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Profile Name

johannschumann

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Publications: 3
Edited: 0

Aliases

Schumann, Johann
J. Schumann
Schumann, J.
Schumann
Johann Schumann

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Johann Schumann's Profile

Publications

Unidentified Publications

Publications with a 'Johann Schumann' as author, editor, or advisor:

Parallel Inference MachinesWolfgang Bibel, Franz J. Kurfess, K. Aspetsberger, P. Hintenaus, Johann Schumann. ac 1987: 185-226
An Empirical Evaluation of Automated Theorem Provers in Software CertificationEwen Denney, Bernd Fischer, Johann Schumann. ijait, 15(1):81-108, 2006. [doi]
Using the Theorem Prover SETHEO for Verifying the Development of a Communication Protocol in FOCUS: A Case StudyJohann Schumann. tableaux 1995: 338-352
Automated Theorem Proving in Generation, Verification, and Certification of Safety Critical CodeJohann Schumann. tableaux 2003: 3 [doi]
Verification and Validation Approaches for Model-Based Software EngineeringJohann Schumann, Katerina Goseva-Popstojanova. MoDELS 2019: 514-518 [doi]
Towards software health management with bayesian networksJohann Schumann, Ole J. Mengshoel, Ashok N. Srivastava, Adnan Darwiche. FSE 2010: 331-336 [doi]
Analysis of Air Traffic Track Data with the AutoBayes Synthesis SystemJohann Schumann, Karen Cate, Alan Lee. LOPSTR 2011: 21-36 [doi]
PARTHEO: A High-Performance Parallel Theorem ProverJohann Schumann, Reinhold Letz. cade 1990: 40-56
Application of Neural Networks in High Assurance Systems: A SurveyJohann Schumann, Pramod Gupta, Yan Liu 0003. In Johann Schumann, Yan Liu 0003, editors, Applications of Neural Networks in High Assurance Systems. Volume 268 of Studies in Computational Intelligence, pages 1-19, Springer, 2010. [doi]
The Ten Lockheed Martin Cyber-Physical Challenges: Formalized, Analyzed, and ExplainedAnastasia Mavridou, Hamza Bourbouh, Dimitra Giannakopoulou, Thomas Pressburger, Mohammad Hejase, Pierre-Loïc Garoche, Johann Schumann. RE 2020: 300-310 [doi]
Software health management: a necessity for safety critical systemsAshok N. Srivastava, Johann Schumann. isse, 9(4):219-233, 2013. [doi]
R2U2: Monitoring and Diagnosis of Security Threats for Unmanned Aerial SystemsJohann Schumann, Patrick Moosbrugger, Kristin Y. Rozier. RV 2015: 233-249 [doi]
Learning Heuristics for a Theorem Prover Using Back PropagationWolfgang Ertel, Johann Schumann, Christian B. Suttner. ogai 1989: 87-95
SETHEO Goes Software Engineering: Application of ATP to Software ReuseBernd Fischer, Johann Schumann. cade 1997: 65-68
Automatic Debugging Support for UML DesignsJohann Schumann. AADEBUG 2000: [doi]
An Implementation of a PROLOG-like Theorem Prover based on the Connection MethodStefan Bayerl, Elmar Eder, Franz J. Kurfess, Reinhold Letz, Johann Schumann. aimsa 1986: 29-36
Bridging the Gap Between Requirements and Simulink Model AnalysisAnastasia Mavridou, Hamza Bourbouh, Pierre-Loïc Garoche, Dimitra Giannakopoulou, Thomas Pressburger, Johann Schumann. refsq 2020: [doi]
The Anatomy of Software Changes and Bugs in Autonomous Operating SystemKaterina Goseva-Popstojanova, Denny Hood, Johann Schumann, Noble Nkwocha. compsac 2023: 28-38 [doi]
Applying AutoBayes to the Analysis of Planetary Nebulae ImagesBernd Fischer, Johann Schumann. ASE 2003: 337-342 [doi]
Parallel Theorem Provers - An OverviewJohann Schumann. Dagstuhl 1992: 26-50
Synthesizing Certified CodeMichael W. Whalen, Johann Schumann, Bernd Fischer. FM 2002: 431-450 [doi]
SiCoTHEO - Simple competitive parallel theorem provers based on SETHEOJohann Schumann. In James Geller, Hiroaki Kitano, Christian B. Suttner, editors, Parallel Processing for Artificial Intelligence 3. Volume 20 of Machine Intelligence and Pattern Recognition, pages 231-246, Elsevier, 1997. [doi]
SiCoTHEO: Simple Competitive Parallel Theorem ProversJohann Schumann. cade 1996: 240-244
Automated theorem proving in software engineeringJohann Schumann. Springer, 2001. [doi]
Who Guards the Guardians? - Toward V&V of Health Management Software - (Short Paper)Johann Schumann, Ashok N. Srivastava, Ole J. Mengshoel. RV 2010: 399-404 [doi]
Certification Support for Automatically Generated ProgramsJohann Schumann, Bernd Fischer, Michael W. Whalen, Jon Whittle. hicss 2003: 337 [doi]
AutoBayes: a system for generating data analysis programs from statistical modelsBernd Fischer, Johann Schumann. JFP, 13(3):483-508, 2003. [doi]
Toward V&V of neural network based controllersJohann Schumann, Stacy D. Nelson. woss 2002: 67-72 [doi]
NORA/HAMMR: Making Deduction-Based Software Component Retrieval PracticalJohann Schumann, Bernd Fischer. jckbse 1997: 246-254 [doi]
Statistical Prediction of Failures in Aircraft Collision Avoidance SystemsYuning He, Dimitra Giannakopoulou, Johann Schumann. BIRTHDAY 2019: 249-267 [doi]
KPROP - An AND-parallel Theorem Prover for Propositional Logic implemented in KL1 (System Abstract)Johann Schumann. cade 1992: 740-742
A Framework for the Analysis of Deep Neural Networks in Autonomous Aerospace Applications using Bayesian StatisticsYuning He, Johann Schumann. sp 2020: 234-239 [doi]
Modelling and Performances Analysis of a Parallel Theorem ProverManfred R. Jobmann, Johann Schumann. sigmetrics 1992: 259-260
SETHEO V3.2: Recent Developments - System AbstractChristoph Goller, Reinhold Letz, Klaus Mayr, Johann Schumann. cade 1994: 778-782
A framework for the analysis of adaptive systems using bayesian statisticsYuning He, Johann Schumann. ICSE 2020: 64-70 [doi]
Software health management with Bayesian networksJohann Schumann, Timmy Mbaya, Ole J. Mengshoel, Knot Pipatsrisawat, Ashok N. Srivastava, Arthur Choi, Adnan Darwiche. isse, 9(4):271-292, 2013. [doi]
Amphion/NAV: Deductive Synthesis of State Estimation SoftwareJon Whittle, Jeffrey Van Baalen, Johann Schumann, Peter Robinson, Thomas Pressburger, John Penix, Phil Oh, Michael R. Lowry, Guillaume P. Brat. ASE 2001: 395-399 [doi]
Exploring Requirements for Software that Learns: A Research PreviewMarie Farrell, Anastasia Mavridou, Johann Schumann. refsq 2023: 179-188 [doi]
SETHEO: A High-Performance Theorem ProverReinhold Letz, Johann Schumann, Stefan Bayerl, Wolfgang Bibel. JAR, 8(2):183-212, 1992.
Formal Requirements Elicitation with FRETDimitra Giannakopoulou, Thomas Pressburger, Anastasia Mavridou, Julian Rhein, Johann Schumann, Nija Shi. refsq 2020: [doi]
PARTHEO: A Parallel Inference MachineStefan Bayerl, Reinhold Letz, Johann Schumann. wi 1989: 527-539
Generating Data Analysis Programs from Statistical ModelsBernd Fischer, Johann Schumann, Thomas Pressburger. saig 2000: 212-229 [doi]
Generating statechart designs from scenariosJon Whittle, Johann Schumann. ICSE 2000: 314-323 [doi]
R2U2: monitoring and diagnosis of security threats for unmanned aerial systemsPatrick Moosbrugger, Kristin Y. Rozier, Johann Schumann. fmsd, 51(1):31-61, 2017. [doi]
Automated formalization of structured natural language requirementsDimitra Giannakopoulou, Thomas Pressburger, Anastasia Mavridou, Johann Schumann. INFSOF, 137:106590, 2021. [doi]
PIL/SETHEO: A Tool for the Automatic Analysis of Authentication ProtocolsJohann Schumann. cav 1999: 500-504 [doi]
Verifikation von Authentifikationsprotokollen mit Automatischen BeweisernJohann Schumann. ki, 12(4):48-53, 1998.
Generation of Formal Requirements from Structured Natural LanguageDimitra Giannakopoulou, Thomas Pressburger, Anastasia Mavridou, Johann Schumann. refsq 2020: 19-35 [doi]
Analysing the Load Balancing Scheme of a Parallel System on Multiprocessors - A Modeling ApproachJohann Schumann, Manfred R. Jobmann. parle 1994: 819-822
Performance Analysis of Dynamic Cell StructuresYan Liu, Bojan Cukic, Johann Schumann, Michael Jiang. In Ke Chen, Lipo Wang, editors, Trends in Neural Computation. Volume 35 of Studies in Computational Intelligence, pages 367-389, Springer, 2007. [doi]
Automatic Synthesis of Agent Designs in UMLJohann Schumann, Jon Whittle. faabs 2001: 148-162 [doi]
Intelligent Systems for Modeling and Control: Advances in Design and ValidationDanil Prokhorov, Johann Schumann. IEEEisic 2008: 18 [doi]
DELTA - A Bottom-up Preprocessor for Top-Down Theorem Provers - System AbstractJohann Schumann. cade 1994: 774-777
Tutorial on High-Performance Theorem Provers: Efficient Implementation and ParallelisationJohann Schumann, Reinhold Letz, Franz J. Kurfess. cade 1990: 683
Modelling and performance Analysis of a Parallel Theorem ProverManfred R. Jobmann, Johann Schumann. mmb 1991: 228-243
Runtime Observer Pairs and Bayesian Network Reasoners On-board FPGAs: Flight-Certifiable System Health Management for Embedded SystemsJohannes Geist, Kristin Y. Rozier, Johann Schumann. RV 2014: 215-230 [doi]
An ensemble approach to building Mercer Kernels with prior informationAshok N. Srivastava, Johann Schumann, Bernd Fischer 0002. SMC 2005: 2352-2359 [doi]
Automating the implementation of Kalman filter algorithmsJon Whittle, Johann Schumann. TOMS, 30(4):434-453, 2004. [doi]
SETHEO and E-SETHEO - The CADE-13 SystemsMax Moser, Ortrun Ibens, Reinhold Letz, Joachim Steinbach, Christoph Goller, Johann Schumann, Klaus Mayr. JAR, 18(2):237-246, 1997.
Capture, Analyze, Diagnose: Realizability Checking Of Requirements in FRETAndreas Katis, Anastasia Mavridou, Dimitra Giannakopoulou, Thomas Pressburger, Johann Schumann. cav 2022: 490-504 [doi]
Automated Theorem Proving in High-Quality Software DesignJohann Schumann. BIRTHDAY 2000: 295-312
Runtime Analysis with R2U2: A Tool Exhibition ReportJohann Schumann, Patrick Moosbrugger, Kristin Y. Rozier. RV 2016: 504-509 [doi]
AutoBayes/CC - Combining Program Synthesis with Automatic Code Certification - System DescriptionMichael W. Whalen, Johann Schumann, Bernd Fischer. cade 2002: 290-294 [doi]
ILF-SETHEO: Processing Model Elimination Proofs for Natural Language OutputAndreas Wolf, Johann Schumann. cade 1997: 61-64
Formal testing for separation assuranceDimitra Giannakopoulou, David H. Bushnell, Johann Schumann, Heinz Erzberger, Karen Heere. AMAI, 63(1):5-30, 2011. [doi]
Performance Estimation of a Neural Network-Based ControllerJohann Schumann, Yan Liu. isnn 2006: 981-990 [doi]
Tool Support for Parametric Analysis of Large Software Simulation SystemsJohann Schumann, Karen Gundy-Burlet, Corina S. Pasareanu, Tim Menzies, Tony Barrett. ASE 2008: 497-498 [doi]
A Framework for the Analysis of Deep Neural Networks in Aerospace applications using Bayesian StatisticsYuning He, Johann Schumann. ijcnn 2020: 1-9 [doi]
Automated Testcase Generation for Numerical Support Functions in Embedded SystemsJohann Schumann, Stefan-Alexander Schneider. NFM 2014: 252-257 [doi]
A Framework for Software Health Management using Bayesian Statistics: Position PaperYuning He, Johann Schumann. ICSE 2020: 719-722 [doi]
Exploring Model Quality for ACAS XDimitra Giannakopoulou, Dennis Guck, Johann Schumann. FM 2016: 274-290 [doi]
Automatic Verification of Cryptographic Protocols with SETHEOJohann Schumann. cade 1997: 87-100
Applications of Neural Networks in High Assurance SystemsJohann Schumann, Yan Liu 0003, editors, Volume 268 of Studies in Computational Intelligence, Springer, 2010. [doi]
Tableaux-based Theorem Provers: Systems and ImplementationsJohann Schumann. JAR, 13(3):409-421, 1994.
R2U2: Tool OverviewKristin Yvonne Rozier, Johann Schumann. RV 2017: 138-156 [doi]
A Tool for Verification and Validation of Neural Network Based Adaptive Controllers for High Assurance SystemsPramod Gupta, Johann Schumann. hase 2004: 277-278 [doi]
What Makes a Code Review Trustworthy?Stacy D. Nelson, Johann Schumann. hicss 2004: [doi]
Temporal-Logic Based Runtime Observer Pairs for System Health Management of Real-Time SystemsThomas Reinbacher, Kristin Yvonne Rozier, Johann Schumann. TACAS 2014: 357-372 [doi]

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