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ORCIDArie van Deursen
Person information
- affiliation: Delft University of Technology, The Netherlands
- affiliation (former): National Research Institute for Mathematics and Computer Science, Amsterdam, Netherlands
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2020 – today
- 2024
[c204]Patrick Altmeyer, Mojtaba Farmanbar, Arie van Deursen, Cynthia C. S. Liem:
Faithful Model Explanations through Energy-Constrained Conformal Counterfactuals. AAAI 2024: 10829-10837- [c203]Aral de Moor
, Arie van Deursen, Maliheh Izadi:
A Transformer-Based Approach for Smart Invocation of Automatic Code Completion. AIware 2024 - [c202]Lorena Poenaru-Olaru, Natalia Karpova, Luis Cruz, Jan S. Rellermeyer, Arie van Deursen:
Is Your Anomaly Detector Ready for Change? Adapting AIOps Solutions to the Real World. CAIN 2024: 222-233 - [c201]George Siachamis, George Christodoulou, Kyriakos Psarakis, Marios Fragkoulis, Arie van Deursen, Asterios Katsifodimos:
Evaluating Stream Processing Autoscalers. DEBS 2024: 110-122 - [c200]Bob Brockbernd, Nikita Koval, Arie van Deursen, Burcu Kulahcioglu Ozkan:
Understanding Concurrency Bugs in Real-World Programs with Kotlin Coroutines. ECOOP 2024: 8:1-8:20 - [c199]Jonathan Katzy, Razvan Mihai Popescu, Arie van Deursen, Maliheh Izadi:
An Exploratory Investigation into Code License Infringements in Large Language Model Training Datasets. FORGE 2024: 74-85 - [c198]George Siachamis, Kyriakos Psarakis, Marios Fragkoulis, Arie van Deursen, Paris Carbone, Asterios Katsifodimos:
CheckMate: Evaluating Checkpointing Protocols for Streaming Dataflows. ICDE 2024: 4030-4043 - [c197]Eileen Kapel, Luis Cruz, Diomidis Spinellis, Arie van Deursen:
On the Difficulty of Identifying Incident-Inducing Changes. ICSE-SEIP 2024: 36-46 - [c196]Ali Al-Kaswan, Maliheh Izadi, Arie van Deursen:
Traces of Memorisation in Large Language Models for Code. ICSE 2024: 78:1-78:12 - [c195]Maliheh Izadi, Jonathan Katzy, Tim van Dam, Marc Otten, Razvan Mihai Popescu, Arie van Deursen:
Language Models for Code Completion: A Practical Evaluation. ICSE 2024: 79:1-79:13 - [c194]Arumoy Shome, Luís Cruz, Arie van Deursen:
Data vs. Model Machine Learning Fairness Testing: An Empirical Study. ICSE Companion 2024: 366-367 - [c193]Arumoy Shome, Luis Cruz, Arie van Deursen:
Towards Automatic Translation of Machine Learning Visual Insights to Analytical Assertions. NLBSE@ICSE 2024: 29-32 - [i54]Arumoy Shome, Luis Cruz, Arie van Deursen:
Towards Automatic Translation of Machine Learning Visual Insights to Analytical Assertions. CoRR abs/2401.07696 (2024) - [i53]Arumoy Shome, Luis Cruz, Arie van Deursen:
Data vs. Model Machine Learning Fairness Testing: An Empirical Study. CoRR abs/2401.07697 (2024) - [i52]Lorena Poenaru-Olaru, Luis Cruz, Jan S. Rellermeyer, Arie van Deursen:
McUDI: Model-Centric Unsupervised Degradation Indicator for Failure Prediction AIOps Solutions. CoRR abs/2401.14093 (2024) - [i51]Maliheh Izadi, Jonathan Katzy, Tim van Dam, Marc Otten, Razvan Mihai Popescu, Arie van Deursen:
Language Models for Code Completion: A Practical Evaluation. CoRR abs/2402.16197 (2024) - [i50]George Siachamis, Kyriakos Psarakis, Marios Fragkoulis, Arie van Deursen, Paris Carbone, Asterios Katsifodimos:
CheckMate: Evaluating Checkpointing Protocols for Streaming Dataflows. CoRR abs/2403.13629 (2024) - [i49]Jonathan Katzy, Razvan Mihai Popescu, Arie van Deursen, Maliheh Izadi:
An Exploratory Investigation into Code License Infringements in Large Language Model Training Datasets. CoRR abs/2403.15230 (2024) - [i48]Aral de Moor, Arie van Deursen, Maliheh Izadi:
A Transformer-Based Approach for Smart Invocation of Automatic Code Completion. CoRR abs/2405.14753 (2024) - [i47]Egor Bogomolov, Aleksandra Eliseeva, Timur Galimzyanov, Evgeniy Glukhov, Anton Shapkin, Maria Tigina, Yaroslav Golubev, Alexander Kovrigin, Arie van Deursen, Maliheh Izadi, Timofey Bryksin:
Long Code Arena: a Set of Benchmarks for Long-Context Code Models. CoRR abs/2406.11612 (2024) - [i46]Arumoy Shome, Luis Cruz, Diomidis Spinellis, Arie van Deursen:
Understanding Feedback Mechanisms in Machine Learning Jupyter Notebooks. CoRR abs/2408.00153 (2024) - 2023
- [j60]Chandra Shekhar Maddila, Sai Surya Upadrasta, Chetan Bansal, Nachiappan Nagappan, Georgios Gousios, Arie van Deursen:
Nudge: Accelerating Overdue Pull Requests toward Completion. ACM Trans. Softw. Eng. Methodol. 32(2): 35:1-35:30 (2023) - [j59]Pouria Derakhshanfar, Xavier Devroey, Annibale Panichella, Andy Zaidman, Arie van Deursen:
Generating Class-Level Integration Tests Using Call Site Information. IEEE Trans. Software Eng. 49(4): 2069-2087 (2023) - [c192]Arie van Deursen:
Getting Things Done: The Eelco Way. Eelco Visser Commemorative Symposium 2023: 1:1-1:4 - [c191]Tim Yarally, Luis Cruz, Daniel Feitosa, June Sallou, Arie van Deursen:
Uncovering Energy-Efficient Practices in Deep Learning Training: Preliminary Steps Towards Green AI. CAIN 2023: 25-36 - [c190]Lorena Poenaru-Olaru, Luis Cruz, Jan S. Rellermeyer, Arie van Deursen:
Maintaining and Monitoring AIOps Models Against Concept Drift. CAIN 2023: 98-99 - [c189]Arumoy Shome, Luís Cruz, Arie van Deursen:
Towards Understanding Machine Learning Testing in Practise. CAIN 2023: 117-118 - [c188]George Siachamis, Kyriakos Psarakis, Marios Fragkoulis, Odysseas Papapetrou, Arie van Deursen, Asterios Katsifodimos:
Adaptive Distributed Streaming Similarity Joins. DEBS 2023: 25-36 - [c187]Tim Yarally, Luís Cruz, Daniel Feitosa, June Sallou, Arie van Deursen:
Batching for Green AI - An Exploratory Study on Inference. SEAA 2023: 112-119 - [c186]Lorena Poenaru-Olaru, June Sallou, Luis Cruz, Jan S. Rellermeyer, Arie van Deursen:
Retrain AI Systems Responsibly! Use Sustainable Concept Drift Adaptation Techniques. GREENS@ICSE 2023: 17-18 - [c185]George Siachamis, Job Kanis, Wybe Koper, Kyriakos Psarakis, Marios Fragkoulis, Arie van Deursen, Asterios Katsifodimos:
Towards Evaluating Stream Processing Autoscalers. ICDEW 2023: 95-99 - [c184]Jiyang Zhang, Chandra Shekhar Maddila, Ram Bairi, Christian Bird, Ujjwal Raizada, Apoorva Agrawal, Yamini Jhawar, Kim Herzig, Arie van Deursen:
Using Large-scale Heterogeneous Graph Representation Learning for Code Review Recommendations at Microsoft. ICSE-SEIP 2023: 162-172 - [c183]Tim van Dam, Maliheh Izadi, Arie van Deursen:
Enriching Source Code with Contextual Data for Code Completion Models: An Empirical Study. MSR 2023: 170-182 - [c182]Ali Al-Kaswan, Maliheh Izadi, Arie van Deursen:
STACC: Code Comment Classification using SentenceTransformers. NLBSE@ICSE 2023: 28-31 - [c181]Patrick Altmeyer, Giovan Angela, Aleksander Buszydlik, Karol Dobiczek, Arie van Deursen, Cynthia C. S. Liem:
Endogenous Macrodynamics in Algorithmic Recourse. SaTML 2023: 418-431 - [c180]Jonathan Katzy, Maliheh Izadi, Arie van Deursen:
On the Impact of Language Selection for Training and Evaluating Programming Language Models. SCAM 2023: 271-276 - [c179]Elvan Kula, Eric Greuter, Arie van Deursen, Georgios Gousios:
Dynamic Prediction of Delays in Software Projects using Delay Patterns and Bayesian Modeling. ESEC/SIGSOFT FSE 2023: 1012-1023 - [c178]Ali Al-Kaswan, Toufique Ahmed, Maliheh Izadi, Anand Ashok Sawant, Premkumar T. Devanbu, Arie van Deursen:
Extending Source Code Pre-Trained Language Models to Summarise Decompiled Binarie. SANER 2023: 260-271 - [d13]Jonathan Katzy, Maliheh Izadi, Arie van Deursen:
On the Impact of Language Selection for Training and Evaluating Programming Language Models. Zenodo, 2023
- [d12]Tim Yarally, Luís Cruz, Daniel Feitosa, June Sallou, Arie van Deursen:
Material of the paper entitled "Uncovering Energy-Efficient Practices in Deep Learning Training: Preliminary Steps Towards Green AI". Zenodo, 2023 - [i45]Ali Al-Kaswan, Toufique Ahmed, Maliheh Izadi, Anand Ashok Sawant, Premkumar T. Devanbu, Arie van Deursen:
Extending Source Code Pre-Trained Language Models to Summarise Decompiled Binaries. CoRR abs/2301.01701 (2023) - [i44]Ali Al-Kaswan, Maliheh Izadi, Arie van Deursen:
Targeted Attack on GPT-Neo for the SATML Language Model Data Extraction Challenge. CoRR abs/2302.07735 (2023) - [i43]Ali Al-Kaswan, Maliheh Izadi, Arie van Deursen:
STACC: Code Comment Classification using SentenceTransformers. CoRR abs/2302.13149 (2023) - [i42]Tim Yarally, Luís Cruz, Daniel Feitosa, June Sallou, Arie van Deursen:
Uncovering Energy-Efficient Practices in Deep Learning Training: Preliminary Steps Towards Green AI. CoRR abs/2303.13972 (2023) - [i41]Tim van Dam, Maliheh Izadi, Arie van Deursen:
Enriching Source Code with Contextual Data for Code Completion Models: An Empirical Study. CoRR abs/2304.12269 (2023) - [i40]Arumoy Shome, Luis Cruz, Arie van Deursen:
Towards Understanding Machine Learning Testing in Practise. CoRR abs/2305.04988 (2023) - [i39]Tim Yarally, Luis Cruz, Daniel Feitosa, June Sallou, Arie van Deursen:
Batching for Green AI - An Exploratory Study on Inference. CoRR abs/2307.11434 (2023) - [i38]Patrick Altmeyer, Arie van Deursen, Cynthia C. S. Liem:
Explaining Black-Box Models through Counterfactuals. CoRR abs/2308.07198 (2023) - [i37]Patrick Altmeyer, Giovan Angela, Aleksander Buszydlik, Karol Dobiczek, Arie van Deursen, Cynthia C. S. Liem:
Endogenous Macrodynamics in Algorithmic Recourse. CoRR abs/2308.08187 (2023) - [i36]Jonathan Katzy, Maliheh Izadi, Arie van Deursen:
On the Impact of Language Selection for Training and Evaluating Programming Language Models. CoRR abs/2308.13354 (2023) - [i35]Elvan Kula, Eric Greuter, Arie van Deursen, Georgios Gousios:
Dynamic Prediction of Delays in Software Projects using Delay Patterns and Bayesian Modeling. CoRR abs/2309.12449 (2023) - [i34]Lorena Poenaru-Olaru, Natalia Karpova, Luis Cruz, Jan S. Rellermeyer, Arie van Deursen:
Maintenance Techniques for Anomaly Detection AIOps Solutions. CoRR abs/2311.10421 (2023) - [i33]Patrick Altmeyer, Mojtaba Farmanbar, Arie van Deursen, Cynthia C. S. Liem:
Faithful Model Explanations through Energy-Constrained Conformal Counterfactuals. CoRR abs/2312.10648 (2023) - [i32]Ali Al-Kaswan, Maliheh Izadi, Arie van Deursen:
Traces of Memorisation in Large Language Models for Code. CoRR abs/2312.11658 (2023) - 2022
- [j58]Chandra Shekhar Maddila, Nachiappan Nagappan, Christian Bird, Georgios Gousios, Arie van Deursen:
ConE: A Concurrent Edit Detection Tool for Large-scale Software Development. ACM Trans. Softw. Eng. Methodol. 31(2): 22:1-22:26 (2022) - [j57]Elvan Kula, Eric Greuter, Arie van Deursen, Georgios Gousios:
Factors Affecting On-Time Delivery in Large-Scale Agile Software Development. IEEE Trans. Software Eng. 48(9): 3573-3592 (2022) - [c177]Lorena Poenaru-Olaru, Luis Cruz, Arie van Deursen, Jan S. Rellermeyer:
Are Concept Drift Detectors Reliable Alarming Systems? - A Comparative Study. IEEE Big Data 2022: 3364-3373 - [c176]Arumoy Shome, Luís Cruz, Arie van Deursen:
Data smells in public datasets. CAIN 2022: 205-216 - [c175]Haiyin Zhang, Luís Cruz, Arie van Deursen:
Code smells for machine learning applications. CAIN 2022: 217-228 - [c174]Sara Salimzadeh, Ujwal Gadiraju, Claudia Hauff, Arie van Deursen:
Exploring the Feasibility of Crowd-Powered Decomposition of Complex User Questions in Text-to-SQL Tasks. HT 2022: 154-165 - [c173]Kevin Anderson, Denise Visser, Jan-Willem Mannen, Yuxiang Jiang, Arie van Deursen:
Challenges in Applying Continuous Experimentation: A Practitioners' Perspective. ICSE (SEIP) 2022: 107-114 - [c172]Mitchell Olsthoorn, Dimitri Michel Stallenberg, Arie van Deursen, Annibale Panichella:
SynTest-Solidity: Automated Test Case Generation and Fuzzing for Smart Contracts. ICSE-Companion 2022: 202-206 - [c171]Bart van Oort, Luis Cruz, Babak Loni, Arie van Deursen:
"Project smells" - Experiences in Analysing the Software Quality of ML Projects with mllint. ICSE (SEIP) 2022: 211-220 - [c170]Matthías Páll Gissurarson, Leonhard Applis, Annibale Panichella, Arie van Deursen, David Sands:
PROPR: Property-Based Automatic Program Repair. ICSE 2022: 1768-1780 - [c169]Mitchell Olsthoorn, Arie van Deursen, Annibale Panichella:
Guiding Automated Test Case Generation for Transaction-Reverting Statements in Smart Contracts. ICSME 2022: 163-174 - [c168]Ching-Chi Chuang, Luís Cruz, Robbert van Dalen, Vladimir Mikovski, Arie van Deursen:
Removing dependencies from large software projects: are you really sure? SCAM 2022: 105-115 - [c167]Chandra Shekhar Maddila, Suhas Shanbhogue, Apoorva Agrawal, Thomas Zimmermann, Chetan Bansal, Nicole Forsgren, Divyanshu Agrawal, Kim Herzig, Arie van Deursen:
Nalanda: a socio-technical graph platform for building software analytics tools at enterprise scale. ESEC/SIGSOFT FSE 2022: 1246-1256 - [d11]Ali Al-Kaswan, Toufique Ahmed, Maliheh Izadi, Anand Ashok Sawant, Prem Devanbu, Arie van Deursen:
BinT5: Binary Code Summarisation Model. Zenodo, 2022 - [d10]Ali Al-Kaswan, Toufique Ahmed, Maliheh Izadi, Anand Ashok Sawant, Prem Devanbu, Arie van Deursen:
CAPYBARA: Decompiled Binary Functions and Related Summaries. Zenodo, 2022 - [d9]Leonhard Applis, Annibale Panichella, Arie van Deursen:
Reproduction: Assessing Robustness of ML-Based Program Analysis Tools using Metamorphic Program Transformations. Version 1.0. Zenodo, 2022 [all versions] - [d8]Leonhard Applis, Annibale Panichella, Arie van Deursen:
Reproduction: Assessing Robustness of ML-Based Program Analysis Tools using Metamorphic Program Transformations. Version 1.0. Zenodo, 2022 [all versions] - [d7]Leonhard Applis, Annibale Panichella, Arie van Deursen:
Reproduction: Assessing Robustness of ML-Based Program Analysis Tools using Metamorphic Program Transformations. Version 1.1. Zenodo, 2022 [all versions] - [d6]Mitchell Olsthoorn, Arie van Deursen, Annibale Panichella:
Replication package of "Guiding Automated Test Case Generation for Transaction-Reverting Statements in Smart Contracts". Zenodo, 2022 - [i31]Bart van Oort, Luis Cruz, Babak Loni, Arie van Deursen:
"Project smells" - Experiences in Analysing the Software Quality of ML Projects with mllint. CoRR abs/2201.08246 (2022) - [i30]Jiyang Zhang, Chandra Shekhar Maddila, Ram Bairi, Christian Bird, Ujjwal Raizada, Apoorva Agrawal, Yamini Jhawar, Kim Herzig, Arie van Deursen:
Using Large-scale Heterogeneous Graph Representation Learning for Code Review Recommendations. CoRR abs/2202.02385 (2022) - [i29]Arumoy Shome, Luis Cruz, Arie van Deursen:
Data Smells in Public Datasets. CoRR abs/2203.08007 (2022) - [i28]Haiyin Zhang, Luis Cruz, Arie van Deursen:
Code Smells for Machine Learning Applications. CoRR abs/2203.13746 (2022) - [i27]Maliheh Izadi, Pooya Rostami Mazrae, Tom Mens, Arie van Deursen:
LinkFormer: Automatic Contextualised Link Recovery of Software Artifacts in both Project-based and Transfer Learning Settings. CoRR abs/2211.00381 (2022) - [i26]Lorena Poenaru-Olaru, Luis Cruz, Arie van Deursen, Jan S. Rellermeyer:
Are Concept Drift Detectors Reliable Alarming Systems? - A Comparative Study. CoRR abs/2211.13098 (2022) - 2021
- [j56]Mark Haakman, Luis Cruz, Hennie Huijgens, Arie van Deursen:
AI lifecycle models need to be revised. Empir. Softw. Eng. 26(5): 95 (2021) - [j55]Jeanderson Cândido, Maurício Aniche, Arie van Deursen:
Log-based software monitoring: a systematic mapping study. PeerJ Comput. Sci. 7: e489 (2021) - [j54]Alexandre Perez, Rui Abreu, Arie van Deursen:
A Theoretical and Empirical Analysis of Program Spectra Diagnosability. IEEE Trans. Software Eng. 47(2): 412-431 (2021) - [c166]Bart van Oort, Luis Cruz, Maurício Aniche, Arie van Deursen:
The Prevalence of Code Smells in Machine Learning projects. WAIN@ICSE 2021: 35-42 - [c165]Pouria Derakhshanfar, Xavier Devroey, Gilles Perrouin, Andy Zaidman, Arie van Deursen:
Summary of Search-based Crash Reproduction using Behavioral Model Seeding. ICST 2021: 281 - [c164]Elvan Kula, Arie van Deursen, Georgios Gousios:
Modeling Team Dynamics for the Characterization and Prediction of Delays in User Stories. ASE 2021: 991-1002 - [c163]Leonhard Applis, Annibale Panichella, Arie van Deursen:
Assessing Robustness of ML-Based Program Analysis Tools using Metamorphic Program Transformations. ASE 2021: 1377-1381 - [c162]Jeanderson Cândido, Jan Haesen, Maurício Aniche, Arie van Deursen:
An Exploratory Study of Log Placement Recommendation in an Enterprise System. MSR 2021: 143-154 - [i25]Chandra Shekhar Maddila, Nachiappan Nagappan, Christian Bird, Georgios Gousios, Arie van Deursen:
ConE: A Concurrent Edit Detection Tool for Large ScaleSoftware Development. CoRR abs/2101.06542 (2021) - [i24]Jeanderson Cândido, Jan Haesen, Maurício Finavaro Aniche, Arie van Deursen:
An Exploratory Study of Log Placement Recommendation in an Enterprise System. CoRR abs/2103.01755 (2021) - [i23]Bart van Oort, Luis Cruz, Maurício Finavaro Aniche, Arie van Deursen:
The Prevalence of Code Smells in Machine Learning projects. CoRR abs/2103.04146 (2021) - [i22]Vivek Arora, Enrique Larios Vargas, Maurício Aniche, Arie van Deursen:
Secure Software Engineering in the Financial Services: A Practitioners' Perspective. CoRR abs/2104.03476 (2021) - [i21]Chandra Shekhar Maddila, Apoorva Agrawal, Thomas Zimmermann, Nicole Forsgren, Kim Herzig, Arie van Deursen:
Nalanda: A Socio-Technical Graph for Building Software Analytics Tools at Enterprise Scale. CoRR abs/2110.08403 (2021) - 2020
- [j53]Mozhan Soltani, Pouria Derakhshanfar, Xavier Devroey, Arie van Deursen:
A benchmark-based evaluation of search-based crash reproduction. Empir. Softw. Eng. 25(1): 96-138 (2020) - [j52]Pouria Derakhshanfar, Xavier Devroey, Gilles Perrouin, Andy Zaidman, Arie van Deursen:
Search-based crash reproduction using behavioural model seeding. Softw. Test. Verification Reliab. 30(3) (2020) - [j51]Kristín Fjóla Tómasdóttir, Mauricio Finavaro Aniche, Arie van Deursen:
The Adoption of JavaScript Linters in Practice: A Case Study on ESLint. IEEE Trans. Software Eng. 46(8): 863-891 (2020) - [j50]Mozhan Soltani, Annibale Panichella, Arie van Deursen:
Search-Based Crash Reproduction and Its Impact on Debugging. IEEE Trans. Software Eng. 46(12): 1294-1317 (2020) - [c161]Pouria Derakhshanfar, Xavier Devroey, Andy Zaidman, Arie van Deursen, Annibale Panichella:
Crash reproduction using helper objectives. GECCO Companion 2020: 309-310 - [c160]Pouria Derakhshanfar, Xavier Devroey, Andy Zaidman, Arie van Deursen, Annibale Panichella:
Good Things Come In Threes: Improving Search-based Crash Reproduction With Helper Objectives. ASE 2020: 211-223 - [c159]Mitchell Olsthoorn, Arie van Deursen, Annibale Panichella:
Generating Highly-structured Input Data by Combining Search-based Testing and Grammar-based Fuzzing. ASE 2020: 1224-1228 - [c158]Pouria Derakhshanfar, Xavier Devroey, Annibale Panichella, Andy Zaidman, Arie van Deursen:
Botsing, a Search-based Crash Reproduction Framework for Java. ASE 2020: 1278-1282 - [c157]Hennie Huijgens, Ayushi Rastogi, Ernst Mulders, Georgios Gousios, Arie van Deursen:
Questions for data scientists in software engineering: a replication. ESEC/SIGSOFT FSE 2020: 568-579 - [d5]Pouria Derakhshanfar, Xavier Devroey, Andy Zaidman, Arie van Deursen, Annibale Panichella:
Replication package of "Good Things Come In Threes: Improving Search-based Crash Reproduction With Helper Objectives". Zenodo, 2020 - [i20]Pouria Derakhshanfar, Xavier Devroey, Annibale Panichella, Andy Zaidman, Arie van Deursen:
Towards Integration-Level Test Case Generation Using Call Site Information. CoRR abs/2001.04221 (2020) - [i19]Mark Haakman, Luis Cruz, Hennie Huijgens, Arie van Deursen:
AI Lifecycle Models Need To Be Revised. An Exploratory Study in Fintech. CoRR abs/2010.02716 (2020) - [i18]Hennie Huijgens, Ayushi Rastogi, Ernst Mulders, Georgios Gousios, Arie van Deursen:
Questions for Data Scientists in Software Engineering: A Replication. CoRR abs/2010.03165 (2020) - [i17]Chandra Shekhar Maddila, Sai Surya Upadrasta, Chetan Bansal, Nachiappan Nagappan, Georgios Gousios, Arie van Deursen:
Nudge: Accelerating Overdue Pull Requests Towards Completion. CoRR abs/2011.12468 (2020)
2010 – 2019
- 2019
- [j49]Marco di Biase, Magiel Bruntink, Arie van Deursen, Alberto Bacchelli:
The effects of change decomposition on code review - a controlled experiment. PeerJ Comput. Sci. 5: e193 (2019) - [j48]Markus Voelter, Bernd Kolb, Tamás Szabó, Daniel Ratiu, Arie van Deursen:
Lessons learned from developing mbeddr: a case study in language engineering with MPS. Softw. Syst. Model. 18(1): 585-630 (2019) - [c156]Sohon Roy, Arie van Deursen, Felienne Hermans:
Perceived Relevance of Automatic Code Inspection in End-User Development: A Study on VBA. EASE 2019: 167-176 - [c155]Marco di Biase, Ayushi Rastogi, Magiel Bruntink, Arie van Deursen:
The delta maintainability model: measuring maintainability of fine-grained code changes. TechDebt@ICSE 2019: 113-122 - [c154]Hennie Huijgens, Eric Greuter, Jerry Brons, Evert A. van Doorn, Ioannis Papadopoulos, Francisco Morales Martinez, Mauricio Finavaro Aniche, Otto Visser, Arie van Deursen:
Factors affecting cloud infra-service development lead times: a case study at ING. ICSE (SEIP) 2019: 233-242 - [c153]