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Measuring the Bytecode Quality of Object-Oriented Software

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Soft Computing: Theories and Applications

Abstract

Software metrics can be delineated as the practice of quantifying various characteristics of the software development process in order to obtain valuable and pertinent information for effectual management throughout the development process. This research work’s aspiration is to investigate quality metrics and develop a method which can be utilized to evaluate the quality object-oriented programs from its bytecode.

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References

  1. Xu J, Ho D, Capretz LF (2010) An empirical study on the procedure to derive software quality estimation models. Int J Comput Sci Inf Technol (IJCSIT) 2(4)

    Google Scholar 

  2. Demyanova Y, Pani T, Veith H, Zuleger F (2015) Empirical software metrics for benchmarking of verification tools. In: Computer aided verification. Springer International Publishing, pp 561–579

    Google Scholar 

  3. Padmini KV, Dilum Bandara HMN, Perera I (2015) Use of software metrics in agile software development process. In: Moratuwa engineering research conference (MERCon). IEEE

    Google Scholar 

  4. Khomh F, Adams B, Dhaliwal T, Zou Y (2015) Understanding the impact of rapid releases on software quality. Empir Softw Eng 20(2):336–373

    Article  Google Scholar 

  5. Cartwright M, Shepperd M (2000) An empirical investigation of an object-oriented software system. IEEE Trans Softw Eng 26(7):786–796

    Article  Google Scholar 

  6. Ganesan K, Khoshgoftaar TM, Allen EB (2000) Case-based software quality prediction. Int J Softw Eng Knowl Eng 10(2):139–152

    Article  Google Scholar 

  7. Xu Z, Khoshgoftaar TM (2000) Software quality prediction for high-assurance network telecommunications systems. Comput J 44(6):557–568

    Article  Google Scholar 

  8. Thwin MMT, Quah TS (2005) Application of neural networks for software quality prediction using object-oriented metrics. J Syst Softw 76(2):147–156

    Article  Google Scholar 

  9. Pai GJ, Dugan JB (2007) Empirical analysis of software fault content and fault proneness using Bayesian methods. IEEE Trans Softw Eng 33(10):675–686

    Article  Google Scholar 

  10. Chidamber SR, Kemerer CF (1994) A metrics suite for object-oriented design. IEEE Trans Softw Eng 20(6):476–493

    Article  Google Scholar 

  11. Subramanyan R, Krisnan MS (2003) Empirical analysis of CK metrics for object-oriented design complexity: implications for software defects. IEEE Trans Softw Eng 29(4):297–310

    Article  Google Scholar 

  12. Yu P, Systa T, Muller H (2002) Predicting fault-proneness using OO metrics: an industrial case study. In: Proceedings of sixth European conference on software maintenance and reengineering, pp 99–107

    Google Scholar 

  13. Khoshgoftaar TM, Gao K (2007) Count models for software quality estimation. IEEE Trans Reliab 56(2):212–222

    Article  Google Scholar 

  14. Halstead MH (1977) Elements of software science. Elsevier North Holland, New York

    MATH  Google Scholar 

  15. McCabe TJ (1976) A complexity measure. IEEE Trans Softw Eng 2(4):308–320

    Article  MathSciNet  Google Scholar 

  16. Abreu FB, Melo W (1996) Evaluating the impact of object oriented design on software quality. In: 3rd international symposium on software metrics, Berlin, pp 90–99

    Google Scholar 

  17. Agarwal A (2013) Implementation of cylomatrix complexity matrix. J Nat Inspir Comput 1

    Google Scholar 

  18. Saleem A, Agarwal AK (2016) Analysis and design of secure web services. In: Proceedings of fifth international conference on soft computing for problem solving. Springer, Singapore

    Google Scholar 

  19. Agarwal T, Agarwal AK, Singh SK (2014) Cloud computing security: issues and challenges. In: Proceedings of SMART-2014, pp 10–14

    Google Scholar 

  20. Joshi M, Agarwal AK, Gupta B (2019) Fractal image compression and its techniques: a review. In: Ray K, Sharma T, Rawat S, Saini R, Bandyopadhyay A (eds) Soft computing: theories and applications. Advances in intelligent systems and computing, vol 742. Springer, Singapore

    Google Scholar 

  21. Gupta N, Agarwal DAK (2018) Object identification using super sonic sensor: Arduino object radar. In: 2018 international conference on system modeling & advancement in research trends (SMART), Moradabad, pp 92–96

    Google Scholar 

  22. Tiwari RG, Srivastava AP, Bhardwaj G, Kumar V (2021) Exploiting UML diagrams for test case generation: a review. In: 2021 2nd international conference on intelligent engineering and management (ICIEM), Apr 2021. IEEE, pp 457–460

    Google Scholar 

  23. Agrawal N, Jain A, Agarwal A (2019) Simulation of network on chip for 3D router architecture. Int J Recent Technol Eng 8(1C2):58–62

    Google Scholar 

  24. Jindal RK, Agarwal AK, Sahoo AK (2020) Envisaging the road accidents using regression analysis. Int J Adv Sci Technol 29(5 Special Issue):1708–1716

    Google Scholar 

  25. Tiwari RG, Husain M, Srivastava V, Singh K (2011) A hypercube novelty model for comparing E-commerce and M-commerce. In: Proceedings of the 2011 international conference on communication, computing & security, pp 616–619

    Google Scholar 

  26. Chhabra R, Verma S, Krishna CR. A survey on driver behaviour detection techniques for intelligent transportation systems. https://ieeexplore.ieee.org/document/7943120

  27. Agarwal AK, Jain A (2019) Synthesis of 2D and 3D NoC mesh router architecture in HDL environment. J Adv Res Dyn Control Syst 11(04)

    Google Scholar 

  28. Tiwari RG, Husain M, Gupta B, Agrawal A (2010) Amalgamating contextual information into recommender system. In: 2010 3rd international conference on emerging trends in engineering and technology, Nov 2010. IEEE, pp 15–20

    Google Scholar 

  29. Jindal RK, Agarwal AK, Sahoo AK (2020) Data analytics for analysing traffic accidents. Test Eng Manag 83(14796)

    Google Scholar 

  30. Tiwari RG, Agarwal AK, Kaushal RK, Kumar N (2021) Prophetic analysis of bitcoin price using machine learning approaches. In: In 2021 6th international conference on signal processing, computing and control (ISPCC). IEEE, pp 428–432

    Google Scholar 

  31. Agarwal H, Tiwari P, Tiwari RG (2019) Exploiting sensor fusion for mobile robot localization. In: 2019 third international conference on I-SMAC (IoT in social, mobile, analytics and cloud) (I-SMAC), Dec 2019. IEEE, pp 463–466

    Google Scholar 

  32. Tiwari RG, Husain M, Srivastava V, Agrawal A (2011) Web personalization by assimilating usage data and semantics expressed in ontology terms. In: Proceedings of the international conference & workshop on emerging trends in technology, pp 516–521

    Google Scholar 

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Correspondence to Ambuj Kumar Agarwal .

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Agarwal, A.K., Tiwari, R.G., Khullar, V., Ahuja, R., Sharma, T. (2022). Measuring the Bytecode Quality of Object-Oriented Software. In: Kumar, R., Ahn, C.W., Sharma, T.K., Verma, O.P., Agarwal, A. (eds) Soft Computing: Theories and Applications. Lecture Notes in Networks and Systems, vol 425. Springer, Singapore. https://doi.org/10.1007/978-981-19-0707-4_5

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