In the engineering and scientific domains software commonly has a long lifespan, lasting decades instead of years. Due to this lifespan, software often outlives the current generation of hardware, and in turn needs to be modified to execute on newer classes of hardware architectures. Supporting developers in this difficult software maintenance activity is very important in order to improve their productivity, reduce bugs, and prevent architectural erosion. Our position is that the use of textual and structural analyses coupled with platform usage patterns extracted by mining similar open source projects can improve the quality and efficiency of scientific and engineering software maintenance.