Automated GUI Testing Professors and Supervisors in Germany | ApplySharif

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Sam Malekمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Sam Malek is a Professor in the Department of Informatics at the University of California, Irvine's School of Information and Computer Sciences, where he directs the Software Engineering and Analysis Laboratory. Previously serving as Director of the Institute for Software Research (2018-2022), his academic leadership spans software engineering research and institutional management. His research centers on software engineering with specialized expertise in software analysis and testing , mobile computing , security , software architecture , and accessible computing . Malek's work consistently focuses on developing practical techniques and tools for constructing, analyzing, and maintaining large-scale software systems, with recent emphasis on accessibility challenges in mobile and web environments. His publication trends reveal a strategic shift toward accessible computing since 2020, where he pioneered frameworks like Ma11y for web accessibility testing and Groundhog for mobile app crawling. Earlier work established foundations in energy testing (2020), GUI input generation (2021), and architectural analysis, demonstrating methodological evolution from core software engineering to human-centered accessibility solutions. ACM SIGSOFT test-of-time award (2020) National Science Foundation CAREER award (2013) GMU Emerging Researcher/Scholar/Creator award (2013) GMU Computer Science Department Outstanding Faculty Research Award (2011) Malek serves on editorial boards for ACM Transactions on Software Engineering and Methodology and ACM Transactions on Autonomous and Adaptive Systems , while frequently acting as a software expert witness in intellectual property litigation. His research group actively recruits PhD students through UCI's Software Engineering PhD program, with current projects focusing on AI-driven accessibility solutions and mobile testing frameworks. The Software Engineering and Analysis Laboratory under his direction maintains strong industry connections through sponsored research and tool development, particularly in accessibility testing and mobile application quality assurance.

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Thomas Lembergerمشاهده پروفایل

پژوهشگر

Ludwig Maximilian University of MunichGermany

Thomas Lemberger is a researcher in the Department of Computer Science at Ludwig-Maximilians-Universität München (LMU Munich), contributing to the Software and Computational Systems Lab. He specializes in software verification, formal methods, and automated testing, with a focus on improving tool efficiency and scalability. His work includes extensions to CPAchecker, such as distributed summary synthesis and cooperative verification approaches, as well as developing user-friendly tools like CoVeriTeam GUI. His research interests involve integrating verification into build systems and IDEs, optimizing verification workflows, and exploring hybrid techniques that combine testing and formal methods. He has actively participated in competitions like SV-COMP and Test-Comp, contributing tools like PRTest and Nacpa. His projects aim to reduce tool restarts, enhance fault localization, and streamline verification processes through parallel portfolio analyses. Thomas mentors students on topics related to verification tool development, test-case generation, and open-source software. His contributions are supported by grants from the DFG (CONVEY, COOP, IDEFIX), emphasizing cooperative verification and scalable analysis. Recent work focuses on enabling developers to use verification tools seamlessly within their existing workflows.

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Ralf Hagemannمشاهده پروفایل

مدرس

Osnabrück University of Applied SciencesGermany

Ralf Hagemann is a Lecturer/Research Associate at Osnabrück University of Applied Sciences, specifically within the Faculty of Engineering and Computer Science . His academic work combines Embedded Systems , Software Engineering , and innovative teaching methods like Problem-Based Learning . He actively develops educational hardware and tools for engineering education. Embedded Systems Board design (STMNucleo32-Baseboard) Problem-oriented curriculum development for computer science students Qt-based visualization frameworks for algorithm training His research spans geometric algorithms (2013 dissertation), digital signal processing (1991 thesis), and domain-specific programming languages (1997 PIPL invention). Recent publications focus on multicultural engineering education and cost-effective product development . As a part-time faculty member , he leads technical workshops and contributes to European Project Semester initiatives. His 1991 Diplomarbeit at Fachhochschule Bielefeld laid foundations for his work in hardware-software integration . He regularly demonstrates his MpC-Bildschirmstellwerk software at international model railway exhibitions (2008-2016) and has published in journals like MIBA digital Extra and Eisenbahn Kurier .

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Lingling Fanمشاهده پروفایل

دانشیار

Max Planck Institute for Security and PrivacyGermany

Lingling Fan is an Associate Professor (100 Young Academic Leaders of Nankai University) at Nankai University, China. Her research focuses on software security analysis, software testing and analysis, and big data-driven analysis, with significant contributions to mobile application security, particularly in Android security and accessibility. Her research interests include: Software Security Analysis, with emphasis on mobile application security and vulnerability detection Software Testing and Analysis, particularly for Android applications and accessibility issues Big Data-driven Analysis for security and quality assessment of software systems Dr. Fan's publication record shows strong trends in automated security testing, vulnerability detection in open-source ecosystems, and accessibility analysis for mobile applications. Her work spans multiple disciplines including software engineering, security, and human-computer interaction, with a particular focus on practical applications for Android ecosystem and measurable real-world impact. Her notable scientific awards include: ACM SIGSOFT Distinguished Paper Award (ASE 2022) ACM SIGSOFT Distinguished Paper Award (ICSE 2021) ACM SIGSOFT Distinguished Paper Award (ICSE 2018) Research Tool Award at NASAC 2018 National Scholarship from The Ministry of Education, China (2018) ACM SIGSOFT CAPS Award (ASE 2018) Dr. Fan has served in various academic service roles including as a program committee member for major conferences such as ASE, ICSE, FSE, and ISSRE. She has also been a reviewer for prestigious journals including IEEE Transactions on Information Forensics and Security (TIFS), IEEE Transactions on Dependable and Secure Computing (TDSC), IEEE Transactions on Software Engineering (TSE), and ACM Transactions on Software Engineering and Methodology (TOSEM).

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Guoqiang Liمشاهده پروفایل

دانشیار

Max Planck Institute for Security and PrivacyGermany

Dr. Guoqiang Li is an Associate Professor in the School of Computer Science at Shanghai Jiao Tong University, where he conducts research at the intersection of formal methods, programming languages, and security. His academic journey includes prior positions as Assistant Professor (2009-2013) and subsequent promotion to Associate Professor (2014-present) at the same institution. He has held international appointments including a postdoctoral fellowship at Nagoya University (2008-2009), an academic visit at the University of Oxford (2015-2016), and a Guest Associate Professorship at Kyushu University's Research and Development Center for Smart Mobility (2016-2020). Dr. Li earned his B.S. from Taiyuan University of Technology (2001), M.S. from Shanghai Jiao Tong University (2005), and Ph.D. from Japan Advanced Institute of Science and Technology (2008). His educational background reflects a strong foundation in both Chinese and Japanese academic traditions. His research focuses on formal verification, programming language theory, zero-knowledge proofs, knowledge reasoning, and intelligent system verification and security. Over the past decade, his work has evolved from traditional formal methods applied to timed automata and process calculi to contemporary topics including neural network verification, zero-knowledge proof systems, and the application of large language models to program analysis. His publication record demonstrates a clear progression toward addressing verification challenges in increasingly complex modern systems. Dr. Li's recent publications reveal a strategic research trajectory: early work centered on timed automata and formal verification of concurrent systems, while current research addresses the verification of AI systems, zero-knowledge cryptographic protocols, and LLM-enhanced program analysis. This evolution reflects his commitment to applying rigorous formal methods to emerging computational challenges. Distinguished Paper Award at ICSE 2020 for 'Unblind Your Apps: Predicting Natural-Language Labels for Mobile GUI Components by Deep Learning' Consistent publication in top-tier venues including ASE, ICSE, FSE, and OOPSLA Recognition through multiple National Natural Science Foundation of China (NSFC) grants as Principal Investigator Dr. Li actively contributes to the academic community as a Senior Member of the China Computer Federation, Deputy Director of Theoretical Computer Science for the Shanghai Computer Society, and committee member for multiple technical organizations. He serves as Organization Chair for SEKM'20-22 and FMAC'17, Publicity Chair for TASE'21-23, and has participated in program committees for numerous international conferences. His teaching portfolio includes undergraduate and graduate courses in algorithm design, mathematical foundations, and scientific writing, demonstrating his commitment to both theoretical computer science education and practical application.

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Mark Harmanمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Mark Harman is a part-time Professor of Software Engineering at University College London's Department of Computer Science within the Faculty of Engineering Sciences, while working full-time as a Research Scientist at Meta Platforms in the Instagram Product Performance team. He previously served as head of Software Engineering at UCL and director of its CREST centre from 2006 to 2017 before joining Meta when his startup Majicke was acquired in 2017. Harman's research spans multiple domains of software engineering, with particular emphasis on Search Based Software Engineering (SBSE), which he co-founded in 2001. His work has evolved to include LLM-based software engineering, software testing, program analysis, and bias mitigation in machine learning systems. He has made significant contributions to automated testing through systems like Sapienz and WW that have been deployed at scale at Meta. His publication record shows a clear evolution from traditional software testing and analysis toward increasingly sophisticated integration of machine learning techniques. Recent work demonstrates strong focus on addressing fairness challenges in ML systems, improving test reliability in continuous integration environments, and exploring the applications of large language models in software engineering tasks. This reflects both his ability to identify emerging challenges and his commitment to practical, industry-relevant research. IEEE Harlan Mills Award (2019) ACM Outstanding Research Award (2019) Fellowship of the Royal Academy of Engineering (2020) Harman maintains a unique bridge between academia and industry, having co-founded the Simulation-Based Testing team at Meta and previously directing UCL's CREST research centre. His work on Sapienz grew from his startup Majicke and has had significant industrial impact while maintaining strong academic foundations. He frequently participates in academic conferences as both contributor and committee member, demonstrating ongoing commitment to the research community despite his industry position. At Meta, Harman works within the Instagram Product Performance team, building on his earlier work with the Simulation-Based Testing team where he co-developed platforms for client- and server-side testing. His research on cyber-cyber digital twins represents an innovative application of simulation techniques to virtual software systems rather than physical ones.

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Shin Hongمشاهده پروفایل

دانشیار

Max Planck Institute for Security and PrivacyGermany

Shin Hong is an Associate Professor at the School of Computer Science, Chungbuk National University (CBNU) in South Korea. He leads the SDEV lab (소프트웨어 개발검증 연구실) and maintains active roles in major software engineering conferences including ASE 2025 (Local Arrangement Co-Chair), ICST 2026 (General Co-Chair), and SSBSE 2025 (General Chair). His research focuses on Software Testing, Automated Debugging, and Program Analyses , with specific expertise in test case generation, debugging automation, and static/dynamic/neural program analysis techniques. Dr. Hong's work bridges theoretical advances with practical applications, as evidenced by his industrial case study with SAP HANA. Analysis of his recent publications reveals strong trends in fuzzing techniques (ZigZagFuzz, BUGOSS), regression bug benchmarking, mutation analysis, and GUI test case repair. His research demonstrates increasing sophistication in combining traditional software engineering approaches with machine learning methods for test optimization and fault diagnosis. Research Focus Areas: Advanced test generation techniques Automated debugging and fault localization Machine learning applications in software testing Empirical evaluation of testing techniques Dr. Hong actively contributes to the academic community through program committee service at top conferences and mentorship of graduate students at CBNU. His leadership roles in major conferences reflect his standing in the software engineering research community.

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Sen Chenمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Sen Chen is a Professor at Nankai University, holding positions in both the College of Cryptology and Cyber Science and the College of Computer Science. He leads the Nankai Software Security Laboratory (NKSSecLab) and is a member of Professor Zheli Liu's research group. Previously, he served as a tenured associate professor and research professor at Tianjin University (2021-2024), and as a research assistant professor at Nanyang Technological University (NTU), Singapore. Dr. Chen's research focuses on software security and software supply chain security, with particular emphasis on vulnerability analysis and malware detection. His work spans multiple domains including mobile security, AI security, open-source security, and intelligent software development and testing. His research has led to significant contributions in automated security vulnerability detection, software composition analysis, and security tool development for various platforms including Android, Java, and blockchain systems. Analysis of Dr. Chen's recent publications (2023-2025) reveals a strong focus on software supply chain security, with particular attention to vulnerability detection and remediation in open-source ecosystems. His work demonstrates expertise in applying advanced machine learning techniques to security problems, especially in the context of Android applications and containerized environments. There's a clear trajectory toward addressing emerging challenges in AI security and large language model supply chains, reflecting his ability to adapt research directions to evolving technological landscapes. ACM SIGSOFT Distinguished Paper Award (FSE 2024) ACM SIGSOFT Distinguished Paper Award (ASE 2023) First Place of the 13th Challenge Cup China College Students' Entrepreneurship Competition ACM SIGSOFT Distinguished Paper Award (ICSE 2023) Prototype Research Tool Award 2nd Place (Freestyle) in CCF ChinaSoft 2022 First Place of The 8th China International College Students' 'Internet+' Innovation and Entrepreneurship Competition ACM SIGSOFT Distinguished Paper Award (ASE 2022) ACM China Rising Star Award (ACM Tianjin Council) ACM SIGSOFT Distinguished Paper Award (ICSE 2021) First Class of Progress of Science and Technology Prize of Tianjin, 2020 Dr. Chen has successfully secured funding from multiple prestigious sources including key R&D programs, general and pre-research projects of the National Natural Science Foundation of China, and the Populus euphratica Forest Fund. His theoretical research has been applied by major companies such as State Grid, China Automotive Industry Corporation, and Huawei. He has mentored students to win national gold medals in both the 'Internet Plus' and Challenge Cup programs, demonstrating his commitment to student development and practical application of research. Dr. Chen leads NKSSecLab (Nankai Software Security Laboratory), which focuses on cutting-edge research in software security and supply chain security. The lab has developed several notable tools including SCTruster (a digital trust chain platform for software supply chain security) and LiDetector. The lab maintains strong international collaborations with institutions like Nanyang Technological University in Singapore and has established itself as a leading research group in software security within China.

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Philippe A. Palanqueمشاهده پروفایل

استاد

University of TrierGermany

Philippe A. Palanque is affiliated with Université Toulouse III - Paul Sabatier and has made significant contributions to the field of Human-Computer Interaction (HCI) , particularly in Interactive Systems Engineering , Dependability in Automation , and Formal Methods . His work spans Safety-Critical Systems , Task Modeling , and User Experience (UX) enhancement through interdisciplinary collaboration. Philippe has co-authored numerous studies on Human-AI Team Coordination , Dependable GUI Engineering , and Cybersecurity Training frameworks, often involving students like Célia Martinie and Axel Carayon . His recent publications (2025–2024) focus on Hybrid Automation and AI Integration in interactive design. Key research areas include Formal Verification (e.g., Event-B models), Feedforward Usability for GUI widgets, and Human Error Analysis in safety contexts. He actively participates in workshops like EICS and CHI , addressing challenges in Automation Transparency and Worker Well-Being . His work bridges Academic Research and Industry Applications , particularly in Healthcare Rehabilitation and Manufacturing Control Rooms .

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Yuetian Maoمشاهده پروفایل

پژوهشگر

Technical University of MunichGermany

Yuetian Mao is a Doctoral Candidate and Research Associate at the Technical University of Munich (TUM), affiliated with the TUM School of Computation, Information and Technology (CIT). He holds a Master's degree in Software Engineering from Shanghai Jiao Tong University (2020-2023) and a Bachelor's degree in the same field from the same institution (2016-2020). His research focuses on Intelligent Software Engineering and Query Refinement , particularly in the application of large language models (LLMs) to code search and optimization tasks. His work addresses challenges in Code Vulnerability Detection , GUI Testing Simulation , and LLM-based Tool Use for software development. Recent publications analyzed include topics in Code Search , Query Reformulation , HiveQL Anti-patterns , and LLM-enhanced Software Engineering . His research also intersects with Human-Centric AI , Accessibility Testing , and Automated GUI Repair . Scientific Awards : Hypergryph Scholarship (2021.11) The First Prize Graduate Study Scholarship (2020.9, 2021.9, 2022.9) Yuetian is part of the Chair of Software Engineering & AI at TUM's Heilbronn campus, contributing to projects in Model Context Protocols , Generative Engine Optimization , and EU AI Act Compliance research.

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Tingting Hanمشاهده پروفایل

مدرس

RWTH Aachen UniversityGermany

Tingting Han is a Lecturer in Computer Science at Birkbeck, University of London since October 2013. She holds a BSc and MEng in Computer Science from Nanjing University (2003, 2006) and a PhD from RWTH Aachen University and University of Twente (2009), supervised by Joost-Pieter Katoen. Prior to her current role, she was a postdoc at RWTH Aachen University (2009–2011) and a research assistant at the University of Oxford (2011–2013) under the VERIWARE project. Her research focuses on formal verification of probabilistic systems, machine learning applications in verification, and software model checking. She has contributed to advancements in adversarial robustness, code generation, and automated analysis of probabilistic programs. Her work integrates formal methods with machine learning to enhance software correctness and security. Han has taught courses such as 'Problem Solving for Programming', 'Big Data Analytics using R', and 'Introduction to Programming'. She actively participates in academic service, including PC memberships in QAPL 2014 and SAC SVT 2015–2017.

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Jieshan Chenمشاهده پروفایل

پژوهشگر

Technical University of MunichGermany

Jieshan Chen is a Researcher at CSIRO's Data61 , Australia, and a Dieter Schwarz Fellow at the Institute for Advanced Study (TUM-IAS) under the mentorship of Prof. Chunyang Chen. His research bridges software engineering and human-AI interaction , focusing on dark pattern detection , UI design automation , and mobile accessibility enhancement . Education: PhD in Computer Science from Australian National University. His work leverages LLM-based agents to address challenges in responsible software development by design , with publications in top-tier venues like ICSE , ASE , and UIST . Notable awards include the CSIRO SCS Early Career in Science Award (2024) and Women in Science Career Award (2023) . His research trends highlight advancements in AI-assisted mobile app development and ethical user interface design , contributing to fields like software security and human-centered AI . Scientific Awards: CSIRO SCS Biannual Awards - Early Career in Science Award 2024 CSIRO SCS Biannual Awards - Women in Science Career Award 2023 ACM SIGSOFT Distinguished Paper Award (ICSE2020)

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Zhe Liuمشاهده پروفایل

استادیار

Max Planck Institute for Security and PrivacyGermany

Zhe Liu is an Assistant Scientist at the Institute of Software, Chinese Academy of Sciences, and is affiliated with the University of Chinese Academy of Sciences. With a PhD from the University of Chinese Academy of Sciences, Liu focuses on innovative research at the intersection of software engineering, mobile testing, and artificial intelligence. Liu's research interests span multiple areas including: Software Engineering Mobile Testing Deep Learning Human-Computer Interaction Machine Learning Computer Vision UI Testing Crowd Testing Liu applies AI and lightweight program analysis technology in several key directions: AI/LLM-assisted automated mobile app development (requirement elicitation, app GUI testing, usability, bug replay) Human-machine collaborative testing (testing guides for testers) AI-empowered mining of software repositories (issue report mining) Liu has published 15 papers at top international Software Engineering and Human-Computer Interaction conferences/journals (CCF-A) with over 1,300 Google Scholar citations. The research shows a strong trend toward leveraging large language models for mobile app testing, with significant contributions in automated GUI testing, crash reproduction, and text input generation. Notable scientific achievements include: ACM Student Research Competition (SRC) 2023 Grand Finals Winners, 1st Place, Graduate Category Best Paper Honourable Mention in CHI'24 ACM Student Research Competition (SRC) at ICSE 2022, 1st Place ACM Student Research Competition (SRC) at ASE 2020, 1st Place Excellent Doctoral Dissertation of Chinese Academy of Sciences in 2024 Liu has served as a program committee member for ASE 2025 and has been involved in multiple research projects funded by the National Key Research and Development Program of China, National Natural Science Foundation of China, and Populus Innovation Research Funding. Current research focuses on advancing the integration of large language models with mobile application testing frameworks to improve app quality and user experience.

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Chunyang Chenمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Chunyang Chen is a Professor at the School of CIT, Technical University of Munich (TUM), Germany. He maintains an active research profile in software engineering with a focus on applying data analysis and artificial intelligence techniques to software development processes. His primary research interests include Software Engineering , Applied Data Analysis , Deep Learning , and Human-Computer Interaction . Dr. Chen is particularly known for his work in applying data analysis to automated software development and mining software repositories, with significant contributions in mobile application testing, GUI testing, and leveraging Large Language Models for software engineering tasks. His recent publications (2024-2026) demonstrate a strong focus on integrating Large Language Models with software testing methodologies, particularly for mobile applications. The research trends show increasing sophistication in using multimodal LLMs, dynamic memory techniques, and retrieval augmentation to improve automated testing capabilities. Dr. Chen maintains an active presence in the software engineering research community, serving on program committees for major conferences including ASE, ICSE, and ESEC/FSE. He has also delivered keynote speeches on mobile application testing with Large Language Models, highlighting his thought leadership in this emerging area.

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Dan Haoمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Professor Dan Hao is a distinguished faculty member at the Institute of Software, School of Computer Science, Peking University, where he has established himself as a leading researcher in software engineering. His extensive service to the academic community includes membership on the Steering Committee for The International Conference on Automated Software Engineering (ASE) since 2021, The ACM SIGSOFT International Symposium on Software Testing and Analysis since 2025, and The International Systems and Software Product Line Conference (SPLC) from 2018-2022. He has served as Program Co-Chair for multiple major conferences including ISSTA 2027, ICSME 2025, ICST 2023, SANER 2022, and ASE 2021. Professor Hao received his Bachelor's degree from Harbin Institute of Technology in 2002 and completed his Ph.D. at Peking University in 2008, followed by post-doctoral research at the same institution until 2009. His academic journey reflects a deep commitment to advancing software engineering research and education in China. Professor Hao's research primarily focuses on software testing and debugging, program comprehension, and software maintenance. His work has significantly contributed to compiler testing, fault localization, regression testing, and automated program repair. He has pioneered approaches in compiler auto-tuning, test-case prioritization, and history-guided testing techniques. His research bridges theoretical foundations with practical applications, addressing real-world challenges in large-scale software systems, particularly in online service environments. His publication record demonstrates a consistent trajectory of high-impact research in top-tier software engineering venues. Professor Hao's work shows increasing integration of machine learning techniques with traditional software engineering problems, particularly evident in his recent publications on LLM applications for code generation, neural theorem proving, and contrastive learning for vulnerability detection. His research maintains strong connections between theoretical rigor and practical applicability in industrial settings. ACM SIGSOFT Distinguished Paper Award for PDCAT: Preference-Driven Compiler Auto-Tuning at FSE 2025 Distinguished Paper Award for Formalizing, Mechanizing, and Verifying Class-Based Refinement Types at ECOOP 2024 ACM SIGSOFT Distinguished Paper Award for History-Guided Configuration Diversification for Compiler Test-Program Generation at ASE 2019 ACM SIGSOFT Distinguished Paper Award for History-driven Build Failure Fixing: How Far Are We? at ISSTA 2019 As an advisor, Professor Hao has mentored numerous graduate students, currently supervising 9 Ph.D. students and 7 Master's students. His former students have gone on to prestigious positions at institutions including King's College London, Tianjin University, Fudan University, and major technology companies like Huawei and China Construction Bank. His academic leadership extends through editorial roles as Deputy Editor-in-Chief of Software Testing, Verification and Reliability (STVR) and membership on the editorial boards of several premier journals including ACM Transactions on Software Engineering and Methodology, ACM Computing Surveys, and Empirical Software Engineering. Professor Hao leads a vibrant research group at Peking University's Institute of Software, focusing on cutting-edge problems at the intersection of traditional software engineering and artificial intelligence. His team actively collaborates with both academic institutions and industry partners to address practical challenges in software development and maintenance processes.

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