RESTful APIs are arguably the most popular endpoints for accessing Web services. Blackbox testing is one of the emerging techniques for ensuring the reliability of RESTful APIs. The major challenge in testing RESTful APIs is the need for correct sequences of API operation calls for in-depth testing. To build meaningful operation call sequences, researchers have proposed techniques to learn and utilize the API dependencies based on OpenAPI specifications. However, these techniques either lack the overall awareness of how all the APIs are connected or the flexibility of adaptively fixing the learned knowledge.

MOTIVATION: Genome-wide association studies (GWAS) have played an important role in identifying genetic variants underlying human complex traits. However, its success is hindered by weak effect at causal variants and presence of noise at non-causal variants. In an effort to overcome these difficulties, a previous study proposed a regularized regression method that penalizes on the difference of signal strength between two consecutive single-nucleotide polymorphisms (SNPs). RESULTS: We provide a generalization to the afore-mentioned method so that more adjacent SNPs can be incorporated. The choice of optimal number of SNPs is studied. Simulation studies indicate that when consecutive SNPs have similar absolute coefficients our method performs better than using LASSO penalty. In other situations, our method is still comparable to using LASSO penalty. The practical utility of the proposed method is demonstrated by applying it to Genetic Analysis Workshop 16 rheumatoid arthritis GWAS data. AVAILABILITY AND IMPLEMENTATION: An implementation of the proposed method is provided in R package MWLasso. CONTACT: [email protected].