In chemistry, one of the crucial problems has been the structure identification of molecules, whose chemical composition is unknown. This research topic has impacts on various fields such as natural product and drug discovery studies. For the efficient and the fast identification process, computer assisted structure elucidation (CASE) toolkits has been developed. These tools utilise spectral data of unknown molecules as the input to determine their structure. The effectiveness of these software primarily depends on how well the structure generators perform. The basic input for these generators is the molecular formula of the unknown molecule to generate its unique list of isomers. In cheminformatics, there has been several software for the structure generation, especially, MOLGEN was considered as the de-facto gold standard in the field due to its speed and efficiency. However, it is a commercial tool and there was the need of an efficient open-source structure generators, in other words, chemical graph generators. To fulfil this need, the development of efficient open-source chemical graph generators was aimed for this PhD study, and the aim was succeeded by the development of two software, namely, MAYGEN and surge. First MAYGEN was developed as an alternative to MOLGEN. It was benchmarked against MOLGEN and was just around 3 times slower than MOLGEN. Following MAYGEN, another software, surge, was developed as an open-source chemical graph generator. It was benchmarked against MOLGEN for randomly chosen natural products' molecular formulae. Based on the results, surge is approximately 100 times faster than MOLGEN, which made it the state-of-art in the field.