The quality of any product depends on the quality of the basis of making it, i.e., the quality of the requirements has strong effect on the quality of the end products. Proper requirements engineering is, however, not an established practice within the software developing community (Firesmith, 2005). This causes that most of all errors are introduced in the requirements phase and are caused by poorly written, ambiguous, unclear or missed requirements as reported by several studies (Firesmith, 2005; Martin, 1984; Damian, 2002). Failure to correctly specify the requirements can lead to major delays, cost overruns, commercial consequences including the loss of money, property, layoffs, and even the loss of lives.

Simulation is helpful in exploring alternatives, spotting flaws, and optimizing product performance before the detailed design. Simulation allows important decisions to be made on functionality and allocation early in the cycle based on simulation results.

However, as long as the RE process is in progress, the requirements engineers have to deal with incomplete and informally stated requirements. In practice, that means that in order to run simulations based on formal languages requirements engineers are forced to define a semantically correct and formal system model based on these incomplete and informal requirements. This is not feasible in many cases, and thus, there are some approaches that support simulating based on these informal descriptions. These technologies are the focus of this solution.