The invention belongs to the technical field of
software development and testing, and discloses an
artificial intelligence-based
software development automatic
test case generation
system, which is characterized in that an immune
heuristic case self-repairing module is adopted, defects are regarded as antigens,
antibody cases capable of being self-updated are generated by using a clone
selection algorithm, and a
gene rearrangement mechanism is automatically triggered when an interface is changed, so that the
test efficiency is improved. The details of the use case are adjusted while the core detection logic is reserved; compared with a traditional method, the mechanism can realize use case dynamic
adaptation without manual intervention, the maintenance
workload is remarkably reduced, and the method is particularly suitable for a complex
software system with frequent iteration; the space-time
coupling test scene generation engine fuses dynamic scenes such as interaction and state transition of a module and short-time operation after precise coverage login by using a space-time convolutional network; the cross-dimension holographic use case synthesis module integrates multi-
source data such as codes, hardware and user behaviors through
tensor decomposition to generate a composite use case; functions and performance of software in a complex scene can be comprehensively verified, and test blind areas are remarkably reduced.