Abstract
For software developers as well as software product users, fault removal efficiency is crucial. Developers can estimate the amount of work required by evaluating the proportion of addressed faults. At the same time, the level of trust in utilizing the software product can be determined by customers, based on this information. The proposed software reliability growth model considers fault removal efficiency relevant to contemporary scenarios characterized by automated testing and debugging tools. A comparison between the proposed model and other existing models is conducted by utilizing two data sets from software testing. Additionally, the best release plans are created by considering warranty costs, risk costs, and error removal costs while still meeting reliability requirements.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Aggarwal AG, Dhaka V, Nijhawan N (2017) Reliability analysis for multi-release open-source software systems with change point and exponentiated weibull fault reduction factor. Life Cycle Reliab Saf Eng 6:3–14. https://doi.org/10.1007/s41872-017-0001-0
Ahmad N, Bokhari M, Quadri S, Khan MG (2008) The exponentiated weibull software reliability growth model with various testing-efforts and optimal release policy: a performance analysis. Int J Qual Reliab Manag. https://doi.org/10.1108/02656710810846952
Chang IH, Pham H, Lee SW, Song KY (2014) A testing-coverage software reliability model with the uncertainty of operating environments. Int J Syst Sci: Op Logist 1(4):220–227. https://doi.org/10.1080/23302674.2014.970244
Chatterjee S, Shukla A (2019) A unified approach of testing coverage-based software reliability growth modelling with fault detection probability, imperfect debugging, and change point. J Softw: Evolut Process 31(3):2150. https://doi.org/10.1002/smr.2150
Chatterjee S, Shukla A, Pham H (2019) Modeling and analysis of software fault detectability and removability with time variant fault exposure ratio, fault removal efficiency, and change point. Proc Inst Mech Eng, Part O: J Risk Reliab 233(2):246–256. https://doi.org/10.1177/1748006X18772930
Chatterjee S, Chaudhuri B, Bhar C, Shukla A (2016) Modeling and analysis of reliability and optimal release policy of software with testing domain coverage efficiency. In: 2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions)(ICRITO), pp 90–95. https://doi.org/10.1109/ICRITO.2016.7784932 . IEEE
Chiu K-C, Huang Y-S, Lee T-Z (2008) A study of software reliability growth from the perspective of learning effects. Reliab Eng Syst Saf 93(10):1410–1421. https://doi.org/10.1016/j.ress.2007.11.004
Driel WD, Bikker J, Tijink M (2021) Prediction of software reliability. Microelectron Reliab 119:114074. https://doi.org/10.1016/j.microrel.2021.114074
Farooq SU, Quadri S, Ahmad N (2012) Metrics, models and measurements in software reliability. In: 2012 IEEE 10th International Symposium on Applied Machine Intelligence and Informatics (SAMI), pp 441–449. https://doi.org/10.1109/SAMI.2012.6209008 . IEEE
Gao K (2021) Simulated software testing process and its optimization considering heterogeneous debuggers and release time. IEEE Access 9:38649–38659. https://doi.org/10.1109/ACCESS.2021.3064296
Goel AL, Okumoto K (1979) Time-dependent error-detection rate model for software reliability and other performance measures. IEEE Trans Reliab 28(3):206–211. https://doi.org/10.1109/TR.1979.5220566
Gupta S, Mishra A, Chawla M (2016) Analysis and recommendation of common fault and failure in software development systems. In: 2016 International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES), pp 1730–1734. https://doi.org/10.1109/SCOPES.2016.7955739 . IEEE
Huang C-Y, Lin C-T, Kuo S-Y, Lyu MR, Sue C-C (2004) Software reliability growth models incorporating fault dependency with various debugging time lags. In: Proceedings of the 28th Annual International Computer Software and Applications Conference. COMPSAC, pp 186–191. https://doi.org/10.1109/CMPSAC.2004.1342826 . IEEE
Huang C-Y, Lyu MR (2005) Optimal release time for software systems considering cost, testing-effort, and test efficiency. IEEE Trans Reliab 54(4):583–591. https://doi.org/10.1109/TR.2005.859230
Iqbal J (2017) Software reliability growth models: a comparison of linear and exponential fault content functions for study of imperfect debugging situations. Cogent Eng 4(1):1286739. https://doi.org/10.1080/23311916.2017.1286739
Jelinski Z, Moranda P (1972) Software reliability research. In: Statistical Computer Performance Evaluation, pp. 465–484. Elsevier. https://doi.org/10.1016/B978-0-12-266950-7.50028-1
Jhaa M, Jha R (2020) Optimal release time for software systems. In: 2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS), pp 1155–1160. https://doi.org/10.1109/ICACCS48705.2020.9074453 . IEEE
Jiang W, Zhang C, Liu D, Liu K, Sun Z, Wang J, Qiu Z, Lv W (2022) Srgm decision model considering cost-reliability. Int J Digit Crime Forensics (IJDCF) 14(2):1–19. https://doi.org/10.4018/IJDCF.302873
Kapur P, Panwar S, Singh O, Kumar V (2019) Joint release and testing stop time policy with testing-effort and change point. Risk Based Technol. https://doi.org/10.1007/978-981-13-5796-1_12
Kelion L (2015) Airbus a400m plane crash linked to software fault
Khurshid S, Shrivastava A, Iqbal J (2021) Effort based software reliability model with fault reduction factor, change point and imperfect debugging. Int J Inform Technol 13:331–340. https://doi.org/10.1007/s41870-019-00286-x
Khurshid S, Iqbal J, Malik IA, Yousuf B (2022) Modelling of nhpp based software reliability growth model from the perspective of testing coverage, error propagation and fault withdrawal efficiency. Int J Reliab Qual Saf Eng. https://doi.org/10.1142/S0218539322500139
Li Q, Pham H (2021) Software reliability modeling incorporating fault detection and fault correction processes with testing coverage and fault amount dependency. Mathematics 10(1):60. https://doi.org/10.3390/math10010060
Ohba M (1984) Inflection s-shaped software reliability growth model. In: Stochastic Models in Reliability Theory: Proceedings of a Symposium Held in Nagoya, Japan, April 23–24, 1984, pp 144–162. https://doi.org/10.1007/978-3-642-45587-2_10 . Springer
Park S (2021) A comparative study on the attributes of nhpp software reliability model based on exponential family and non-exponential family distribution. J Theor Appl Inf Technol 99(23):5735–5747
Pham H (2007) System Software Reliability. Springer
Pham H, Zhang X (1997) An nhpp software reliability model and its comparison. Int J Reliab Qual Saf Eng 4(03):269–282. https://doi.org/10.1142/S0218539397000199
Pham H, Zhang X (2003) Nhpp software reliability and cost models with testing coverage. Eur J Oper Res 145(2):443–454. https://doi.org/10.1016/S0377-2217(02)00181-9
Pham H, Nordmann L, Zhang Z (1999) A general imperfect-software-debugging model with s-shaped fault-detection rate. IEEE Trans Reliab 48(2):169–175. https://doi.org/10.1109/24.784276
Pradhan SK, Kumar A, Kumar V (2022) An effort allocation model for a three stage software reliability growth model. In: Predictive Analytics in System Reliability, pp 263–282. Springer. https://doi.org/10.1007/978-3-031-05347-4_17
Pradhan V, Kumar A, Dhar J (2022) Modelling software reliability growth through generalized inflection s-shaped fault reduction factor and optimal release time. Proc Inst Mech Eng, Part O: J Risk Reliab 236(1):18–36. https://doi.org/10.1177/1748006X211033713
Pradhan V, Dhar J, Kumar A (2023) Testing coverage-based software reliability growth model considering uncertainty of operating environment. Syst Eng. https://doi.org/10.1002/sys.21671
Samal U, Kumar A (2023) Redefining software reliability modeling: embracing fault-dependency, imperfect removal, and maximum fault considerations. Qual Eng. https://doi.org/10.1080/08982112.2023.2241067
Samal U, Kushwaha S, Kumar A (2023) A testing-effort based srgm incorporating imperfect debugging and change point. Reliab: Theory Appl. https://doi.org/10.24412/1932-2321-2023-172-86-93
Saraf I, Iqbal J (2019) Generalized software fault detection and correction modeling framework through imperfect debugging, error generation and change point. Int J Inform Technol 11:751–757. https://doi.org/10.1007/s41870-019-00321-x
Saraf I, Iqbal J (2019) Generalized multi-release modelling of software reliability growth models from the perspective of two types of imperfect debugging and change point. Qual Reliab Eng Int 35(7):2358–2370. https://doi.org/10.1002/qre.2516
Sgarbossa F, Pham H (2010) A cost analysis of systems subject to random field environments and reliability. IEEE Trans Syst Man Cybern Part C (Appl Rev) 40(4):429–437. https://doi.org/10.1109/TSMCC.2010.2042713
Song KY, Chang IH, Pham H (2017) An nhpp software reliability model with s-shaped growth curve subject to random operating environments and optimal release time. Appl Sci 7(12):1304. https://doi.org/10.3390/app7121304
Song KY, Chang IH, Pham H (2019) Nhpp software reliability model with inflection factor of the fault detection rate considering the uncertainty of software operating environments and predictive analysis. Symmetry 11(4):521. https://doi.org/10.3390/sym11040521
Verma V, Anand S, Kapur P, Aggarwal AG (2022) Unified framework to assess software reliability and determine optimal release time in presence of fault reduction factor, error generation and fault removal efficiency. Int J Syst Assur Eng Manag 13(5):2429–2441. https://doi.org/10.1007/s13198-022-01653-x
Wang L, Hu Q, Liu J (2016) Software reliability growth modeling and analysis with dual fault detection and correction processes. IIE Trans 48(4):359–370. https://doi.org/10.1080/0740817X.2015.1096432
Wood A (1996) Software reliability growth models. Tandem Tech Rep 96(130056):900
Yamada S, Ohba M, Osaki S (1984) S-shaped software reliability growth models and their applications. IEEE Trans Reliab 33(4):289–292. https://doi.org/10.1109/TR.1984.5221826
Yamada S, Ohtera H, Narihisa H (1986) Software reliability growth models with testing-effort. IEEE Trans Reliab 35(1):19–23. https://doi.org/10.1109/TR.1986.4335332
Yamada S, Tokuno K, Osaki S (1992) Imperfect debugging models with fault introduction rate for software reliability assessment. Int J Syst Sci 23(12):2241–2252. https://doi.org/10.1080/00207729208949452
Zhang X, Pham H (1998) A software cost model with warranty cost, error removal times and risk costs. IIE Trans 30(12):1135–1142. https://doi.org/10.1080/07408179808966570
Zhang X, Teng X, Pham H (2003) Considering fault removal efficiency in software reliability assessment. IEEE Trans Syst Man Cybern-Part A: Syst Hum 33(1):114–120. https://doi.org/10.1109/TSMCA.2003.812597
Zheng S (2002) Dynamic release policies for software systems with a reliability constraint. IIE Trans 34(3):253–262. https://doi.org/10.1080/07408170208928867
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Samal, U., Kumar, A. A software reliability model incorporating fault removal efficiency and it’s release policy. Comput Stat (2023). https://doi.org/10.1007/s00180-023-01430-9
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s00180-023-01430-9