CSE 7314/5314 (Fall 2026): Additional References (Papers)

Some relevant papers published before the publication of our main textbook are listed in the Bibliography (pp.389-402) of our textbook. The following is a list of relevant papers, and a set of classified lists of the same papers (some may appear in multiple categories), mostly published after 2005. The categories include, 1. testing, 2. other QA, 3. QQI (also additional ones for 4. SRE, and 5. SSE), corresponding to the classification we used in our class.

For other references (books, additional SRE and SSE papers, and papers from SMU/Tian-group), see the notes below:

Additional References (All Papers)

  1. Ai, Jun, et al. "A Software Network Model for Software Structure and Faults Distribution Analysis." IEEE Transactions on Reliability, vol. 68, no. 3, 2019, pp. 844-858., https://doi.org/10.1109/tr.2019.2909786.

  2. Mohammed Alannsary, "A Defect Classification Framework for AI-Based Software Systems (AIODC)", In e-Informatica Software Engineering Journal, vol. 20, no. 1, pp. 260102, 2026. DOI: 10.37190/e-Inf260102.

  3. Mohammed Alannsary, "WCAG-ODC: an orthogonal defect classification framework for web accessibility defects", In Sci. J. King Faisal Univ.: Basic Appl. Sci. (2026)27:11.

  4. Nathaniel Ayewah, William Pugh, David Hovemeyer, I. David Morgenthaler, and John Penix, "Using Static Analysis to Find Bugs", IEEE Software, Sep., 2008, pp.22-29.

  5. Baron, Claude, and Vincent Louis. "Towards a Continuous Certification of Safety-Critical Avionics Software". Computers in Industry, vol. 125, 2021, p. 103382., https://doi.org/10.1016/j.compind.2020.103382.

  6. Al Bessey, Ken Block, Ben Chelf, Andy Chou, Bryan Fulton, Seth Hallem, Charles Henri-Gros, Asya Kamsky, Scott CMcPeak, and Dawson Engler, "A Few Billion Lines of Code Later: Using Static Analysis to Find Bugs in the Real World", Comm. of the ACM, Vol.53, No.2, pp.66-75, Feb., 2010.

  7. Y. Bontemps, P. Heymans, and P.-Y. Schobbens, "From Live-Sequence Charts to State Machines and Back: A Guided Tour", IEEE Trans. on Software Engineering, Vol.31, No.12, pp.999-1014, Dec., 2005.

  8. Jeffrey C. Carver, Nachiappan Nagappan, and Alan Page, "The Impact of Educational Background on the Effectiveness of Requirements Inspections: An Empirical Study", IEEE Trans. on Software Engineering, Vol.34, No.6, pp.800-812, Nov., 2008.
    To me, the most interesting finding is that no-CS inspectors found more req. defects than CS ones!

  9. Nazanin Bayati Chaleshtari, Fabrizio Pastore, Arda Goknil, and Lionel C. Briand, “Metamorphic Testing for Web System Security,” IEEE Transactions on Software Engineering 49(6)3430-3471, 2023.

  10. Edmund M. Clarke, E. Allen Emerson, and Joseph Sifakis, "Model Checking: Algorithmic Verification and Debugging", Communications of the ACM, Vol.52, No.111, pp.75-84, Nov., 2009.

  11. Jacek Czerwonka, Michaela Greiler, Christian Bird, Lucas Panjer, and Terry Coatta, "CodeFlow: Improving the Code Review Process at Microsoft", Communications of the ACM, Vol.62, NO.2, pp.36-44, Feb., 2019.
    The most interesting observation to me is that more importantly, code review improves long-term maintainability than just finding bugs.

  12. C. Damas, B. Lambeau, P. Dupont, and A. van Lamsweerde, "Generating Annotated Behavior MOdels from End-User Scenarios", IEEE Trans. on Software Engineering, Vol.31, No.12, pp.1056-1073, Dec., 2005.

  13. Phelim Dowling and Kevin McGrath, "Using Free and Open Source Tools to Manage Software Quality", Communications of the ACM, Vol.58, No.7, pp.51-55, July, 2015.

  14. Christof Ebert and Michael Weyrich, "Validation of Autonomous Systems", IEEE Software, Vol.36, No.5, Sept., 2019.
    BB vs WB; man. vs. auto: 2x2 classification of techniques; also important role of simulation!

  15. B. Freimut, L.C. Briand, and F. Vollei, "Determining Inspection Cost-Effectiveness by Combining Project Data and Expert Opinion", IEEE Trans. on Software Engineering, Vol.31, No.12, pp.1074-1092, Dec., 2005.

  16. Patrice Godefroid, Peli de Halleux, Aditya V. Nori, Sriram K. Rajamani, Wolfram Schulte, Nikolai Tillmann, and Michael, Y. Levin, "Automating Software Testing Using Program Analysis", IEEE Software, Sep., 2008, pp.30-37.

  17. Haas, Roman, Michael Sailer, Mitchell Joblin, Elmar Juergens, and Sven Apel. “Prioritizing Test Gaps by Risk in Industrial Practice: An Automated Approach and Multimethod Study.” IEEE Transactions on Software Engineering, vol. 51, no. 5, 2025, pp. 1554-1568. DOI: 10.1109/TSE.2025.3556248. Available at: https://www.se.cs.uni-saarland.de/publications/docs/HSJ+25.pdf

  18. Lulu He, Jeffrey C. Carver, and Rayford B. Vaughn, "Using Inspection to Teach Requirement Validation", Crosstalk, Jan., 2008, pp.11-15.

  19. Thong Hoang, Hoa Khanh Dam, Yasutaka Kamei, David Lo, Naoyasu Ubayashi, "DeepJIT: An End-To-End Deep Learning Framework for Just-In-Time Defect Prediction" 2019 IEEE/ACM 16th International Conference on Mining Software Repositories (MSR) .

  20. Jia, Y., and Harman, M. (2021). "An Analysis and Survey of the Development of Mutation" Testing. IEEE Transactions on Software Engineering 37(5):649-678, Sept., 2011.

  21. Natalia Juristo, Ana M. Moreno, Sira Vegas, and Martin Solari, "In Search of What We Experimentally Know about Unit Testing", IEEE Software, Nov., 2006, pp.72-80.
    Despite its title, I found the classification of testing techniques in this paper very interesting, not just for unit testing, but for all testing sub-phases: based on: 1. tester's intuition and experience (ad hoc in our book), 2. specification 3. code, 4. fault, 5. usage, 6. fault seeding; related topic on test-set selection: 1. filtering, 2. prioritization, 3. regression.

  22. Upulee Kanewala and Tsong Yueh Chen, "Metamorphic Testing: A Simple Yet Effective Approach for Testing Scientific Software", IEEE Computer, July 2020, pp.8-14.
    a good intro to MT: I/O change relations, e.g., input reshuffling won't change output:avg. Can be a good oracle example.

  23. H. E. Kim, H. S. Son, B. G. Kim, J. Cho, S. M. Shin and H. G. Kang, "Input-Domain Software Testing for Failure Probability Estimation of Safety-Critical Applications in Consideration of Past Input Sequence," in IEEE Access, vol. 6, pp. 8440-8451, 2018, doi: 10.1109/ACCESS.2017.2765698.

  24. Kumar, Chandan, and Dilip Kumar Yadav. "Software Defects Estimation Using Metrics of Early Phases of Software Development Life Cycle." International Journal of System Assurance Engineering and Management, vol. 8, no. Suppl 4, 2017, pp. 2109-17, https://doi.org/10.1007/s13198-014-0326-2.

  25. Pramod Kumar, Lalit Kumar Singh, Chiranjeev Kumar, "Software reliability analysis for safety-critical and control systems"

  26. P. Kumar, L. K. Singh, C. Kumar, S. Verma and S. Kumar, "A Bayesian Belief Network Model for Early Prediction of Reliability for Computer-Based Safety-Critical Systems," 2021 2nd International Conference on Range Technology (ICORT), Chandipur, Balasore, India, 2021, pp. 1-6, doi: 10.1109/ICORT52730.2021.9581624.

  27. Lee, S. H., Shin, S.-M., Hwang, J. S., & Park, J. (2020). Operational vulnerability identification procedure for nuclear facilities using Stamp/STPA. IEEE Access, 8, 166034.166046. https://doi.org/10.1109/access.2020.3021741

  28. Xavier Leroy, "Formal Verification of a Realistic Compiler", Comm. of the ACM, Vol.52, No.7, pp.107-115, July, 2009.
    "with proof assistants, ... using only elementary semantic and algorithmic approaches"

  29. Panagiotis Louridas, "JUnit: Unit Testing and Coding in Tandem", IEEE Software, Vol.22, No.4, pp.12-15, July/Aug., 2005.
    - A nice short survey about JUnit.

  30. Panos Louridas, "Test Management", IEEE Software, Vol.28, No.5, pp.86-91, Sept./Oct. 2011.
    - Including interesting figures about testing effort % (larger system, higher %), developer-to-tester ratios (high-assurance, more testing), test measurement, and test case management tools.

  31. R. R. Lutz, "Safe-AR: Reducing Risk While Augmenting Reality," 2018 IEEE 29th International Symposium on Software Reliability Engineering (ISSRE), Memphis, TN, USA, 2018, pp. 70-75, doi: 10.1109/ISSRE.2018.00018.

  32. Mika V. Mantyla and Casper Lassenius, "What Type of Defects Are Really Discovered in Code Reviews?" IEEE Trans. on Software Engineering, Vol.35, No.3, pp.430-448, May, 2009.
    more evolvability defects (documentation, visual representation, and structure) than functional ones: 5:1 to 3:1.

  33. Steven P. Miller, Michael W. Whalen, and Darren D. Coffer, "Software Model Checking Takes Off", Comm. of the ACM, Vol.53, No.2, pp.58-64, Feb., 2010.
    avionics...

  34. Robert O'Callahan, Kyle Huey, Devon O'Dell, and Terry Coatta, "To Catch a Failure: The Record-and-Replay Approach to Debugging", Comm. of the ACM, Vol.63, No.8, pp.34-40, Aug., 2020.

  35. Jalaj Pachouly, Swati Ahirrao1, Ketan Kotecha1, Ambarish Kulkarni & Sultan Alfarhood, "Multilabel classification for defect prediction in software engineering", Scientific Reports (2025)15:8739.

  36. David Lorge Parnas, "Really Rethinking 'Formal Methods'", IEEE Computer, Jan., 2010, pp.28-34.
    more of a balanced, "engineer's view"...

  37. Perera, A., Aleti, A., Turhan, B., & Bohme, M. (2023). An Experimental Assessment of Using Theoretical Defect Predictors to Guide Search-Based Software Testing. IEEE Transactions on Software Engineering, 49(1), 131–146. https://doi.org/10.1109/TSE.2022.3147008

  38. Macario Polo Usaola and Pedro Reales Mateo, "Mutation Testing Cost Reduction Techniques: A Survey", IEEE Software, May, 2010, pp.80-86.

  39. Quamara, Megha, et al. "Multi-Layered Model-Based Design Approach towards System Safety and Security Co-Engineering". 2021 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C), 2021, https://doi.org/10.1109/models-c53483.2021.00048.

  40. Singh, Y., & Kumar, P. (2010). Application of feed-forward neural networks for software reliability prediction. ACM SIGSOFT Software Engineering Notes, 35(5), 1.6. https://doi.org/10.1145/1838687.18387

  41. M. Soylemez and A. Tarhan, "Using Process Enactment Data Analysis to Support Orthogonal Defect Classification for Software Process Improvement," 2013 Joint Conference of the 23rd International Workshop on Software Measurement and the 8th International Conference on Software Process and Product Measurement, Ankara, Turkey, 2013, pp. 120-125, doi: 10.1109/IWSM-Mensura.2013.27.

  42. Vlasta Stavova, Lenka Dedkova, Martin Uktrop, and Vashek Matyas, "A Large-Scale Comparative Study of Beta Testers and Regular Users", Communications of the ACM, Vol.61, No.2, pp.64-71, Feb., 2018.
    "beta testers as geeks", OK for large org./widely distributed software

  43. Roger Stewart and Lew Priven, "How to Avoid Inspection Failures and Achieve Ongoing Benefits", Crosstalk, Jan., 2008, pp.23-27.

  44. Thung, F., Lo, D., & Jiang, L. (2012). Automatic defect categorization. 2012 19th Working Conference on Reverse Engineering. https://doi.org/10.1109/wcre.2012.30

  45. Jan Wloka, Einar W. Host, Barbara G. Ryder, "Tool Support for Change-Centric Test Development", IEEE Software, May, 2010, pp.66-71.

  46. L. Xia, J. Yang, H. Wang and X. Hou, "Safety Analysis and Risk Assessment of LPAR Software System," 2018 12th International Conference on Reliability, Maintainability, and Safety (ICRMS), Shanghai, China, 2018, pp. 150-154, doi: 10.1109/ICRMS.2018.00037.

  47. F. Zeng, M. Lu and D. Zhong, "Software Safety Certification Framework Based on Safety Case," 2012 International Conference on Computer Science and Service System, Nanjing, China, 2012, pp. 566-569, doi: 10.1109/CSSS.2012.147.

  48. Danjiang ZHU, et al. "A Software Safety Requirements Elicitation Approach Based on Hazardous Control Action Tree Modelling". CHINESE JOURNAL OF ELECTRONICS, vol. 30, no. 4, 2021, pp. 676.85, https://doi.org/10.1049/cje.2021.05.009

Testing Papers

  1. Y. Bontemps, P. Heymans, and P.-Y. Schobbens, "From Live-Sequence Charts to State Machines and Back: A Guided Tour", IEEE Trans. on Software Engineering, Vol.31, No.12, pp.999-1014, Dec., 2005.

  2. Nazanin Bayati Chaleshtari, Fabrizio Pastore, Arda Goknil, and Lionel C. Briand, “Metamorphic Testing for Web System Security,” IEEE Transactions on Software Engineering 49(6)3430-3471, 2023.

  3. C. Damas, B. Lambeau, P. Dupont, and A. van Lamsweerde, "Generating Annotated Behavior MOdels from End-User Scenarios", IEEE Trans. on Software Engineering, Vol.31, No.12, pp.1056-1073, Dec., 2005.

  4. Christof Ebert and Michael Weyrich, "Validation of Autonomous Systems", IEEE Software, Vol.36, No.5, Sept., 2019.
    BB vs WB; man. vs. auto: 2x2 classification of techniques; also important role of simulation!

  5. Patrice Godefroid, Peli de Halleux, Aditya V. Nori, Sriram K. Rajamani, Wolfram Schulte, Nikolai Tillmann, and Michael, Y. Levin, "Automating Software Testing Using Program Analysis", IEEE Software, Sep., 2008, pp.30-37.

  6. Haas, Roman, Michael Sailer, Mitchell Joblin, Elmar Juergens, and Sven Apel. “Prioritizing Test Gaps by Risk in Industrial Practice: An Automated Approach and Multimethod Study.” IEEE Transactions on Software Engineering, vol. 51, no. 5, 2025, pp. 1554-1568. DOI: 10.1109/TSE.2025.3556248. Available at: https://www.se.cs.uni-saarland.de/publications/docs/HSJ+25.pdf

  7. Natalia Juristo, Ana M. Moreno, Sira Vegas, and Martin Solari, "In Search of What We Experimentally Know about Unit Testing", IEEE Software, Nov., 2006, pp.72-80.
    Despite its title, I found the classification of testing techniques in this paper very interesting, not just for unit testing, but for all testing sub-phases: based on: 1. tester's intuition and experience (ad hoc in our book), 2. specification 3. code, 4. fault, 5. usage, 6. fault seeding; related topic on test-set selection: 1. filtering, 2. prioritization, 3. regression.

  8. Jia, Y., and Harman, M. (2021). "An Analysis and Survey of the Development of Mutation" Testing. IEEE Transactions on Software Engineering 37(5):649-678, Sept., 2011.

  9. Upulee Kanewala and Tsong Yueh Chen, "Metamorphic Testing: A Simple Yet Effective Approach for Testing Scientific Software", IEEE Computer, July 2020, pp.8-14.
    a good intro to MT: I/O change relations, e.g., input reshuffling won't change output:avg. Can be a good oracle example.

  10. H. E. Kim, H. S. Son, B. G. Kim, J. Cho, S. M. Shin and H. G. Kang, "Input-Domain Software Testing for Failure Probability Estimation of Safety-Critical Applications in Consideration of Past Input Sequence," in IEEE Access, vol. 6, pp. 8440-8451, 2018, doi: 10.1109/ACCESS.2017.2765698.

  11. Panagiotis Louridas, "JUnit: Unit Testing and Coding in Tandem", IEEE Software, Vol.22, No.4, pp.12-15, July/Aug., 2005.
    - A nice short survey about JUnit.

  12. Panos Louridas, "Test Management", IEEE Software, Vol.28, No.5, pp.86-91, Sept./Oct. 2011.
    - Including interesting figures about testing effort % (larger system, higher %), developer-to-tester ratios (high-assurance, more testing), test measurement, and test case management tools.

  13. Robert O'Callahan, Kyle Huey, Devon O'Dell, and Terry Coatta, "To Catch a Failure: The Record-and-Replay Approach to Debugging", Comm. of the ACM, Vol.63, No.8, pp.34-40, Aug., 2020.

  14. Perera, A., Aleti, A., Turhan, B., & Bohme, M. (2023). An Experimental Assessment of Using Theoretical Defect Predictors to Guide Search-Based Software Testing. IEEE Transactions on Software Engineering, 49(1), 131–146. https://doi.org/10.1109/TSE.2022.3147008

  15. Macario Polo Usaola and Pedro Reales Mateo, "Mutation Testing Cost Reduction Techniques: A Survey", IEEE Software, May, 2010, pp.80-86.

  16. Vlasta Stavova, Lenka Dedkova, Martin Uktrop, and Vashek Matyas, "A Large-Scale Comparative Study of Beta Testers and Regular Users", Communications of the ACM, Vol.61, No.2, pp.64-71, Feb., 2018.
    "beta testers as geeks", OK for large org./widely distributed software

  17. Jan Wloka, Einar W. Host, Barbara G. Ryder, "Tool Support for Change-Centric Test Development", IEEE Software, May, 2010, pp.66-71.

Other QA (QA other than testing) Papers

  1. Nathaniel Ayewah, William Pugh, David Hovemeyer, I. David Morgenthaler, and John Penix, "Using Static Analysis to Find Bugs", IEEE Software, Sep., 2008, pp.22-29.

  2. Al Bessey, Ken Block, Ben Chelf, Andy Chou, Bryan Fulton, Seth Hallem, Charles Henri-Gros, Asya Kamsky, Scott CMcPeak, and Dawson Engler, "A Few Billion Lines of Code Later: Using Static Analysis to Find Bugs in the Real World", Comm. of the ACM, Vol.53, No.2, pp.66-75, Feb., 2010.

  3. Jeffrey C. Carver, Nachiappan Nagappan, and Alan Page, "The Impact of Educational Background on the Effectiveness of Requirements Inspections: An Empirical Study", IEEE Trans. on Software Engineering, Vol.34, No.6, pp.800-812, Nov., 2008.
    To me, the most interesting finding is that no-CS inspectors found more req. defects than CS ones!

  4. Edmund M. Clarke, E. Allen Emerson, and Joseph Sifakis, "Model Checking: Algorithmic Verification and Debugging", Communications of the ACM, Vol.52, No.111, pp.75-84, Nov., 2009.

  5. Jacek Czerwonka, Michaela Greiler, Christian Bird, Lucas Panjer, and Terry Coatta, "CodeFlow: Improving the Code Review Process at Microsoft", Communications of the ACM, Vol.62, NO.2, pp.36-44, Feb., 2019.
    The most interesting observation to me is that more importantly, code review improves long-term maintainability than just finding bugs.

  6. Christof Ebert and Michael Weyrich, "Validation of Autonomous Systems", IEEE Software, Vol.36, No.5, Sept., 2019.
    BB vs WB; man. vs. auto: 2x2 classification of techniques; also important role of simulation!

  7. B. Freimut, L.C. Briand, and F. Vollei, "Determining Inspection Cost-Effectiveness by Combining Project Data and Expert Opinion", IEEE Trans. on Software Engineering, Vol.31, No.12, pp.1074-1092, Dec., 2005.

  8. Patrice Godefroid, Peli de Halleux, Aditya V. Nori, Sriram K. Rajamani, Wolfram Schulte, Nikolai Tillmann, and Michael, Y. Levin, "Automating Software Testing Using Program Analysis", IEEE Software, Sep., 2008, pp.30-37.

  9. Lulu He, Jeffrey C. Carver, and Rayford B. Vaughn, "Using Inspection to Teach Requirement Validation", Crosstalk, Jan., 2008, pp.11-15.

  10. Xavier Leroy, "Formal Verification of a Realistic Compiler", Comm. of the ACM, Vol.52, No.7, pp.107-115, July, 2009.
    "with proof assistants, ... using only elementary semantic and algorithmic approaches"

  11. Mika V. Mantyla and Casper Lassenius, "What Type of Defects Are Really Discovered in Code Reviews?" IEEE Trans. on Software Engineering, Vol.35, No.3, pp.430-448, May, 2009.
    more evolvability defects (documentation, visual representation, and structure) than functional ones: 5:1 to 3:1.

  12. Steven P. Miller, Michael W. Whalen, and Darren D. Coffer, "Software Model Checking Takes Off", Comm. of the ACM, Vol.53, No.2, pp.58-64, Feb., 2010.
    avionics...

  13. David Lorge Parnas, "Really Rethinking 'Formal Methods'", IEEE Computer, Jan., 2010, pp.28-34.
    more of a balanced, "engineer's view"...

  14. Roger Stewart and Lew Priven, "How to Avoid Inspection Failures and Achieve Ongoing Benefits", Crosstalk, Jan., 2008, pp.23-27.

QQI (quantifiable quality improvement) Papers (mostly on quality measurement, analysis, and feedback, but excluding SRE and SSE papers below)

  1. Ai, Jun, et al. "A Software Network Model for Software Structure and Faults Distribution Analysis." IEEE Transactions on Reliability, vol. 68, no. 3, 2019, pp. 844-858., https://doi.org/10.1109/tr.2019.2909786.

  2. Mohammed Alannsary, "A Defect Classification Framework for AI-Based Software Systems (AIODC)", In e-Informatica Software Engineering Journal, vol. 20, no. 1, pp. 260102, 2026. DOI: 10.37190/e-Inf260102.

  3. Mohammed Alannsary, "WCAG-ODC: an orthogonal defect classification framework for web accessibility defects", In Sci. J. King Faisal Univ.: Basic Appl. Sci. (2026)27:11.

  4. Phelim Dowling and Kevin McGrath, "Using Free and Open Source Tools to Manage Software Quality", Communications of the ACM, Vol.58, No.7, pp.51-55, July, 2015.

  5. B. Freimut, L.C. Briand, and F. Vollei, "Determining Inspection Cost-Effectiveness by Combining Project Data and Expert Opinion", IEEE Trans. on Software Engineering, Vol.31, No.12, pp.1074-1092, Dec., 2005.

  6. Thong Hoang, Hoa Khanh Dam, Yasutaka Kamei, David Lo, Naoyasu Ubayashi, "DeepJIT: An End-To-End Deep Learning Framework for Just-In-Time Defect Prediction" 2019 IEEE/ACM 16th International Conference on Mining Software Repositories (MSR) .

  7. Kumar, Chandan, and Dilip Kumar Yadav. "Software Defects Estimation Using Metrics of Early Phases of Software Development Life Cycle." International Journal of System Assurance Engineering and Management, vol. 8, no. Suppl 4, 2017, pp. 2109-17, https://doi.org/10.1007/s13198-014-0326-2.

  8. Lee, S. H., Shin, S.-M., Hwang, J. S., & Park, J. (2020). Operational vulnerability identification procedure for nuclear facilities using Stamp/STPA. IEEE Access, 8, 166034.166046. https://doi.org/10.1109/access.2020.3021741

  9. Jalaj Pachouly, Swati Ahirrao1, Ketan Kotecha1, Ambarish Kulkarni & Sultan Alfarhood, "Multilabel classification for defect prediction in software engineering", Scientific Reports (2025)15:8739.

  10. Perera, A., Aleti, A., Turhan, B., & Bohme, M. (2023). An Experimental Assessment of Using Theoretical Defect Predictors to Guide Search-Based Software Testing. IEEE Transactions on Software Engineering, 49(1), 131–146. https://doi.org/10.1109/TSE.2022.3147008

  11. Singh, Y., & Kumar, P. (2010). Application of feed-forward neural networks for software reliability prediction. ACM SIGSOFT Software Engineering Notes, 35(5), 1.6. https://doi.org/10.1145/1838687.18387

  12. M. Soylemez and A. Tarhan, "Using Process Enactment Data Analysis to Support Orthogonal Defect Classification for Software Process Improvement," 2013 Joint Conference of the 23rd International Workshop on Software Measurement and the 8th International Conference on Software Process and Product Measurement, Ankara, Turkey, 2013, pp. 120-125, doi: 10.1109/IWSM-Mensura.2013.27.

  13. Thung, F., Lo, D., & Jiang, L. (2012). Automatic defect categorization. 2012 19th Working Conference on Reverse Engineering. https://doi.org/10.1109/wcre.2012.30

SRE (software reliability engineering) Papers

  1. H. E. Kim, H. S. Son, B. G. Kim, J. Cho, S. M. Shin and H. G. Kang, "Input-Domain Software Testing for Failure Probability Estimation of Safety-Critical Applications in Consideration of Past Input Sequence," in IEEE Access, vol. 6, pp. 8440-8451, 2018, doi: 10.1109/ACCESS.2017.2765698.

  2. Pramod Kumar, Lalit Kumar Singh, Chiranjeev Kumar, "Software reliability analysis for safety-critical and control systems"

  3. P. Kumar, L. K. Singh, C. Kumar, S. Verma and S. Kumar, "A Bayesian Belief Network Model for Early Prediction of Reliability for Computer-Based Safety-Critical Systems," 2021 2nd International Conference on Range Technology (ICORT), Chandipur, Balasore, India, 2021, pp. 1-6, doi: 10.1109/ICORT52730.2021.9581624.

SSE (software safety engineering) Papers

  1. Baron, Claude, and Vincent Louis. "Towards a Continuous Certification of Safety-Critical Avionics Software". Computers in Industry, vol. 125, 2021, p. 103382., https://doi.org/10.1016/j.compind.2020.103382.

  2. H. E. Kim, H. S. Son, B. G. Kim, J. Cho, S. M. Shin and H. G. Kang, "Input-Domain Software Testing for Failure Probability Estimation of Safety-Critical Applications in Consideration of Past Input Sequence," in IEEE Access, vol. 6, pp. 8440-8451, 2018, doi: 10.1109/ACCESS.2017.2765698.

  3. Pramod Kumar, Lalit Kumar Singh, Chiranjeev Kumar, "Software reliability analysis for safety-critical and control systems"

  4. P. Kumar, L. K. Singh, C. Kumar, S. Verma and S. Kumar, "A Bayesian Belief Network Model for Early Prediction of Reliability for Computer-Based Safety-Critical Systems," 2021 2nd International Conference on Range Technology (ICORT), Chandipur, Balasore, India, 2021, pp. 1-6, doi: 10.1109/ICORT52730.2021.9581624.

  5. Lee, S. H., Shin, S.-M., Hwang, J. S., & Park, J. (2020). Operational vulnerability identification procedure for nuclear facilities using Stamp/STPA. IEEE Access, 8, 166034.166046. https://doi.org/10.1109/access.2020.3021741

  6. R. R. Lutz, "Safe-AR: Reducing Risk While Augmenting Reality," 2018 IEEE 29th International Symposium on Software Reliability Engineering (ISSRE), Memphis, TN, USA, 2018, pp. 70-75, doi: 10.1109/ISSRE.2018.00018.

  7. Quamara, Megha, et al. "Multi-Layered Model-Based Design Approach towards System Safety and Security Co-Engineering". 2021 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C), 2021, https://doi.org/10.1109/models-c53483.2021.00048.

  8. Singh, Y., & Kumar, P. (2010). Application of feed-forward neural networks for software reliability prediction. ACM SIGSOFT Software Engineering Notes, 35(5), 1.6. https://doi.org/10.1145/1838687.18387

  9. L. Xia, J. Yang, H. Wang and X. Hou, "Safety Analysis and Risk Assessment of LPAR Software System," 2018 12th International Conference on Reliability, Maintainability, and Safety (ICRMS), Shanghai, China, 2018, pp. 150-154, doi: 10.1109/ICRMS.2018.00037.

  10. F. Zeng, M. Lu and D. Zhong, "Software Safety Certification Framework Based on Safety Case," 2012 International Conference on Computer Science and Service System, Nanjing, China, 2012, pp. 566-569, doi: 10.1109/CSSS.2012.147.

  11. Danjiang ZHU, et al. "A Software Safety Requirements Elicitation Approach Based on Hazardous Control Action Tree Modelling". CHINESE JOURNAL OF ELECTRONICS, vol. 30, no. 4, 2021, pp. 676.85, https://doi.org/10.1049/cje.2021.05.009

Prepared by Jeff Tian (tian@smu.edu).
Posted: Aug. 24, 2026. Last update: Aug. 24, 2026.

Back to CSE 5314/7314 webpage