Automation in Distributed Shared Memory Testing for Multi-Processor Systems

Authors

  • Swethasri Kavuri  Independent Researcher, USA

DOI:

https://doi.org/10.32628/IJSRSET12411594

Keywords:

Distributed Shared Memory, Multi-Processor Systems, Automated Testing, Fault Injection, Concurrency Detection, Formal Verification, Performance Benchmarking, Parallel Computing

Abstract

This research paper explores the critical domain of automated testing for Distributed Shared Memory (DSM) systems in multi-processor environments. As the complexity of multi-core and distributed computing systems continues to grow, ensuring the reliability and performance of DSM implementations becomes increasingly challenging. This study investigates various automated testing strategies, including test generation techniques, fault injection mechanisms, and concurrency detection methods. It also examines automated test execution frameworks, real-time monitoring solutions, and advanced verification and validation techniques. The research highlights the challenges faced in DSM testing, such as scalability issues and non-determinism, and proposes future directions for research, including the integration of artificial intelligence and cloud-based testing platforms. The findings of this study contribute to the advancement of DSM testing methodologies and provide valuable insights for both researchers and practitioners in the field of distributed systems and parallel computing.

References

  1. Adamoli, A., & Hauswirth, M. (2010). Trevis: A context tree visualization & analysis tool for performance traces. In Proceedings of the 5th international symposium on Software visualization (pp. 153–162).
  2. Adve, S. V., & Gharachorloo, K. (1996). Shared memory consistency models: A tutorial. Computer, 29(12), 66–76.
  3. Arlat, J., Aguera, M., Amat, L., Crouzet, Y., Fabre, J. C., Laprie, J. C., & Powell, D. (1990). Fault injection for dependability validation: A methodology and some applications. IEEE Transactions on Software Engineering, 16(2), 166–182.
  4. Banzai, T., Koizumi, H., Kanbayashi, R., Imada, T., Hanawa, T., & Sato, M. (2010). D-cloud: Design of a software testing environment for reliable distributed systems using cloud computing technology. In 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing (pp. 631–636).
  5. Baresi, L., & Young, M. (2001). Test oracles. Technical Report CIS-TR-01-02, University of Oregon, Dept. of Computer and Information Science, Eugene, Oregon, USA.
  6. Barham, P., Donnelly, A., Isaacs, R., & Mortier, R. (2004). Using magpie for request extraction and workload modelling. In OSDI (Vol. 4, pp. 18–18).
  7. Bershad, B. N., & Zekauskas, M. J. (1991). Midway: Shared memory parallel programming with entry consistency for distributed memory multiprocessors. Carnegie-Mellon University, Department of Computer Science.
  8. Bienia, C., Kumar, S., Singh, J. P., & Li, K. (2008). The PARSEC benchmark suite: Characterization and architectural implications. In Proceedings of the 17th international conference on Parallel architectures and compilation techniques (pp. 72–81).
  9. Cantin, J. F., Lipasti, M. H., & Smith, J. E. (2005). The complexity of verifying memory coherence and consistency. IEEE Transactions on Parallel and Distributed Systems, 16(7), 663–671.
  10. Carreira, J., & Costa, D. (1997). Automatically verifying an object-oriented specification of the Steam-Boiler control system. In International Symposium of Formal Methods Europe (pp. 262–279). Springer, Berlin, Heidelberg.
  11. Chen, T. Y., Cheung, S. C., & Yiu, S. M. (1998). Metamorphic testing: A new approach for generating next test cases. Technical Report HKUST-CS98-01, Department of Computer Science, Hong Kong University of Science and Technology, Hong Kong.
  12. Choi, J. D., Lee, K., Loginov, A., O'Callahan, R., Sarkar, V., & Sridharan, M. (2002). Efficient and precise data-race detection for multithreaded object-oriented programs. In Proceedings of the ACM SIGPLAN 2002 Conference on Programming language design and implementation (pp. 258–269).
  13. Clarke, E. M., Grumberg, O., & Peled, D. (1999). Model checking. MIT press.
  14. Dawson, S., Jahanian, F., & Mitton, T. (1996). ORCHESTRA: A fault injection environment for distributed systems. In Proceedings of 26th International Symposium on Fault-Tolerant Computing (FTCS-26) (pp. 404–414).
  15. Engler, D., & Ashcraft, K. (2003). RacerX: Effective, static detection of race conditions and deadlocks. ACM SIGOPS Operating Systems Review, 37(5), 237–252.
  16. Ferdman, M., Adileh, A., Kocberber, O., Volos, S., Alisafaee, M., Jevdjic, D., & Falsafi, B. (2012). Clearing the clouds: A study of emerging scale-out workloads on modern hardware. ACM SIGPLAN Notices, 47(4), 37–48.
  17. Flanagan, C., Freund, S. N., Qadeer, S., & Seshia, S. A. (2005). Modular verification of multithreaded programs. Theoretical Computer Science, 338(1–3), 153–183.
  18. Garvin, B. J., Cohen, M. B., & Dwyer, M. B. (2011). Evaluating improvements to a meta-heuristic search for constrained interaction testing. Empirical Software Engineering, 16(1), 61–102.
  19. Garousi, V., Briand, L. C., & Labiche, Y. (2008). Traffic-aware stress testing of distributed real-time systems based on UML models using genetic algorithms. Journal of Systems and Software, 81(2), 161–185.
  20. Gharachorloo, K., Lenoski, D., Laudon, J., Gibbons, P., Gupta, A., & Hennessy, J. (1990). Memory consistency and event ordering in scalable shared-memory multiprocessors. ACM SIGARCH Computer Architecture News, 18(2SI), 15–26.
  21. Hennessy, J. L., & Patterson, D. A. (2011). Computer architecture: A quantitative approach. Elsevier.
  22. Hower, D. R., & Hill, M. D. (2008). Rerun: Exploiting episodes for lightweight memory race recording. ACM SIGARCH Computer Architecture News, 36(3), 265–276.
  23. Huang, J., Meredith, P. O., & Rosu, G. (2014). Maximal sound predictive race detection with control flow abstraction. ACM SIGPLAN Notices, 49(6), 337–348.
  24. Kanawati, G. A., Kanawati, N. A., & Abraham, J. A. (1995). FERRARI: A flexible software-based fault and error injection system. IEEE Transactions on Computers, 44(2), 248–260.
  25. Keleher, P., Cox, A. L., Dwarkadas, S., & Zwaenepoel, W. (1992). Lazy release consistency for software distributed shared memory. In Proceedings of the 19th annual international symposium on Computer architecture (pp. 13–21).
  26. Kuhn, D. R., Wallace, D. R., & Gallo, A. M. (2004). Software fault interactions and implications for software testing. IEEE Transactions on Software Engineering, 30(6), 418–421.
  27. Lamport, L. (1979). How to make a multiprocessor computer that correctly executes multiprocess programs. IEEE Transactions on Computers, 100(9), 690–691.
  28. Laudon, J., & Lenoski, D. (1997). The SGI Origin: A ccNUMA highly scalable server. ACM SIGARCH Computer Architecture News, 25(2), 241–251.
  29. Leavens, G. T., Baker, A. L., & Ruby, C. (1999). Preliminary design of JML: A behavioral interface specification language for Java. ACM SIGSOFT Software Engineering Notes, 31(3), 1–38.
  30. Leung, H. K., & White, L. (1989). Insights into regression testing (software testing). In Proceedings. Conference on Software Maintenance-1989 (pp. 60–69). IEEE.
  31. Li, K., & Hudak, P. (1989). Memory coherence in shared virtual memory systems. ACM Transactions on Computer Systems (TOCS), 7(4), 321–359.
  32. Bhavesh Kataria, Characterization and Identification of Rice Grains Through Digital Image Analysis in International Journal – Sanshodhan, ISSN 0975- 4245, December, 2011 (Print)
  33. Lu, S., Park, S., Seo, E., & Zhou, Y. (2008). Learning from mistakes: A comprehensive study on real world concurrency bug characteristics. ACM SIGARCH Computer Architecture News, 36(1), 329–339.
  34. Meredith, P. O., Jin, D., Griffith, D., Chen, F., & Ro?u, G. (2012). An overview of the MOP runtime verification framework. International Journal on Software Tools for Technology Transfer, 14(3), 249–289.
  35. Nelson, J., Holt, B., Myers, B., Briggs, P., Ceze, L., Kahan, S., & Oskin, M. (2015). Latency-tolerant software distributed shared memory. In 2015 USENIX Annual Technical Conference (USENIX ATC 15) (pp. 291–305).
  36. Nie, C., & Leung, H. (2011). A survey of combinatorial testing. ACM Computing Surveys (CSUR), 43(2), 1–29.
  37. Nipkow, T., Paulson, L. C., & Wenzel, M. (2002). Isabelle/HOL: A proof assistant for higher-order logic (Vol. 2283). Springer Science & Business Media.
  38. Orso, A., & Rothermel, G. (2014). Software testing: A research travelogue (2000–2014).
  39. Santhosh Palavesh. (2019). The Role of Open Innovation and Crowdsourcing in Generating New Business Ideas and Concepts. International Journal for Research Publication and Seminar, 10(4), 137–147. https://doi.org/10.36676/jrps.v10.i4.1456
  40. Challa, S. S. S., Tilala, M., Chawda, A. D., & Benke, A. P. (2019). Investigating the use of natural language processing (NLP) techniques in automating the extraction of regulatory requirements from unstructured data sources. Annals of Pharma Research, 7(5), 380-387.
  41. Challa, S. S., Tilala, M., Chawda, A. D., & Benke, A. P. (2019). Investigating the use of natural language processing (NLP) techniques in automating the extraction of regulatory requirements from unstructured data sources. Annals of PharmaResearch, 7(5), 380-387.
  42. Bhavesh Kataria, "Role of Information Technology in Agriculture : A Review, International Journal of Scientific Research in Science, Engineering and Technology, Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 1, Issue 1, pp.01-03, 2014. Available at : https://doi.org/10.32628/ijsrset141115
  43. Dr. Saloni Sharma, & Ritesh Chaturvedi. (2017). Blockchain Technology in Healthcare Billing: Enhancing Transparency and Security. International Journal for Research Publication and Seminar, 10(2), 106–117. Retrieved from https://jrps.shodhsagar.com/index.php/j/article/view/1475
  44. Bhaskar, V. V. S. R., Etikani, P., Shiva, K., Choppadandi, A., & Dave, A. (2019). Building explainable AI systems with federated learning on the cloud. Journal of Cloud Computing and Artificial Intelligence, 16(1), 1–14.
  45. Bhavesh Kataria, Analysis of Rice Grains Through Digital Image Processing, SCI-TECH Research (National Journal) ISSN 0974 – 9780, February, 2012 (Print)
  46. Big Data Analytics using Machine Learning Techniques on Cloud Platforms. (2019). International Journal of Business Management and Visuals, ISSN: 3006-2705, 2(2), 54-58. https://ijbmv.com/index.php/home/article/view/76
  47. Secure Federated Learning Framework for Distributed Ai Model Training in Cloud Environments. (2019). International Journal of Open Publication and Exploration, ISSN: 3006-2853, 7(1), 31-39. https://ijope.com/index.php/home/article/view/145
  48. Challa, S. S. S., Tilala, M., Chawda, A. D., & Benke, A. P. (2019). Investigating the use of natural language processing (NLP) techniques in automating the extraction of regulatory requirements from unstructured data sources. Annals of Pharma Research, 7(5),
  49. Ghavate, N. (2018). An Computer Adaptive Testing Using Rule Based. Asian Journal For Convergence In Technology (AJCT) ISSN -2350-1146, 4(I). Retrieved from http://asianssr.org/index.php/ajct/article/view/443
  50. Tripathi, A. (2019). Serverless architecture patterns: Deep dive into event-driven, microservices, and serverless APIs. International Journal of Creative Research Thoughts (IJCRT), 7(3), 234-239. Retrieved from http://www.ijcrt.org
  51. Kanchetti, D., Munirathnam, R., & Thakkar, D. (2019). Innovations in workers compensation: XML shredding for external data integration. Journal of Contemporary Scientific Research, 3(8). ISSN (Online) 2209-0142.
  52. Aravind Reddy Nayani, Alok Gupta, Prassanna Selvaraj, Ravi Kumar Singh, & Harsh Vaidya. (2019). Search and Recommendation Procedure with the Help of Artificial Intelligence. International Journal for Research Publication and Seminar, 10(4), 148–166. https://doi.org/10.36676/jrps.v10.i4.1503
  53. Rinkesh Gajera , "Leveraging Procore for Improved Collaboration and Communication in Multi-Stakeholder Construction Projects", International Journal of Scientific Research in Civil Engineering (IJSRCE), ISSN : 2456-6667, Volume 3, Issue 3, pp.47-51, May-June.2019
  54. Gudimetla, S. R., et al. (2015). Mastering Azure AD: Advanced techniques for enterprise identity management. Neuroquantology, 13(1), 158-163. https://doi.org/10.48047/nq.2015.13.1.792
  55. Gudimetla, S. R., & et al. (2015). Beyond the barrier: Advanced strategies for firewall implementation and management. NeuroQuantology, 13(4), 558-565. https://doi.org/10.48047/nq.2015.13.4.876
  56. Bhavesh Kataria, "Variant of RSA-Multi prime RSA, International Journal of Scientific Research in Science, Engineering and Technology, Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 1, Issue 1, pp.09-11, 2014. Available at https://doi.org/10.32628/ijsrset14113

International Journal of Scientific Research in Science, Engineering and Technology

Downloads

Published

2019-05-30

Issue

Volume 6, Issue 3, May-June-2019

Section

Research Articles

License

Copyright (c) IJSRSET

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Swethasri Kavuri "Automation in Distributed Shared Memory Testing for Multi-Processor Systems" International Journal of Scientific Research in Science, Engineering and Technology (IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 6, Issue 3, pp.508-521, May-June-2019. Available at doi : https://doi.org/10.32628/IJSRSET12411594