Pouria Derakhshanfar

Ph.D. Candidate

Delft University of Technology

My name is Pouria Derakhshanfar. I am a Ph.D. candidate in the Software Engineering Research Group (SERG) of the Delft University of Technology. I started my Ph.D. in 2017 under the supervision of Prof. Andy Zaidman and Prof. Arie van Deursen. As part of the EU Software Testing AMPlification (STAMP) project, I developed new search-based approaches for crash replication and test amplification in a DevOps context. Currently, I am involved in the collaboration between TU Delft and the ING research lab.

Interests

Software Engineering
Software Testing
Artificial Intelligence
Search-based Software Testing
Machine Learning

Education

MSc in Software Engineering, 2017
Sharif University of Technology
BSc in Software Engineering, 2014
Kharazmi University

Latest news

ASE 2020 paper is accepted (2020-07): Super happy that our paper Good Things Come In Threes: Improving Search-based Crash Reproduction With Helper Objectives has been accepted at The 35th IEEE/ACM International Conference on Automated Software Engineering.
SSBSE 2020 challenge paper is accepted (2020-07): our challenge paper An Application of Model Seeding to Search-based Unit Test Generation for Gson got accepted at the 12th Symposium on Search-Based Software Engineering.
Two papers are accepted to SSBSE 2020 (2020-07): Our papers It is not Only About Control Dependent Nodes: Basic Block Coverage for Search-Based Crash Reproduction and Commonality-Driven Unit Test Generation have been accepted for publication in the proceedings of the 12th Symposium on Search-Based Software Engineering.
ASE 2020 tool demo accepted (2020-07): Our Botsing tool demonstration has been accepted at The 35th IEEE/ACM International Conference on Automated Software Engineering. ( demo video).
ICSE 2020 (2020-07): Our paper A benchmark-based evaluation of search-based crash reproduction will be presented in the journal first track of the 42nd International Conference on Software Engineering ( presentation video).
Crash fault localization master thesis (2020-06): S. Popping is defending his master thesis Automated crash fault localization.
JCrashPack2.0 master thesis (2020-06): B. Cherry is defending his master thesis JCrashPack2.0: Search-based crash reproduction hardness analysis.
CUB-TG master thesis (05/2020): B. Evers is defending his master thesis Unit test generation for common and uncommon behaviors.
Fit2Crash master thesis (03/2020): S. Xiang is defending his master thesis Specializing Fitness Functions for Crash Reproduction.
STVR paper accepted (02/2020): Our paper Search-based Crash Reproduction using Behavioral Model Seeding has been accepted for publication in the Software Testing Verification and Reliability journal.
ING presentation (02/2020): I am going to presdent our newly developed tools and technologies for applying search-based techniques for automated test generation at ING’s AI for Fintech Research (AFR) lab.

Projects

Software Tesing AMPlification (STAMP)

A collaborative effort between 10 organizations, from 6 European countries to advance the state of the art in DevOps and automatic software testing

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My Tools

Botsing (2018-current): An open-source search-based crash reproduction framework.
Cling (2019-current): An open-source search-based test generation tool for class integration testing.
ExRunner (2018-current): A bash-based infrastructure for running multiple instances of crash reproduction tools on 200 hard-to-reproduce crashes. ExRunner can be used to perform empirical evaluations of different crash reproduction techniques.