Testing resource allocation is a core problem in software testing. Most of the existing related studies assume that the software architecture is static and rarely consider cost constraints. To address this problem， a software testing resource allocation algorithm for dynamic changes in architecture was proposed. Firstly， a multi-stage multi-objective multi-constraint testing resource allocation model with dynamically changing architecture was constructed. Then， based on parameter re-estimation and generalized differential evolution， the population re-initialization was added to the algorithm， which was able to reduce the algorithm search space and improve the algorithm performance. Finally， a new repair processing mechanism was added to the algorithm， which was able to eliminate the invalid solutions generated by the algorithm effectively. Compared with the solution sets obtained by the Multi-Objective Differential Evolution based on Weighted Normalized Sum （WNS-MODE） algorithm and Dynamic Testing Resource Allocation based on Generalized Differential Evolution 3 （DTRA-GDE3） algorithm， the solution set obtained by the proposed algorithm has the capacity value improved by about 11.81 times and 0.39 times respectively. In terms of coverage value metrics， the proposed algorithm completely covered the WNS-MODE algorithm and improved 81 percentage points with respect to the DTRA-GDE3 algorithm. In terms of the super volume value metrics， the proposed algorithm improved nearly 6 and 9 times， respectively. Experimental results show that the proposed algorithm can better adapt to the dynamic changes in software architecture， can provide more and better testing resource allocation schemes for dynamic testing of software products， and meets the dynamic changes in user requirements.

Testing resource allocation is one of the basic problems in software testing. However， most existing studies focus on the parallel-series modular software models but rarely consider the architecture-based software models. To this end， firstly， aiming at the test environment with dynamic changes of reliability and error number， a multi-stage and multi-objective testing resource allocation model was constructed based on the architecture. Then， a multi-stage and multi-objective testing resource allocation algorithm for dynamic reliability and error number was designed on the basis of parameter re-estimation， population re-initialization， generalized differential evolution， and weighted normalized sum. Finally， in the simulation experiments， compared with the existing Multi-Objective Differential Evolution based on Weighted Normalized Sum （WNS-MODE） algorithm， the proposed algorithm was able to obtain better solution sets on the architecture-based software model instances with different structures. Specifically， the capacity values increased by about 16 times， the coverage values increased by about 84 percentage points， and the hypervolume values increased by about 6 times. Experimental results demonstrate that the proposed algorithm can better adapt to the dynamic changes of reliability and error number， and can provide more and better testing resource allocation schemes for the dynamic testing of architecture-based software models.