Sven Amann

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Sven Amann

My research focuses on tools that help software developers to become more efficient and, at the same time, increase software quality.

Today, software developers often manually search the web for examples or documentation to solve the problems they face. This requires them to leave their IDEs and includes many redundant and tedious steps. Furthermore, it is often hard to judge the quality of the findings and to know when to stop searching for more information.

Previous work shows that Recommender Systems for Software Engineering (RSSEs) can successfully extract usage patterns and documentation from huge datasets. IDE integration of such tools saves developers much work and many context switches. The knowledge contained in the machine-learned recommendation models is based on far bigger datasets than any developer could possibly inspect by herself. The models effectively provide the wisdom of the crowd to software developers in their every-day work.

But RSSEs can do more than assist developers in writing code faster. My research focuses on strategies that help developer discover and avoid mistakes in using software libraries and frameworks.

Find out more about me and my work on sven-amann.de.

Projects

MUBench – A Benchmark for API-Misuse Detectors

Since about 2005, much research was dedicated API-misuse detection, i.e., to the automated discovery of incorrect API usages, using machine-learned specifications of correct usage. Unfortunately, evalations in the field have been conducted on varying datasets and with quite different settings, such that the empirical results on individual tools is hardly comparable. Therefore, we develop MUBench, a standardized and automated benchmarking infrastructure for static API-misuse detectors.

MUDetect (Eko Project)

I'm project lead of the Eko project. The project was part of the Software Campus, a program funded by the German government that supports young researchers and brings academia and industry together, from 2015 to 2017. We cooperated with DHL IT Services to develop our API-misuse detector MUDetect. MUDetect mines usage patterns from existing software code and detects violations in code under development. Since 2017, the project is continued at the STG.

Next-Generation API-Usage-Pattern Mining

Mining API-usage patterns is the foundation of many research approaches for next-generation assistance tools, like code recommenders or code-anomaly detectors. The quality of the detected patterns is crucial for the performance of these tools. In joint work with Dr. Tien N. Nguyen and Dr. Hoan A. Nguyen from Iowa State University and Dr. Sarah Nadi from the University of Alberta, I search for ways to improve state-of-the-art pattern mining and to automate the evaluation of alternative concepts.

KaVE Project

From 2013 to 2017, I was member of the KaVE project. The project was part of the Software Campus, a program funded by the German government that supports young researchers and brings academia and industry together, from 2013 to 2015. We cooperated with DATEV to develop a recommender system for Visual Studio/C#. The goal of the project is to enrich statically-mined code-recommendation models with feedback provided by experts. The project is led by Sebastian Proksch.

Reusable Evaluation Dataset

A major challenge in our field of research is to create reproducible results. One requirement is to use reusable date sets for the evaluation, however, this is often not the case. I have analyzed this problem in a recent paper together with Sebastian Proksch. We proposed the idea of a data repository for reusable and extensible datasets. We plan to continue this idea. Please get in contact with us if you are interested in a cooperation or to provide feedback.

Machine Learning for Bug Detection (ML4Bugs)

The idea behind “ML4Bugs” is to combine static analysis and machine learning to find bugs in software systems. With this approach, it is significantly easier to create new bug finders than to write a dedicated “bug detection” analysis. At the same time, predictions are much more precise about the location and the kind of bug than in classical “defect prediction”. This is joint work with Johannes Lerch, Michael Eichberg, Ervina Cergani, and Sebastian Proksch.

Contact

Committees

FSE'17 Tool Demonstrations
MSR'17 Mining Challenge
SANER'17

Open Theses

Currently no items available.

Ongoing Theses

Teaching

Term Courses
Winter 2017/18
Winter 2016/17
Summer 2016
Winter 2015/16
Summer 2015
Winter 2014/15
Winter 2013/14
Summer 2013

Publications

Group by: Date | Item type | No grouping
Jump to: 2018 | 2017 | 2016 | 2015 | 2014 | 2013 | 2009
Number of items: 19.

2018

Amann, Sven :
A Systematic Approach to Benchmark and Improve Automated Static Detection of Java-API Misuses.
 [Online-Edition: http://tuprints.ulb.tu-darmstadt.de/7422]
Technische Universität , Darmstadt
[PhD thesis], (2018)

Glanz, Leonid ; Amann, Sven ; Eichberg, Michael ; Reif, Michael ; Mezini, Mira
Tichy, Matthias ; Bodden, Eric ; Kuhrmann, Marco ; Wagner, Stefan ; Steghöfer, Jan-Philipp (eds.) :
CodeMatch: Obfuscation Won't Conceal Your Repackaged App.
 In: Software Engineering und Software Management 2018. Gesellschaft für Informatik , pp. 117-118.
[Book section], (2018)

Amann, Sven ; Nguyen, Hoan Anh ; Nadi, Sarah ; Nguyen, Tien ; Mezini, Mira :
A Systematic Evaluation of API-Misuse Detectors.
 In: IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
[Article], (2018)

2017

Beller, Moritz ; Gousios, Georgius ; Panichella, Annibale ; Proksch, Sebastian ; Amann, Sven ; Zaidman, Andy :
Developer Testing in the IDE: Patterns, Beliefs, and Behavior.
 In: IEEE Transactions on Software Engineering
[Article], (2017) (Im Druck)

Glanz, Leonid ; Amann, Sven ; Eichberg, Michael ; Reif, Michael ; Hermann, Ben ; Lerch, Johannes ; Mezini, Mira :
CodeMatch: Obfuscation Won’t Conceal Your Repackaged App.
 [Online-Edition: http://dl.acm.org/citation.cfm?id=3106305]
In: Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering. Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering Paderborn, Germany
[Conference or workshop item], (2017)

Proksch, Sebastian ; Nadi, Sarah ; Amann, Sven ; Mezini, Mira :
Enriching In-IDE Process Information with Fine-Grained Source Code History.
 In: International Conference on Software Analysis, Evolution, and Reengineering, 21-24 Feb 2017, Klagenfurt, Austria.
[Conference or workshop item], (2017)

Salvaneschi, Guido ; Proksch, Sebastian ; Amann, Sven ; Nadi, Sarah ; Mezini, Mira :
On the Positive Effect of Reactive Programming on Software Comprehension: An Empirical Study.
 [Online-Edition: http://ieeexplore.ieee.org/document/7827078/]
IEEE ISSN 1939-3520
[Journal], (2017) (Im Druck)

2016

Proksch, Sebastian ; Amann, Sven ; Nadi, Sarah ; Mezini, Mira :
Evaluating the Evaluations of Code Recommender Systems: A Reality Check.
 [Online-Edition: http://doi.acm.org/10.1145/2970276.2970330]
In: International Conference on Automated Software Engineering pp. 111-121. ISSN 978-1-4503-3845-5
[Article], (2016)

Amann, Sven ; Proksch, Sebastian ; Nadi, Sarah :
FeedBaG: An Interaction Tracker for Visual Studio.
 [Online-Edition: http://sven-amann.de/publications/feedbag.pdf]
In: International Conference on Program Comprehension, May 16–17, 2016, Austin, Texas, USA. In: ICPC .
[Conference or workshop item], (2016)

Amann, Sven ; Nadi, Sarah ; Nguyen, Hoan A. ; Nguyen, Tien N. ; Mezini, Mira :
MUBench: A Benchmark for API-Misuse Detectors.
 In: 13th International Conference on Mining Software Repositories, May 14–15, 2016, Austin, Texas, USA. In: MSR'16 .
[Conference or workshop item], (2016)

Proksch, Sebastian ; Amann, Sven ; Nadi, Sarah ; Mezini, Mira :
A Dataset of Simplified Syntax Trees for C#.
 [Online-Edition: http://doi.acm.org/10.1145/2901739.2903507]
In: 13th International Conference on Mining Software Repositories, May 14–15, 2016, Austin, Texas, USA. In: MSR'16 .
[Conference or workshop item], (2016)

Amann, Sven ; Proksch, Sebastian ; Nadi, Sarah ; Mezini, Mira :
A Study of Visual Studio Usage in Practice.
 [Online-Edition: http://dx.doi.org/10.1109/SANER.2016.39]
In: 23rd IEEE International Conference on Software Analysis, Evolution, and Reengineering, 14-18 March 2016, Osaka, Japan. In: SANER '16 .
[Conference or workshop item], (2016)

2015

Amann, Sven ; Beyer, Stefanie ; Kevic, Katja ; Gall, Harald
Meyer, Bertrand ; Nordio, Martin (eds.) :
Software Mining Studies: Goals, Approaches, Artifacts, and Replicability.
 In: Advances in the theory and practice of software engineering - LASER 2013-2014. Springer , pp. 121-159.
[Book section], (2015)

2014

Proksch, Sebastian ; Amann, Sven ; Mezini, Mira :
Towards Standardized Evaluation of Developer-Assistance Tools.
 [Online-Edition: http://dx.doi.org/10.1145/2593822.2593827]
Proceedings of the 4th International Workshop on Recommendation Systems for Software Engineering - RSSE 2014
[Conference or workshop item], (2014)

Amann, Sven ; Proksch, Sebastian ; Mezini, Mira :
Method-Call Recommendations from Implicit Developer Feedback.
 [Online-Edition: http://dx.doi.org/10.1145/2593728.2593730]
Proceedings of the 1st International Workshop on CrowdSourcing in Software Engineering - CSI-SE 2014
[Conference or workshop item], (2014)

Salvaneschi, Guido ; Amann, Sven ; Proksch, Sebastian ; Mezini, Mira :
An empirical study on program comprehension with reactive programming.
 [Online-Edition: http://dx.doi.org/10.1145/2635868.2635895]
Proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering - FSE 2014
[Conference or workshop item], (2014)

2013

Amann, Sven :
Code Completion Based on Implicit User Feedback.
 Technische Universität Darmstadt
[Master thesis], (2013)

2009

Amann, Sven :
Spezifikation und Codegenerierung von Sicherheitsautomaten.
 TU Darmstadt
[Bachelor thesis], (2009)

Amann, Sven :
Spezifikation und Codegenerierung von Sicherheitsautomaten.
[Other], (2009)

This list was generated on Fri Sep 21 05:37:48 2018 CEST.

Finished Theses