Natural Language (NL) requirements play a significant role in specifying the system design, implementation and testing processes. Nevertheless, NL requirements are generally syntactically ambiguous and semantically inconsistent. Issues with NL requirements can result into inaccurate and preposterous system design, implementation and testing. Moreover, informal nature of NL is a major hurdle in machine processing of system requirements specifications. To confront this problem, a requirement template is introduced, based on controlled NL to produce deterministic and consistent representation of the system. The ultimate focus of this thesis is to generate test cases from system specifications driven from requirements communicated in natural language. Manual software systems testing is a labour intensive, error prone and high cost activity. Traditionally, model-driven test generation approaches are employed for automated testing. However, system models are created manually for test generation. The test cases generated from system models are not generally deterministic and traceable with individual requirements. This thesis proposes an approach for software system testing based on template-driven requirements. This systematic approach is applied on the requirements elicited from system stakeholders. For this purpose natural language processing (NLP) methods are used. Using NLP approaches, useful information is extracted from controlled NL requirements and afterwards the gathered information is processed to generate test scenarios. Our inceptive observation exhibits that this method provides remarkable gains in terms of reducing the cost, time and complexity of requirements based testing.