In this paper, the development cost attributes were newly analyzed by applying the Exponential–type lifetime distributions (Burr-Hatke-exponential, ExponentialBasic, Exponential-exponential, Inverse-exponential) widely utilized in the field of software lifetime testing and quality evaluation to the software development cost model. Also, to verify the attributes of the analyzed development cost, after analyzing the future reliability, the optimal cost model was presented. For this study, an analysis algorithm using software failure time data was proposed to solve the research solution, the maximum likelihood estimation (MLE) was applied to solve the parameter values, and the nonlinear equation was calculated using the binary method. Simulations show that if the cost of removing one flaw found during the test phase increases, the development cost increases, but the release time does not change. However, if the cost of flaws correction discovered by operators increased, both development costs and release times increased. Therefore, we must remove all possible flaws at the testing stage to eliminate failures. In conclusion, First, the Exponential-exponential distribution model showed the best performance among the proposed models because it had the lowest software development cost and the highest future reliability. Second, the software development cost attributes of the Exponential-type lifetime distributions were newly analyzed. Third, through this data, it was able to help software developers to analyze the most economical development cost
Software Development Cost Model based on NHPP Gompertz Distribution