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ORCIDKim Herzig
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- affiliation: Saarland University, Saarbrücken, Germany
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2020 – today
- 2023
[c31]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- [c30]Sumit Asthana
, Hitesh Sajnani, Elena Voyloshnikova, Birendra Acharya, Kim Herzig:
A Case Study of Developer Bots: Motivations, Perceptions, and Challenges. ESEC/SIGSOFT FSE 2023: 1268-1280 - 2022
- [c29]Kim Herzig, Luke Ghostling, Maximilian Grothusmann, Sascha Just, Nora Huang, Alan Klimowski, Yashasvini Ramkumar, Myles McLeroy, Kivanç Muslu, Hitesh Sajnani, Varsha Vadaga:
Microsoft CloudMine: Data Mining for the Executive Order on Improving the Nation's Cybersecurity. MSR 2022: 639 - [c28]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 - [i4]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) - 2021
- [c27]An Ju, Hitesh Sajnani, Scot Kelly, Kim Herzig:
Research Tools, Survey Responses, and Interview Analysis from a Case Study of Onboarding Software Teams at Microsoft. ICSE (Companion Volume) 2021: 224 - [c26]An Ju, Hitesh Sajnani, Scot Kelly, Kim Herzig:
A Case Study of Onboarding in Software Teams: Tasks and Strategies. ICSE 2021: 613-623 - [i3]An Ju, Hitesh Sajnani, Scot Kelly, Kim Herzig:
A Case Study of Onboarding in Software Teams: Tasks and Strategies. CoRR abs/2103.05055 (2021) - [i2]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)
2010 – 2019
- 2019
- [j2]Byoungju Choi, María José Escalona Cuaresma, Kim Herzig:
Summary of the 14th edition of the IEEE/ACM Workshop on Automation of Software Test (AST). ACM SIGSOFT Softw. Eng. Notes 44(3): 53 (2019) - [c25]Michele Tufano, Hitesh Sajnani, Kim Herzig:
Towards predicting the impact of software changes on building activities. ICSE (NIER) 2019: 49-52 - [e1]Byoungju Choi, María José Escalona, Kim Herzig:
Proceedings of the 14th International Workshop on Automation of Software Test, AST@ICSE 2019, May 27, 2019, Montreal, QC, Canada. IEEE / ACM 2019, ISBN 978-1-7281-2237-3 [contents] - [i1]Michele Tufano, Hitesh Sajnani, Kim Herzig:
Towards Predicting the Impact of Software Changes on Building Activities. CoRR abs/1901.07142 (2019) - 2018
- [c24]Kim Herzig:
Testing and continuous integration at scale: limits, costs, and expectations. SBST@ICSE 2018: 38 - [c23]Carlene Lebeuf, Elena Voyloshnikova, Kim Herzig, Margaret-Anne D. Storey:
Understanding, Debugging, and Optimizing Distributed Software Builds: A Design Study. ICSME 2018: 496-507 - 2017
- [c22]Christopher Theisen, Kim Herzig, Brendan Murphy, Laurie A. Williams:
Risk-Based Attack Surface Approximation: How Much Data Is Enough? ICSE-SEIP 2017: 273-282 - 2016
- [j1]Kim Herzig, Sascha Just, Andreas Zeller:
The impact of tangled code changes on defect prediction models. Empir. Softw. Eng. 21(2): 303-336 (2016) - [c21]Sascha Just, Kim Herzig, Jacek Czerwonka, Brendan Murphy:
Switching to Git: The Good, the Bad, and the Ugly. ISSRE 2016: 400-411 - [p4]Kim Herzig:
There's never enough time to do all the testing you want. Perspectives on Data Science for Software Engineering 2016: 91-95 - [p3]Sascha Just, Kim Herzig:
Gotchas from mining bug reports. Perspectives on Data Science for Software Engineering 2016: 261-265 - 2015
- [c20]Patrick Morrison, Kim Herzig, Brendan Murphy, Laurie A. Williams:
Challenges with applying vulnerability prediction models. HotSoS 2015: 4:1-4:9 - [c19]Kim Herzig, Nachiappan Nagappan:
Empirically Detecting False Test Alarms Using Association Rules. ICSE (2) 2015: 39-48 - [c18]Christopher Theisen, Kim Herzig, Patrick Morrison, Brendan Murphy, Laurie A. Williams:
Approximating Attack Surfaces with Stack Traces. ICSE (2) 2015: 199-208 - [c17]Kim Herzig, Michaela Greiler, Jacek Czerwonka, Brendan Murphy:
The Art of Testing Less without Sacrificing Quality. ICSE (1) 2015: 483-493 - [c16]Michaela Greiler, Kim Herzig, Jacek Czerwonka:
Code Ownership and Software Quality: A Replication Study. MSR 2015: 2-12 - [c15]Kim Herzig, Sascha Just, Andreas Zeller:
It's Not a Bug, It's a Feature: How Misclassification Impacts Bug Prediction. Software Engineering & Management 2015: 103-104 - [c14]Kim Herzig, Nachiappan Nagappan:
The Impact of Test Ownership and Team Structure on the Reliability, Effectiveness of Quality Test Runs. Software Engineering & Management 2015: 105-106 - 2014
- [c13]Kim Herzig, Nachiappan Nagappan:
The impact of test ownership and team structure on the reliability and effectiveness of quality test runs. ESEM 2014: 2:1-2:10 - [c12]Kim Herzig:
Using Pre-Release Test Failures to Build Early Post-Release Defect Prediction Models. ISSRE 2014: 300-311 - [p2]Kim Herzig, Andreas Zeller:
Mining Bug Data - A Practitioner's Guide. Recommendation Systems in Software Engineering 2014: 131-171 - 2013
- [b1]Kim Sebastian Herzig:
Mining and untangling change genealogies. Saarland University, 2013 - [c11]Kim Herzig, Sascha Just, Andreas Zeller:
It's not a bug, it's a feature: how misclassification impacts bug prediction. ICSE 2013: 392-401 - [c10]Kim Herzig, Sascha Just, Andreas Rau, Andreas Zeller:
Predicting defects using change genealogies. ISSRE 2013: 118-127 - [c9]Kim Herzig, Andreas Zeller:
The impact of tangled code changes. MSR 2013: 121-130 - 2012
- [c8]Christian Holler, Kim Herzig, Andreas Zeller:
Fuzzing with Code Fragments. USENIX Security Symposium 2012: 445-458 - 2011
- [c7]Rahul Premraj, Kim Herzig:
Network Versus Code Metrics to Predict Defects: A Replication Study. ESEM 2011: 215-224 - [c6]Thomas Zimmermann, Nachiappan Nagappan, Kim Herzig, Rahul Premraj, Laurie A. Williams:
An Empirical Study on the Relation between Dependency Neighborhoods and Failures. ICST 2011: 347-356 - [c5]Kim Herzig, Andreas Zeller:
Mining Cause-Effect-Chains from Version Histories. ISSRE 2011: 60-69 - [p1]Kim Sebastian Herzig, Andreas Zeller:
Mining Your Own Evidence. Making Software 2011: 517-530 - 2010
- [c4]Kim Sebastian Herzig:
Capturing the long-term impact of changes. ICSE (2) 2010: 393-396 - [c3]Nachiappan Nagappan, Andreas Zeller, Thomas Zimmermann, Kim Herzig, Brendan Murphy:
Change Bursts as Defect Predictors. ISSRE 2010: 309-318
2000 – 2009
- 2009
- [c2]Tilman Holschuh, Markus Pauser, Kim Herzig, Thomas Zimmermann, Rahul Premraj, Andreas Zeller:
Predicting defects in SAP Java code: An experience report. ICSE Companion 2009: 172-181 - [c1]Kim Herzig, Andreas Zeller:
Mining the Jazz repository: Challenges and opportunities. MSR 2009: 159-162
Coauthor Index
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