Continuous Double Auction(CDA) is one of the electronic marketplaces for trading commodities or services. Different from the single-side auction types, such as English auction and Dutch auction, CDA allows multiple sellers and multiple buyers to update their asks and bids at the same time continuously through the trading period. The information of the ongoing auction is dynamically changed in CDA. The problem on how to respond quickly to the changing markets and how to make the proper ask or bid action is interesting and therefore CDA attracts many researchers to do the research of it. This paper discusses the automatic bidding strategy using Genetic Network Programming(GNP) with Rectifying Nodes (RNs) in CDA environment. Additionally, the proposed bidding strategy used some basic heuristic control functions for helping the auction agent to make his asking or bidding decisions. Due to the directed graph structure of GNP, the proposed method judges and analyzes the auction information, where at each time step, the most competitive and suitable ask or bid price is determined without losing profit considering various aspects of the environment. The GNP-RN strategy was compared with some other methods in the experiments which constitute a group of CDAs under different settings. The results of the experiments showed that the agent using the proposed GNP-RN strategy could get the highest profit among all the agents.