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For the full list of publications see below or check my profile on DBLP and Google Scholar
This paper reports on the findings of 17 semi-structured interviews with developers, architects, and managers in 11 companies to identify microservice API evolution strategies and challenges in practice. In total, we identified six strategies and six challenges for REpresentational State Transfer (REST) and event-driven communication via message brokers. The strategies mainly focus on API backward compatibility, versioning, and close collaboration between teams. The challenges include change impact analysis efforts, ineffective communication of changes, and consumer reliance on outdated versions, leading to API design degradation. We defined two important problems in microservice API evolution resulting from the challenges and their coping strategies: tight organizational coupling and consumer lock-in. To mitigate these two problems, we propose automating the change impact analysis and investigating effective communication of changes as open research directions.
A. Lercher, J. Glock, C. Macho, and M. Pinzger (pdf)
In this paper, we present PASDA, a partition-based semantic differencing approach with best effort classification of undecided cases. It uses symbolic execution (Symbolic PathFinder) to check the equivalence of all paths found in two versions of a Java program to be either equivalent or non-equivalent, as well as a best effort classification for undecided cases. These are cases, for which the solver (Z3) used by PASDA cannot find a solution or PASDA times out. A comparison with three state-of-the-art approaches showed that PASDA outperforms them in terms of accuracy by 3%-7% on program-level. Moreover, PASDA provides partition-level results also for undecided cases and we briefly discuss the value of this information in three potential uses cases.
J. Glock, J. Pichler, and M. Pinzger (pdf)
In this paper, we propose DValidator, an approach that considers dependencies on project level and method call level for validating dependencies in build configurations. First, DValidator encodes a project’s dependency graph as specified in a build configuration and its call graph into a representation using Answer Set Programming (ASP). Then it uses Clingo as a solver to detect problems with the dependencies in that build configuration. In a preliminary evaluation with four open source Maven projects we show that our approach can detect selected dependency smells in less than eight seconds. Next steps concern the investigation of our approach for automatically improving dependency configurations, such as automatically repairing dependency smells and conflicts. Editor’s note: Open Science material was validated by the Journal of Systems and Software Open Science Board.
C. Macho, F. Oraze, and M. Pinzger (pdf)
This paper presents BUILDDIFF, an approach to extract detailed build changes from MAVEN build files and classify them into 143 change types. We then present two studies using the build changes extracted from 144 open source Java projects to study the frequency and time of build changes. The results show that the top-10 most frequent change types account for 51% of the build changes. Among them, changes to version numbers and changes to dependencies of the projects occur most frequently. We also observe frequently co-occurring changes, such as changes to the source code management definitions, and corresponding changes to the dependency management system and the dependency declaration. Furthermore, our results show that build changes frequently occur around release days. In particular, critical changes, such as updates to plu- gin configuration parts and dependency insertions, are performed before a release day.
C. Macho, S. Beyer, S. McIntosh, and M. Pinzger (pdf)
CertGraph: Towards a Comprehensive Knowledge Graph for Cloud Security Certifications (pdf)
S. Schöberl, C. Banse, V. Geist, I. Kunz, and M. Pinzger. Proceedings of the International Conference on Model Driven Engineering Languages and Systems, pp. 76-77, ACM, 2024.
PentestGPT: An LLM-empowered Automatic Penetration Testing Tool (pdf)
G. Deng, Y. Liu, V. M. Vilches, P. Liu, Y. Li, Y. Xu, T. Zhang, Y. Liu, M. Pinzger, and S. Rass. Proceedings of the USENIX Security Symposium, pp. 847-864, USENIX, 2024.
Microservice API Evolution in Practice: A Study on Strategies and Challenges (pdf)
A. Lercher, J. Glock, C. Macho, and M. Pinzger. Journal of Systems and Software (JSS), vol. 215, Elsevier, 2024.
PASDA: A Partition-based Semantic Differencing Approach with Best Effort Classification of Undecided Cases (pdf)
J. Glock, J. Pichler, and M. Pinzger. Journal of Systems and Software (JSS), vol. 213, Elsevier, 2024.
DValidator: An approach for validating dependencies in build configurations (pdf)
C. Macho, F. Oraze, and M. Pinzger. Journal of Systems and Software (JSS), vol. 209, Elsevier, 2024.
RobotPerf: An Open-Source, Vendor-Agnostic, Benchmarking Suite for Evaluating Robotics Computing System Performance (pdf)
V. M. Vilches, J. Jabbour, Y.-S. Hsiao, Z. Wan, M. Crespo-Álvarez, M. Stewart, J. M. Reina-Muñoz, P. Nagras, G. Vikhe, M. Bakhshalipour, M. Pinzger, S. Rass, S. Panigrahi, G. Corradi, N. Roy, P. B. Gibbons, S. M. Neuman, B. Plancher, and V. J. Reddi. Proceedings of the International Conference on Robotics and Automation (ICRA), pp. 8288-8297, IEEE, 2024.
PentestGPT: An LLM-empowered Automatic Penetration Testing Tool (pdf)
G. Deng, Y. Liu, V. M. Vilches, P. Liu, Y. Li, Y. Xu, T. Zhang, Y. Liu, M. Pinzger, and S. Rass. CoRR, , , 2023.
Incentive-Based Software Security: Fair Micro-Payments for Writing Secure Code (pdf)
S. Rass and M. Pinzger. CoRR, , , 2023.
ExploitFlow, cyber security exploitation routes for Game Theory and AI research in robotics (pdf)
V. M. Vilches, G. Deng, Y. Liu, M. Pinzger, and S. Rass. CoRR, , , 2023.
Hacking planned obsolescense in robotics, towards security-oriented robot teardown (pdf)
V. M. Vilches, A. Glera-Picón, U. A. Carbajo, S. Rass, M. Pinzger, F. Maggi, and E. Gil-Uriarte. Electronic Communication of the European Association of Software Science and Technology, vol. 80, , 2022.
Presentation: SymDefFix - Sound Automatic Repair Using Symbolic Execution (pdf)
T. M. Nazir and M. Pinzger. International KLEE Workshop on Symbolic Execution, , CoRR, 2022.
Robot teardown, stripping industrial robots for good (pdf)
V. M. Vilches, A. Glera-Picón, U. A. Carbajo, S. Rass, M. Pinzger, F. Maggi, and E. Gil-Uriarte. International Journal of Cyber Forensics and Advanced Threat Investigations, , Concept Techn Publishing, 2021.
Comparing fine-grained source code changes and code churn for bug prediction - A retrospective (pdf)
M. Pinzger, E. Giger, and H. C. Gall. ACM SIGSOFT Software Engineering Notes, vol. 46, no. 3, pp. 21-23, ACM, 2021.
Comprehending Spreadsheets: Which Strategies do Users Apply? (pdf)
K. M. Hodnigg, C. Macho, M. Pinzger, and D. Jannach. Proceedings of the International Conference on Program Comprehension (ICPC), pp. 386-390, IEEE, 2021.
A Cryptography-Powered Infrastructure to Ensure the Integrity of Robot Workflows (pdf)
B. Breiling, B. Dieber, M. Pinzger, and S. Rass. Journal of Cybersecurity and Privacy, vol 1, no. 1, pp. 93-118, MDPI, 2021.
The Nature of Build Changes: An Empirical Study of Maven-based Build Systems (pdf)
C. Macho, S. Beyer, S. McIntosh, and M. Pinzger. Empirical Software Engineering (EMSE), vol 26, no. 3, pp. 32, Springer, 2021.
A Method for the Joint Analysis of Numerical and Textual IT-System Data to Predict Critical System States (pdf)
P. Kubiak, S. Rass, M. Pinzger, and S. Schneider. Software Technologies. Communications in Computer and Information Science, vol. 1447, pp. 242-261, Springer, 2021.
Runtime Protection of Real-time Critical Control Applications against Known Threats (pdf)
M. T. Khan, M. Pinzger, D. Serpanos, and H. Shrobe. IEEE Design & Test, vol. 37, no. 6, pp. 88-95, IEEE, 2020.
IT-Application Behaviour Analysis: Predicting Critical System States on OpenStack using Monitoring Performance Data and Log Files (pdf)
P. Kubiak, S. Rass, and M. Pinzger. In Proceedings of the International Conference on Software Technologies (ICSOFT), pp. 589-596, SciTePress, 2020.
Leveraging Machine Learning for Software Redocumentation (pdf)
V. Geist, M. Moser, J. Pichler, S. Beyer, and M. Pinzger. In Proceedings of the International Conference on Software Analysis, Evolution and Reengineering (SANER), Industrial Track, pp. 622-626, IEEE, 2020.
Visualizing Evolution and Performance Metrics on Method-Level as Multivariate Data (pdf)
H. Tarner, V. Frick, M. Pinzger, and F. Beck. In Proceedings of the Seminar on Advanced Techniques & Tools for Software Evolution (SATToSE), vol. 2754, CEUR-WS.org, 2020.
Verifying Temporal Specifications of Java Programs (pdf)
F. Spegni, L. Spalazzi, G. Liva, M. Pinzger, and A. Bollin. Software Quality Journal (SQJ), vol. 28, no. 2, pp. 695-744, Springer, 2020.
Automatic Repair of Timestamp Comparisons (pdf)
G. Liva, M. T. Khan, M. Pinzger, F. Spegni, and L. Spalazzi. IEEE Transactions on Software Engineering (TSE), vol. 47, no. 11, pp. 2369-2381, IEEE, 2021.
What kind of questions do developers ask on Stack Overflow? A comparison of automated approaches to classify posts into question categories (pdf)
S. Beyer, C. Macho, M. Di Penta, and M. Pinzger. Journal of Empirical Software Engineering (EMSE), vol. 25, no. 3, pp. 2258-2301, Springer, 2020.
Semantics-Driven Extraction of Timed Automata from Java Programs (pdf)
G. Liva, M. T. Khan, and M. Pinzger. Journal of Empirical Software Engineering (EMSE), vol. 24, no. 5, pp. 3114–3150, Springer, 2019.
Can I Depend on You? Mapping the Dependency and Quality Landscape of ROS Packages (pdf)
M. Pichler, B. Dieber, and M. Pinzger. In Proceedings of the International Conference on Robotic Computing (IRC), 78-85, IEEE, 2019.
Exploring Visual Comparison of Multivariate Runtime Statistics
H. Tarner, V. Frick, M. Pinzger, and F. Beck. In Proceedings of the Symposium on Software Performance (SSP), to appear, GI Softwaretechnik-Trends, 2018.
Noise and Heterogeneity in Historical Build Data: An Empirical Study of Travis CI (pdf)
K. Gallaba, C. Macho, M. Pinzger, and S. McIntosh. In Proceedings of the International Conference on Automated Software Engineering (ASE), pp. 87-97, IEEE/ACM, 2018.
Generating Accurate and Compact Edit Scripts Using Tree Differencing (pdf)
V. Frick, T. Grassauer, F. Beck, and M. Pinzger. In Proceedings of the International Conference on Software Maintenance and Evolution (ICSME), pp. 264-274, IEEE, 2018.
DiffViz: A Diff Algorithm Independent Visualization Tool for Edit Scripts (pdf)
V. Frick, C. Wedenig, and M. Pinzger. In Proceedings of the International Conference on Software Maintenance and Evolution (ICSME), Tool Demo Track, pp. 705-709, IEEE, 2018.
Towards Model Checking Security of Real Time Java Software
F. Spegni, L.Spalazzi, G. Liva, and M. Pinzger. In Proceedings of the International Workshop on Security and High Performance Computing Systems (SHPCS), pp. 642-649, IEEE/ACM, 2018.
Automatically Classifying Posts into Question Categories on Stack Overflow (pdf)
S. Beyer, C. Macho, M. di Penta, and M. Pinzger. In Proceedings of the International Conference on Program Comprehension (ICPC), pp. 211-221, IEEE, 2018.
Modeling Time in Java Programs for Automatic Error Detection (pdf)
G. Liva, M. T. Khan, F. Spegni, L.Spalazzi, A. Bollin, and M. Pinzger. In Proceedings of the International Conference on Formal Methods in Software Engineering (FormaliSE), pp. 50-59, IEEE, 2018.
Co-Evolution Analysis of Production and Test Code by Learning Association Rules of Changes (pdf)
L. Vidács and M. Pinzger. In Proceedings of the International Workshop on Machine Learning Techniques for Software Quality Evaluation (MaLTeSQuE), pp. 31-36, IEEE, 2018.
FEVER: An Approach to Analyze Feature-Oriented Changes and Artefact Co-Evolution in Highly Configurable Systems (pdf)
N. Dintzner, A. van Deursen, and M. Pinzger. Journal of Empirical Software Engineering (EMSE), vol. 23, no. 2, pp. 905-952, Springer, 2018.
Automatically Repairing Dependency-Related Build Breakage (pdf)
C. Macho, S. McIntosh, and M. Pinzger. In Proceedings of the International Conference on Software Analysis, Evolution, and Reengineering (SANER), pp. 106-117, IEEE, 2018.
Extracting Timed Automata from Java Methods (pdf)
G. Liva, M. T. Khan, and M. Pinzger. In Proceedings of the International Working Conference on Source Code Analysis and Manipulation (SCAM), pp. 91-100, IEEE, 2017.
Guest Editorial: Mining Software Repositories (online)
R. Robbes, Y. Kamei, and M. Pinzger. Journal of Empirical Software Engineering (EMSE), vol. 22, no. 3, pp. 1143-1145, Springer, 2017.
Extracting Build Changes with BuildDiff (pdf)
C. Macho, S. McIntosh, and M. Pinzger. In Proceedings of the International Conference on Mining Software Repositories (MSR), pp. 368-378, IEEE/ACM, 2017.
Analysing the Linux Kernel Feature Model Changes Using FMDiff (pdf)
N. Dintzner, A. van Deursen, and M. Pinzger. Journal of Software & Systems Modeling, vol. 16, no. 1, pp. 55-76, Springer, 2017.
Extracting Parallel Control Flow Graphs with Synchronization Information from Java Programs (pdf)
G. Liva, F. Spegni, L. Spalazzi, A. Bollin, M. Pinzger. Technical Report, Alpen-Adria-Universität, , IEEE, 2017.
Guest Editorial: Mining Software Repositories (online)
M. Pinzger and S. Kim. Journal of Empirical Software Engineering (EMSE), vol. 21, no. 5, pp. 2033-2034, Springer, 2016.
Grouping Android Tag Synonyms on Stack Overflow (pdf)
S. Beyer and M. Pinzger. In Proceedings of the International Conference on Mining Software Repositories (MSR), pp. 430-440, IEEE/ACM, 2016.
FEVER: Extracting Feature-Oriented Changes from Commits (pdf)
N. Dintzner, A. van Deursen, and M. Pinzger. In Proceedings of the International Conference on Mining Software Repositories (MSR), EEE/ACM pp. 85-96, IEEE, 2016.
Predicting Build Co-Changes with Source Code Change and Commit Categories (pdf)
C. Macho, S. McIntosh, and M. Pinzger. In Proceedings of the International Conference on Software Analysis, Evolution, and Reengineering (SANER), pp. 541-551, IEEE, 2016. Candidate for Best Paper Award
XVIZIT: Visualizing Cognitive Units in Spreadsheets (pdf)
K. Hodnigg and M. Pinzger. In Proceedings of the Working Conference on Software Visualization, Tool Demo, pp. 210-214, IEEE, 2015.
Synonym Suggestion for Tags on Stack Overflow (pdf)
S. Beyer and M. Pinzger. In Proceedings of the International Conference on Program Comprehension (ICPC), pp. 94-103, IEEE, 2015.
Evaluating Feature Change Impact on Multi-Product Line Configurations Using Partial Information (pdf)
N. Dintzner, U. Kulesza, A. Van Deursen, and M. Pinzger. In Software Reuse for Dynamic Systems in the Cloud and Beyond, pp. 1-16, Lecture Notes in Computer Science, Springer, 2015.
Detecting and Refactoring Code Smells in Spreadsheet Formulas (pdf)
F. Hermans, M. Pinzger, and A. van Deursen. Journal of Empirical Software Engineering (EMSE), vol. 20, no. 2, pp. 549-575, Springer, 2015.
A Manual Categorization of Android App Development Issues Using Stack Overflow Posts (pdf)
S. Beyer and M. Pinzger. In Proceedings of the International Conference on Software Maintenance and Evolution, Early Research Achievements (ICSME ERA), pp. 531-535, IEEE, 2014.
Refactoring Fat Interfaces Using a Genetic Algorithm (pdf)
D. Romano, S. Raemaekers, and M. Pinzger. In Proceedings of the International Conference on Software Maintenance and Evolution (ICSME), pp. 351-360, IEEE, 2014. ICSME 2014 Best Paper award
A Genetic Algorithm to Find the Adequate Granularity for Service Interfaces (pdf)
D. Romano and M. Pinzger. In Proceedings of the World Congress on Services (SERVICES), pp. 478-485, IEEE, 2014.
An Exploratory Study of the Pull-Based Software Development Model (pdf)
G. Gousios, M. Pinzger, and A. van Deursen. In Proceedings of the International Conference on Software Engineering (ICSE), pp. 345-355, IEEE/ACM, 2014.
Special Issue: A Selection of Distinguished Papers from the 18th Working Conference on Reverse Engineering 2011 (online)
M. Pinzger and D. Poshyvanyk. Journal of Software: Evolution and Process, vol. 26, no. 1, pp. 1-2, John Wiley & Sons, 2014.
Studying Late Propagations in Code Clone Evolution Using Software Repository Mining (online)
H. H. Mui, A. Zaidman and M. Pinzger. In Electronic Communications of the EASST, vol. 63, EASST, 2014.
Extracting Feature Model Changes from the Linux Kernel Using FMDiff (pdf)
N. Dintzner, A. van Deursen and M. Pinzger. In Proceedings of the International Workshop on Variability Modelling of Software-intensive Systems (VAMOS), pp. 22:1–22:8, ACM, 2014.
Guest Editorial: Reverse Engineering (online)
M. Pinzger and G. Antoniol. Journal of Empirical Software Engineering (EMSE), vol. 18, no. 5, pp. 857-858, Springer, 2013.
Towards a Weighted Voting System for Q&A Sites (pdf)
D. Romano and M. Pinzger. In Proceedings of the International Conference on Software Maintenance, Early Research Achievements (ICSM ERA), pp. 268-271, IEEE, 2013.
Communication in Open Source Software Development Mailing Lists (pdf)
A. Guzzi, A. Bachelli, M. Lanza, M. Pinzger, and A. van Deursen. In Proceedings of the Working Conference on Mining Software Repositories (MSR), pp. 277-286, IEEE/ACM, 2013.
Data Clone Detection and Visualization in Spreadsheets (pdf)
F. Hermans, B. Sedee, M. Pinzger, and A. van Deursen. In Proceedings of the International Conference on Software Engineering (ICSE), pp. 292-301, IEEE/ACM, 2013. ACM SIGSOFT Distinguished Paper award
Analyzing the Impact of Antipatterns on Change-Proneness Using Fine-Grained Source Code Changes (pdf)
D. Romano, P. Raila, M. Pinzger, and F. Khomh. In Proceedings of the Working Conference on Reverse Engineering (WCRE), pp. 437-446, IEEE, 2012.
Detecting Code Smells in Spreadsheet Formulas (pdf)
F. Hermans, M. Pinzger, and A. van Deursen. In Proceedings of the International Conference on Software Maintenance (ICSM), pp. 409-418, IEEE, 2012.
Measuring Spreadsheet Formula Understandability (pdf)
F. Hermans, M. Pinzger, and A. van Deursen. In Proceedings of the European Spreadsheet Risks Interest Group Conference (EuSpRiG), , CoRR, 2012.
Method-Level Bug Prediction (pdf)
E. Giger, M. D’Ambros, M. Pinzger, H. C. Gall. In Proceedings of the International Symposium on Empirical Software Engineering and Measurement (ESEM), pp. 171-180, IEEE, 2012.
Analyzing the Evolution of Web Services using Fine-Grained Changes (pdf)
D. Romano and M. Pinzger. In Proceedings of the International Conference on Web Services (ICWS), Application and Experience Track, pp. 392-399, IEEE, 2012.
Can we Predict Types of Code Changes? An Empirical Analysis (pdf)
E. Giger, M. Pinzger, H. C. Gall. In Proceedings of the Working Conference on Mining Software Repositories (MSR), pp. 217-226, IEEE/ACM, 2012.
Detecting and Visualizing Inter-Worksheet Smells in Spreadsheets (pdf)
F. Hermans, M. Pinzger, and A. van Deursen. In Proceedings of the International Conference on Software Engineering (ICSE), pp. 441-451, IEEE/ACM, 2012.
Extracting Dynamic Dependencies between Web Services Using Vector Clocks (pdf)
D. Romano, M. Pinzger, and E. Bouwers. In Proceedings of the IEEE International Conference on Service-Oriented Computing and Applications (SOCA), pp. 1-8, IEEE, 2011.
Using Vector Clocks to Monitor Dependencies among Services at Runtime (pdf)
D. Romano and M. Pinzger. In Proceedings of the International Workshop on Quality Assurance for Service-based Applications (QASBA), pp. 1-4, ACM, 2011.
Using the Gini Coefficient for Bug Prediction in Eclipse (pdf)
E. Giger, M. Pinzger, H. C. Gall. In Proceedings of the International Workshop on Principles on Software Evolution, ERCIM Workshop on Software Evolution (IWPSE-EVOL), pp. 51-55, ACM, 2011.
Using Source Code Metrics to Predict Change-Prone Java Interfaces (pdf)
D. Romano and M. Pinzger. In Proceedings of the International Conference on Software Maintenance (ICSM), pp. 303-312, IEEE, 2011.
Breviz: Visualizing Spreadsheets using Dataflow Diagrams (pdf)
F. Hermans, M. Pinzger, A. van Deursen. In Proceedings of the European Spreadsheet Risks Interest Group Conference (EuSpRiG), , CoRR, 2011.
Collective Code Bookmarks for Program Comprehension (pdf)
A. Guzzi, L. Hattori, M. Lanza, M. Pinzger, and A. van Deursen. In Proceedings of the International Conference on Program Comprehension (ICPC), pp. 101-110, IEEE, 2011.
Comparing Fine-Grained Source Code Changes And Code Churn For Bug Prediction (pdf)
E. Giger, M. Pinzger, and H. C. Gall. In Proceedings of the Working Conference on Mining Software Repositories (MSR), pp. 83-92, IEEE/ACM, 2011. Candidate for MSR 2021 Most Influential Paper Award
Supporting Professional Spreadsheet Users by Generating Leveled Dataflow Diagrams (pdf)
F. Hermans, M. Pinzger, and A. van Deursen. In Proceedings of the International Conference on Software Engineering (ICSE), pp. 451-460, IEEE/ACM, 2011.
Combining Micro-Blogging and IDE Interactions to Support Developers in their Quests (pdf)
A. Guzzi, M. Pinzger, and A. van Deursen. In Proceedings of the International Conference on Software Maintenance, Early Research Achievements (ICSM ERA), pp. 1-5, IEEE, 2010.
Visual Patterns in Software Process Data (pdf)
P. Knab, M. Pinzger, and H. C. Gall. In Proceedings of the International Conference on Software Process (ICSP), pp. 222-233, Lecture Notes in Computer Science, Springer, 2010.
Automatically Extracting Class Diagrams from Spreadsheets (pdf)
F. Hermans, M. Pinzger, and A. van Deursen. In Proceedings of the European Conference on Object-Oriented Programming (ECOOP), pp. 52-75, Lecture Notes in Computer Science, Springer, 2010.
Adinda: A Knowledgable, Browser-Based IDE (pdf)
A. van Deursen, A. Mesbah, B. Cornelissen, A. Zaidman, M. Pinzger, and A. Guzzi. In Proceedings of the International Conference on Software Engineering, New Ideas and Emerging Results Track (ICSE NIER), pp. 203-206, ACM, 2010.
Predicting the Fix Time of Bugs (pdf)
E. Giger, M. Pinzger, and H. C. Gall. In Proceedings of the International Workshop on Recommendation Systems for Software Engineering (RSSE), pp. 52-56, ACM, 2010.
Software Evolution
A. Zaidman, M. Pinzger, A. van Deursen. In Encyclopedia of Software Engineering, P. A. Laplante (eds), pp. 1127-1137, Taylor & Francis, 2010.
Dynamic Analysis of Communication and Collaboration in OSS Projects (pdf)
M. Pinzger and H. C. Gall. In Collaborative Software Engineering, I. Mistrík, J. Grundy, A. van der Hoek, J. Whitehead (eds.), pp. 265-284, Springer, 2010.
Change Analysis with Evolizer and ChangeDistiller (pdf)
H. C. Gall, B. Fluri, and M. Pinzger. IEEE Software, vol. 26, no. 1, pp. 26-33, IEEE, 2009.
Domain-Specific Languages in Practice: A User Study on the Success Factors (pdf)
F. Hermans, M. Pinzger, and A. van Deursen. In Proceedings of the International Conference on Model Driven Engineering Languages and Systems (MODELS), pp. 423-437, Lecture Notes in Computer Science, Springer, 2009.
Smart Views for Analyzing Problem Reports: Tool Demo (pdf)
P. Knab, M. Pinzger, and H. C. Gall. In Proceedings of the European Software Engineering Conference (ESEC) and the ACM SIGSOFT Symposium on the Foundations of Software Engineering (FSE), Tool Demo Track, pp. 289-290, ACM, 2009.
Interactive Views for Analyzing Problem Reports (pdf)
P. Knab, B. Fluri, M. Pinzger, and H. C. Gall. In Proceedings of the International Conference on Software Maintenance (ICSM), pp. 527-530, IEEE, 2009.
Using Association Rules to Study the Co-Evolution of Production & Test Code (pdf)
Z. Lubsen, A. Zaidman, and M. Pinzger. In Proceedings of the Working Conference on Mining Software Repositories (MSR), pp. 151-154, IEEE, 2009.
Can Developer-Module Networks Predict Failures? (pdf)
M. Pinzger, N. Nagappan, and B. Murphy. In Proceedings of the International Symposium on Foundations of Software Engineering (FSE), pp. 2-12, ACM, 2008.
A Tool for Visual Understanding of Source Code Dependencies (pdf)
M. Pinzger, K. Gräfenhain, P. Knab, and H. C. Gall. In Proceedings of the International Conference on Program Comprehension (ICPC), pp. 254-259, IEEE, 2008.
Analyzing Software Repositories to Understand Software Evolution (pdf)
M. D’Ambros, H. C. Gall, M. Lanza, and M. Pinzger. In Software Evolution, T. Mens and S. Demeyer (eds.), pp. 37-67, Springer, 2008.
Software Evolution Analysis and Visualization
M. Pinzger, H. C. Gall, and M. Fischer. In Emerging Methods, Technologies, and Process Management in Software Engineering, A. De Lucia, F. Ferrucci, G. Tortora, M. Tucci (eds.), pp. 177-200, John Wiley & Sons, 2008.
Change Distilling: Tree Differencing for Fine-Grained Source Code Change Extraction (pdf)
B. Fluri, M. Würsch, M. Pinzger, and H. C. Gall. IEEE Transactions on Software Engineering (TSE), vol. 33, no. 11, pp. 725-743, IEEE, 2007.
Quality Assessment Based on Attribute Series of Software Evolution (pdf)
J. Ratzinger, H. C. Gall, and M. Pinzger. In Proceedings of the 14th Working Conference on Reverse Engineering (WCRE), pp. 80–89, IEEE, 2007.
EQ-Mine: Predicting Short-Term Defects for Software Evolution (pdf)
J. Ratzinger, M. Pinzger, and H. C. Gall. In Proceedings of the Fundamental Approaches to Software Engineering (FASE), pp. 12-26, Lecture Notes in Computer Science, Springer, 2007.
Improving Defect Prediction Using Temporal Features and Non Linear Models (pdf)
A. Bernstein, J. Ekanayake, and M. Pinzger. In Proceedings of the International Workshop on Principles of Software Evolution (IWPSE), pp. 11–18, IEEE, 2007.
“A Bug’s Life” Visualizing a Bug Database (pdf)
M. D’Ambros, M. Lanza, and M. Pinzger. In Proceedings of the 4th IEEE International Workshop on Visualizing Software for Understanding and Analysis (VisSoft), pp. 113-120, IEEE, 2007.
Relation of Code Clones and Change Couplings (pdf)
R. Geiger, B. Fluri, H. C. Gall, and M. Pinzger. In Proceedings of the Fundamental Approaches to Software Engineering (FASE), pp. 411-425, Lecture Notes in Computer Science, Springer, 2006.
TA-RE: An Exchange Language for Mining Software Repositories (pdf)
S. Kim, T. Zimmermann, M. Kim, A. Hassan, A. Mockus, T. Girba, M. Pinzger, E. J. Whitehead, Jr., and A. Zeller. In Proceedings of the International Workshop on Mining Software Repositories (MSR), pp. 22-25, ACM, 2006.
Detecting Similar Java Classes Using Tree Algorithms (pdf)
T. Sager, A. Bernstein, M. Pinzger, and C. Kiefer. In Proceedings of the International Workshop on Mining Software Repositories (MSR), pp. 65-71, ACM, 2006.
Predicting Defect Densities in Source Code Files with Decision Tree Learners (pdf)
P. Knab, M. Pinzger, and A. Bernstein. In Proceedings of the International Workshop on Mining Software Repositories (MSR), pp. 119-125, ACM, 2006.
Towards the Integration of Versioning Systems, Bug Reports and Source Code Meta-Models (pdf)
G. Antoniol, M. D. Penta, H. Gall, and M. Pinzger. Electronic Notes in Theoretical Computer Science (ENTCS), vol. 127, no. 3, pp. 87–99, Elsevier, 2005.
Towards an Integrated View on Architecture and its Evolution (pdf)
M. Pinzger, M. Fischer, and H. Gall. Electronic Notes in Theoretical Computer Science (ENTCS), vol. 127, no. 3, pp. 183–196, Elsevier, 2005.
Asset Recovery and Incorporation into Product Lines (pdf)
J. Knodel, I. John, D. Ganesan, M. Pinzger, F. Usero, J. L. Arciniegas, and C. Riva. In Proceedings of the 12th Working Conference on Reverse Engineering (WCRE), pp 120-129, IEEE, 2005.
Visualizing Multiple Evolution Metrics (pdf)
M. Pinzger, H. C. Gall, M. Fischer, and M. Lanza. In Proceedings of the ACM Symposium on Software Visualization (SoftVis), pp. 67-75, ACM, 2005.
CodeCrawler - An Information Visualization Tool for Program Comprehension (pdf)
M. Lanza, S. Ducasse, H. C. Gall, and M. Pinzger. In Proceedings of the International Conference on Software Engineering (ICSE), Tool Demo Track, pp. 672-673, IEEE, 2005.
Fine-Grained Analysis of Change Couplings (pdf)
B. Fluri, H. C. Gall, and M. Pinzger. In Proceedings of the 5th International Workshop on Source Code Analysis and Manipulation (SCAM), pp. 66-74, IEEE, 2005.
Architecture Recovery for Product Families (pdf)
M. Pinzger, H. C. Gall, J.-F. Girard, J. Knode, C. Riva, W. Pasman, C. Broerse, and J. G. Wijnstra. In Proceedings of the International Workshop on Product Family Engineering (PFE), pp. 332-351, Lecture Notes in Computer Science, Springer, 2004.
Abstracting Module Views from Source Code (pdf)
M. Pinzger, M. Fischer, M. Jazayeri, and H. C. Gall. In Proceedings of the International Conference on Software Maintenance (ICSM), Poster Track, pp. 533, IEEE, 2004.
TUAnalyzer - Analyzing Templates in C++ Code (pdf)
T. Gschwind, M. Pinzger, and H. C. Gall. In Proceedings of the Working Conference on Reverse Engineering (WCRE), pp. 48-57, IEEE, 2004.
Analyzing and Relating Bug Report Data for Feature Tracking (pdf)
M. Fischer, M. Pinzger, and H. C. Gall. In Proceedings of the Working Conference on Reverse Engineering (WCRE), pp. 90-99, IEEE, 2003.
Populating a Release History Database from Version Control and Bug Tracking Systems (pdf)
M. Fischer, M. Pinzger, and H. C. Gall. In Proceedings of the International Conference on Software Maintenance (ICSM), pp. 23-32, IEEE, 2003. ICSM 2013 Most Influential Paper award
Improving Fact Extraction of Framework-Based Software Systems (pdf)
J. Knodel and M. Pinzger. In Proceedings of the Working Conference on Reverse Engineering (WCRE), pp.186-195, IEEE, 2003.
Analyzing and Understanding Architectural Characteristics of COM+ Components (pdf)
M. Pinzger, J. Oberleitner, and H. C. Gall. In Proceedings of the International Workshop on Program Comprehension (IWPC), pp. 54-63, IEEE, 2003.
Using Run-Time Data for Program Comprehension (pdf)
T. Gschwind, J. Oberleitner, and M. Pinzger. In Proceedings of the International Workshop on Program Comprehension (IWPC), pp. 245-250, IEEE, 2003.
Revealer: A lexical Pattern Matcher for Architecture Recovery (pdf)
M. Pinzger, M. Fischer, H. C. Gall, M. Jazayeri. In Proceedings of the Working Conference on Reverse Engineering (WCRE), pp. 170-178, IEEE, 2002.
Pattern-Supported Architecture Recovery (pdf)
M. Pinzger and H. C. Gall. In Proceedings of the International Workshop on Program Comprehension (IWPC), pp. 53-61, IEEE, 2002.
ArchView - Analyzing Evolutionary Aspects of Complex Software Systems (pdf)
M. Pinzger. Doctoral Thesis, Vienna University of Technology, 2005.
Reengineering von Flugplanungssoftware (in German)
M. Pinzger. Master’s Thesis, EADS Dornier GmbH and Vienna University of Technology, 2001.