Mutation testing

Abstract: A series of human androgen receptor (AR) deletion mutants was constructed to study the relationship between the structural domains and their different functions in the AR protein. Human AR mutants were expressed in COS-1 and HeLa cells to investigate hormone binding, transcriptional activation, and subcellular localization. The wild-type human AR (AR 1910) was expressed as a 110- to 112-kDa doublet, as revealed on immunoblots. All mutant AR proteins also migrated as doublets, except for one. This AR has a deletion from amino acid residues 51-211 and migrated as a single protein band, possibly due to altered posttranslational modification. The AR steroid-binding domain is encoded by approximately 250 amino acid residues in the Cterminal end. Deletions in this domain as well as truncation of the last 12 C-terminal amino acid residues abolished hormone binding. Cotransfection studies in HeLa cells showed that transcriptional activation of an androgen-regulated reporter gene construct was induced by the wildtype human AR. Mutational analysis revealed two regions in the N-terminal part, encoded by amino acid residues 51-211 and 244-360, to be essential for this transcriptional activation. Deletion of the hormone-binding domain yielded a constitutively active AR protein, indicating that in the absence of hormone this domain displays an inhibitory function. In the presence of its ligand, the wild-type AR was located in the cell nucleus. In the absence of androgens the receptor was mainly nuclear, but cytoplasmic localization was observed as well. In contrast, an AR deletion mutant lacking part of the DNAbinding domain and part of the hinge region was exclusively cytoplasmic in the absence of hormone. This mutant AR lacks a region that is highly conserved among steroid receptors and homologous to the simian virus-40 large T-antigen- and nucleoplas

Abstract: To assess the quality of test suites, mutation analysis seeds artificial defects (mutations) into programs; a nondetected mutation indicates a weakness in the test suite We present an automated approach to generate unit tests that detect these mutations for object-oriented classes This has two advantages: First, the resulting test suite is optimized toward finding defects modeled by mutation operators rather than covering code Second, the state change caused by mutations induces oracles that precisely detect the mutants Evaluated on 10 open source libraries, our μtest prototype generates test suites that find significantly more seeded defects than the original manually written test suites

Abstract: Herein, we have studied a consanguineous Egyptian family with two children diagnosed with severe autosomal recessive osteogenesis imperfecta (AR-OI) and a large umbilical hernia. Homozygosity mapping in this family showed lack of linkage to any of the previously known AR-OI genes, but revealed a 10.27 MB homozygous region on chromosome 8p in the two affected sibs, which comprised the procollagen I C-terminal propeptide (PICP) endopeptidase gene BMP1. Mutation analysis identified both patients with a Phe249Leu homozygous missense change within the BMP1 protease domain involving a residue, which is conserved in all members of the astacin group of metalloproteases. Type I procollagen analysis in supernatants from cultured fibroblasts demonstrated abnormal PICP processing in patient-derived cells consistent with the mutation causing decreased BMP1 function. This was further confirmed by overexpressing wild type and mutant BMP1 longer isoform (mammalian Tolloid protein [mTLD]) in NIH3T3 fibroblasts and human primary fibroblasts. While overproduction of normal mTLD resulted in a large proportion of proα1(I) in the culture media being C-terminally processed, proα1(I) cleavage was not enhanced by an excess of the mutant protein, proving that the Phe249Leu mutation leads to a BMP1/mTLD protein with deficient PICP proteolytic activity. We conclude that BMP1 is an additional gene mutated in AR-OI.

Abstract: Mutation analysis generates tests that distinguish variations, or mutants, of an artifact from the original. Mutation analysis is widely considered to be a powerful approach to testing, and hence is often used to evaluate other test criteria in terms of mutation score, which is the fraction of mutants that are killed by a test set. But mutation analysis is also known to provide large numbers of redundant mutants, and these mutants can inflate the mutation score. While mutation approaches broadly characterized as reduced mutation try to eliminate redundant mutants, the literature lacks a theoretical result that articulates just how many mutants are needed in any given situation. Hence, there is, at present, no way to characterize the contribution of, for example, a particular approach to reduced mutation with respect to any theoretical minimal set of mutants. This paper's contribution is to provide such a theoretical foundation for mutant set minimization. The central theoretical result of the paper shows how to minimize efficiently mutant sets with respect to a set of test cases. We evaluate our method with a widely-used benchmark.