generation13
SmartFast: an accurate and robust formal analysis tool for Ethereum smart contracts13
Applying bayesian data analysis for causal inference about requirements quality: a controlled experiment13
Semantically-enhanced topic recommendation systems for software projects13
Towards understanding the challenges of bug localization in deep learning systems13
Correction to: Examining ownership models in software teams13
A zero-shot framework for cross-project vulnerability detection in source code12
A multi-model framework for semantically enhancing detection of quality-related bug report descriptions12
On the spread and evolution of dead methods in Java desktop applications: an exploratory study12
On detection latencies of network intrusion detectors – discussion and application12
DDImage: an image reduction based approach for automatically explaining black-box classifiers12
A controlled experiment on the impact of microtasking on programming11
A fine-grained evaluation of mutation operators to boost mutation testing for deep learning systems11
A fine-grained data set and analysis of tangling in bug fixing commits11
How challenging it is to identify real code authors: an empirical study11
Static analysis driven enhancements for comprehension in machine learning notebooks11
Learning to Predict Code Review Completion Time In Modern Code Review11
Cross-project defect prediction via semantic and syntactic encoding11
Towards automatic labeling of exception handling bugs: A case study of 10 years bug-fixing in Apache Hadoop11
CsmithEdge: more effective compiler testing by handling undefined behaviour less conservatively11
What have we learned? A conceptual framework on New Zealand software professionals and companies’ response to COVID-1911
Experimental Evaluation of a Checklist-Based Inspection Technique to Verify the Compliance of Software Systems with the Brazilian General Data Protection Law11
Automated detection of algorithm debt in deep learning frameworks: an empirical study11
Implicit security requirements classification with large language models using the OWASP application security verification standard: a shift-left approach11
Fixing Dockerfile smells: an empirical study11
CyberSAGE: The cyber security argument graph evaluation tool11
Identifying performance-sensitive configurations in software systems with LLM-based agents11
Modeling function-level interactions for file-level bug localization11
Styler: learning formatting conventions to repair Checkstyle violations11
KPIRoot+: An efficient integrated framework for anomaly detection and root cause analysis in large-scale cloud systems11
Unveiling overlooked performance variance in serverless computing11
Demystifying API misuses in deep learning applications11
When uncertainty leads to unsafety: Empirical insights into the role of uncertainty in unmanned aerial vehicle safety11
APR4Vul: an empirical study of automatic program repair techniques on real-world Java vulnerabilities11
Seeing confusion through a new lens: on the impact of atoms of confusion on novices’ code comprehension11
Detecting API compatibility issues of android applications based on screen transition graphs10
Empirically evaluating flaky test detection techniques combining test case rerunning and machine learning models10
Transformer-based code model with compressed hierarchy representation10
Silent bugs in deep learning frameworks: an empirical study of Keras and TensorFlow10
A qualitative study on refactorings induced by code review10
Refactoring practices in the context of data-intensive systems10
An empirical study on developers’ shared conversations with ChatGPT in GitHub pull requests and issues10
Understanding and effectively mitigating code review anxiety10
Investigating cross-market android apps: Security, protection, and components10
Studying differentiated code to support smart contract update10
Explainable automated debugging via large language model-driven scientific debugging10
From guidelines to practice: assessing Android app developer compliance with google’s security recommendations10
A qualitative study of developers’ discussions of their problems and joys during the early COVID-19 months10
Navigating fairness: practitioners’ understanding, challenges, and strategies in AI/ML development10
Model vs system level testing of autonomous driving systems: a replication and extension study10
Automatic bi-modal question title generation for Stack Overflow with prompt learning10
Agile software development one year into the COVID-19 pandemic10
Predicting merge conflicts considering social and technical assets10
Detecting data manipulation errors in android applications using scene-guided exploration10
Towards understanding quality challenges of the federated learning for neural networks: a first look from the lens of robustness10
ComPass: Contrastive Learning for Automated Patch Correctness Assessment in Program Repair10
Story points changes in agile iterative development10
Studying the characteristics of AIOps projects on GitHub10
Assessing the exposure of software changes10
Toward a theory on programmer’s block inspired by writer’s block9
Correction to: Why do companies create and how do they succeed with a vendor-led open source foundation9
CMF-Vul: Advancing automated vulnerability detection via contrastive multimodal fusion and challenge-driven representation learning9
Hyperfuzzing: black-box security hypertesting with a grey-box fuzzer9
Can search-based testing with pareto optimization effectively cover failure-revealing test inputs?9
An empirical study of the systemic and technical migration towards microservices9
Decoupling in AI ethics: Learning how to walk the talk9
What characteristics make ChatGPT effective for software issue resolution? An empirical study of task, project, and conversational signals in GitHub issues9
IRJIT: A simple, online, information retrieval approach for just-in-time software defect prediction9
GenCode: A generic data augmentation framework for boosting deep learning-based code understanding9
How programmers find online learning resources9
Understanding refactorings in Elixir functional language9
On the assignment of commits to releases9
Can generative AI bridge the gap? A quasi-experimental study of non-programmers with AI vs. programmers without AI9
An efficient model maintenance approach for MLOps9
Developers and generative AI: A study of self-admitted usage in open source projects9
Leveraging large language models for sentiment analysis in GitHub pull request discussions9
The whos, whats, and whys of issues related to personal data and data protection in open-source projects on GitHub9
Peer-aided repairer: empowering large language models to repair advanced student assignments9
Software selection in large-scale software engineering: A model and criteria based on interactive rapid reviews9
“What really happened to my models?” Extending co-evolution with cross-layer traceability in metamodel-model histories9
Evaluating pre-trained models for user feedback analysis in software engineering: a study on classification of app-reviews9
Extracting enhanced artificial intelligence model metadata from software repositories9
Industrial adoption of machine learning techniques for early identification of invalid bug reports9
Come for syntax, stay for speed, write secure code: an empirical study of security weaknesses in Julia programs9
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