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 2021-09-01 to 2025-09-01.)
ArticleCitations
Introduction to the special issue on program comprehension222
Consensus task interaction trace recommender to guide developers’ software navigation105
Path context augmented statement and network for learning programs71
Optimal priority assignment for real-time systems: a coevolution-based approach67
An empirical study on the effectiveness of large language models for SATD identification and classification67
Does the first response matter for future contributions? A study of first contributions66
The human experience of comprehending source code in virtual reality59
Can static analysis tools find more defects?55
More than React: Investigating the Role of Emoji Reaction in GitHub Pull Requests50
Toward effective secure code reviews: an empirical study of security-related coding weaknesses46
Understanding the characteristics and the role of visual issue reports44
Shaky structures: The wobbly world of causal graphs in software analytics43
Seeing the invisible: test prioritization for object detection system43
A study of documentation for software architecture41
Evaluating few-shot and contrastive learning methods for code clone detection40
Bugs in machine learning-based systems: a faultload benchmark37
Evaluating software user feedback classifier performance on unseen apps, datasets, and metadata37
TestEvoViz: visualizing genetically-based test coverage evolution33
(In)Security of mobile apps in developing countries: a systematic literature review32
An empirical study of IoT topics in IoT developer discussions on Stack Overflow31
Dynamical analysis of diversity in rule-based open source network intrusion detection systems30
Efficient static analysis and verification of featured transition systems29
Effects of variability in models: a family of experiments29
On the adoption and effects of source code reuse on defect proneness and maintenance effort29
Smells in system user interactive tests28
Collaboration failure analysis in cyber-physical system-of-systems using context fuzzy clustering28
Cross-status communication and project outcomes in OSS development28
Deep learning based identification of inconsistent method names: How far are we?27
Towards cost-benefit evaluation for continuous software engineering activities27
Automatic prediction of rejected edits in Stack Overflow27
Evaluating the impact of flaky simulators on testing autonomous driving systems27
A fine-grained taxonomy of code review feedback in TypeScript projects27
Testing the past: can we still run tests in past snapshots for Java projects?26
On the use of commit-relevant mutants26
Analyzing and mitigating (with LLMs) the security misconfigurations of Helm charts from Artifact Hub26
What causes exceptions in machine learning applications? Mining machine learning-related stack traces on Stack Overflow25
App review driven collaborative bug finding24
Practitioner’s view of the success factors for software outsourcing partnership formation: an empirical exploration24
BTLink : automatic link recovery between issues and commits based on pre-trained BERT model24
The impact of the COVID-19 pandemic on women’s contribution to public code24
Developers’ perception matters: machine learning to detect developer-sensitive smells23
Automated test generation for Scratch programs23
Deep learning techniques to detect cybersecurity attacks: a systematic mapping study23
The impact of class imbalance techniques on crashing fault residence prediction models23
On the impact of security vulnerabilities in the npm and RubyGems dependency networks23
A grounded theory of community package maintenance organizations22
How far are we with automated machine learning? characterization and challenges of AutoML toolkits22
A large-scale empirical study of commit message generation: models, datasets and evaluation22
Experimental comparison of features, analyses, and classifiers for Android malware detection22
Indentation and reading time: a randomized control trial on the differences between generated indented and non-indented if-statements22
Static detection of equivalent mutants in real-time model-based mutation testing22
JNFuzz-Droid: a lightweight fuzzing and taint analysis framework for native code of Android applications21
Advantages and disadvantages of (dedicated) model transformation languages21
How far are app secrets from being stolen? a case study on android21
Code reviews in open source projects : how do gender biases affect participation and outcomes?20
Securing dependencies: A comprehensive study of Dependabot’s impact on vulnerability mitigation20
On combining commit grouping and build skip prediction to reduce redundant continuous integration activity19
Understanding practitioners’ reasoning and requirements for efficient tool support in technical debt management19
Real world projects, real faults: evaluating spectrum based fault localization techniques on Python projects19
The well-being of software engineers: a systematic literature review and a theory19
An empirical study of untangling patterns of two-class dependency cycles19
An empirical study of the impact of log parsers on the performance of log-based anomaly detection19
AI support for data scientists: An empirical study on workflow and alternative code recommendations19
A configurable method for benchmarking scalability of cloud-native applications19
An empirical evaluation of a novel domain-specific language – modelling vehicle routing problems with Athos19
Engineering recommender systems for modelling languages: concept, tool and evaluation18
Systematic Evaluation of Deep Learning Models for Log-based Failure Prediction18
LineFlowDP: A Deep Learning-Based Two-Phase Approach for Line-Level Defect Prediction18
Demystifying regular expression bugs18
Visualizing the customization endeavor in product-based-evolving software product lines: a case of action design research18
An empirical study on the potential of word embedding techniques in bug report management tasks18
Take a deep breath: Benefits of neuroplasticity practices for software developers and computer workers in a family of experiments18
Lightweight dynamic build batching algorithms for continuous integration17
Patterns of multi-container composition for service orchestration with Docker Compose17
What really changes when developers intend to improve their source code: a commit-level study of static metric value and static analysis warning changes16
Gamification in software engineering: the mediating role of developer engagement and job satisfaction16
Software product line testing: a systematic literature review16
When less is more: on the value of “co-training” for semi-supervised software defect predictors16
Towards a recipe for language decomposition: quality assessment of language product lines16
A metrics-based approach for selecting among various refactoring candidates16
Language usage analysis for EMF metamodels on GitHub16
Software testing in the machine learning era15
On the Investigation of Empirical Contradictions - Aggregated Results of Local Studies on Readability and Comprehensibility of Source Code15
Enhanced SQL error messages facilitate faster error fixing15
Mastering uncertainty in performance estimations of configurable software systems15
RAG-Driven multiple assertions generation with large language models15
What kinds of contracts do ML APIs need?15
Semantic matching in GUI test reuse15
Präzi: from package-based to call-based dependency networks14
An investigation of online and offline learning models for online Just-in-Time Software Defect Prediction14
Is GitHub’s Copilot as bad as humans at introducing vulnerabilities in code?14
Semantically-enhanced topic recommendation systems for software projects14
Common challenges of deep reinforcement learning applications development: an empirical study14
Test smells 20 years later: detectability, validity, and reliability14
Correction to: Examining ownership models in software teams14
Applying bayesian data analysis for causal inference about requirements quality: a controlled experiment14
Comparing effectiveness and efficiency of Interactive Application Security Testing (IAST) and Runtime Application Self-Protection (RASP) tools in a large java-based system14
Can the configuration of static analyses make resolving security vulnerabilities more effective? - A user study14
Program transformation landscapes for automated program modification using Gin14
OpTrans: enhancing binary code similarity detection with function inlining re-optimization14
Which design decisions in AI-enabled mobile applications contribute to greener AI?13
Why secret detection tools are not enough: It’s not just about false positives - An industrial case study13
Toward granular search-based automatic unit test case generation13
Towards understanding the challenges of bug localization in deep learning systems13
A study of how Docker Compose is used to compose multi-component systems13
Defect prediction using deep learning with Network Portrait Divergence for software evolution13
Challenges and practices of deep learning model reengineering: A case study on computer vision13
Prioritizing test cases for deep learning-based video classifiers13
A multi-model framework for semantically enhancing detection of quality-related bug report descriptions12
Studying the explanations for the automated prediction of bug and non-bug issues using LIME and SHAP12
A controlled experiment on the impact of microtasking on programming12
Correction to: Towards a recipe for language decomposition: quality assessment of language product lines12
Seeing confusion through a new lens: on the impact of atoms of confusion on novices’ code comprehension12
Fixing Dockerfile smells: an empirical study12
SmartFast: an accurate and robust formal analysis tool for Ethereum smart contracts12
Experimental Evaluation of a Checklist-Based Inspection Technique to Verify the Compliance of Software Systems with the Brazilian General Data Protection Law12
Cross-project defect prediction via semantic and syntactic encoding12
What have we learned? A conceptual framework on New Zealand software professionals and companies’ response to COVID-1912
On the spread and evolution of dead methods in Java desktop applications: an exploratory study12
Demystifying API misuses in deep learning applications12
Reflections on the Empirical Software Engineering journal12
Static analysis driven enhancements for comprehension in machine learning notebooks12
Unveiling overlooked performance variance in serverless computing12
DDImage: an image reduction based approach for automatically explaining black-box classifiers12
Styler: learning formatting conventions to repair Checkstyle violations11
CyberSAGE: The cyber security argument graph evaluation tool11
CsmithEdge: more effective compiler testing by handling undefined behaviour less conservatively11
Propagating frugal user feedback through closeness of code dependencies to improve IR-based traceability recovery11
A comprehensive overview of software product management challenges11
Towards automatic labeling of exception handling bugs: A case study of 10 years bug-fixing in Apache Hadoop11
Learning to Predict Code Review Completion Time In Modern Code Review11
A fine-grained evaluation of mutation operators to boost mutation testing for deep learning systems11
An empirical study on self-admitted technical debt in Dockerfiles11
Assessing the exposure of software changes10
Modeling function-level interactions for file-level bug localization10
SoftNER: Mining knowledge graphs from cloud incidents10
Two N-of-1 self-trials on readability differences between anonymous inner classes (AICs) and lambda expressions (LEs) on Java code snippets10
Transformer-based code model with compressed hierarchy representation10
From guidelines to practice: assessing Android app developer compliance with google’s security recommendations10
A qualitative study on refactorings induced by code review10
A fine-grained data set and analysis of tangling in bug fixing commits10
Predicting merge conflicts considering social and technical assets10
Studying differentiated code to support smart contract update10
A qualitative study of developers’ discussions of their problems and joys during the early COVID-19 months10
Explainable automated debugging via large language model-driven scientific debugging10
APR4Vul: an empirical study of automatic program repair techniques on real-world Java vulnerabilities10
Understanding and effectively mitigating code review anxiety10
Refactoring practices in the context of data-intensive systems10
Model vs system level testing of autonomous driving systems: a replication and extension study9
Multi-granular software annotation using file-level weak labelling9
How to cherry pick the bug report for better summarization?9
IRJIT: A simple, online, information retrieval approach for just-in-time software defect prediction9
Software selection in large-scale software engineering: A model and criteria based on interactive rapid reviews9
What happens in my code reviews? An investigation on automatically classifying review changes9
Hyperfuzzing: black-box security hypertesting with a grey-box fuzzer9
Agile software development one year into the COVID-19 pandemic9
Story points changes in agile iterative development9
Empirically evaluating flaky test detection techniques combining test case rerunning and machine learning models9
Towards understanding quality challenges of the federated learning for neural networks: a first look from the lens of robustness9
Inter-team communication in large-scale co-located software engineering: a case study9
Toward a theory on programmer’s block inspired by writer’s block9
Deep learning approaches for bad smell detection: a systematic literature review9
How programmers find online learning resources9
Predicting the objective and priority of issue reports in software repositories9
Come for syntax, stay for speed, write secure code: an empirical study of security weaknesses in Julia programs9
GitHub Discussions: An exploratory study of early adoption9
Characterizing refactoring graphs in Java and JavaScript projects9
Silent bugs in deep learning frameworks: an empirical study of Keras and TensorFlow9
Navigating fairness: practitioners’ understanding, challenges, and strategies in AI/ML development9
An empirical study on developers’ shared conversations with ChatGPT in GitHub pull requests and issues9
On the assignment of commits to releases9
Extracting enhanced artificial intelligence model metadata from software repositories9
Machine learning-based test smell detection9
A comprehensive study of machine learning techniques for log-based anomaly detection9
Can search-based testing with pareto optimization effectively cover failure-revealing test inputs?9
Studying the characteristics of AIOps projects on GitHub9
Automatic bi-modal question title generation for Stack Overflow with prompt learning9
Detecting data manipulation errors in android applications using scene-guided exploration9
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