The effects of NaCl on growth, contents of proteins and proline, and activities of catalase, peroxidase and polyphenol oxidase were investigated in seedlings and calli of Trigonella foenum-graecum L. and T. aphanoneura Rech. f. Seeds and hypocotyl explants were cultured on Murashige and Skoog medium supplemented with 0, 50, 100, 150 and 200 mM NaCl. Seed germination and the fresh and dry mass of the seedlings decreased significantly under salinity. In both species significant increases in protein content of seedlings over that of control were observed at 150 and 200 mM NaCl. Protein content in calli decreased at 200 mM NaCl over that of control. Protein content was higher in seedlings than in calli at all NaCl concentrations. Conversely, proline content was lower in seedlings than in calli at all the tested NaCl concentrations. NaCl caused changes in the activities of peroxidase, catalase and polyphenol oxidase in seedlings and calli.Additional key words: catalase, in vitro culture, peroxidase, polyphenol oxidase, salinity.
In this paper, we describe (con) 2 colic testing -a systematic testing approach for concurrent software. Based on concrete and symbolic executions of a concurrent program, (con) 2 colic testing derives inputs and schedules such that the execution space of the program under investigation is systematically explored. We introduce interference scenarios as key concept in (con) 2 colic testing. Interference scenarios capture the flow of data among different threads and enable a unified representation of path and interference constraints. We have implemented a (con) 2 colic testing engine and demonstrate the effectiveness of our approach by experiments.
We propose null-pointer dereferences as a target for finding bugs in concurrent programs using testing. A null-pointer dereference prediction engine observes an execution of a concurrent program under test and predicts alternate interleavings that are likely to cause null-pointer dereferences. Though accurate scalable prediction is intractable, we provide a carefully chosen novel set of techniques to achieve reasonably accurate and scalable prediction. We use an abstraction to the shared-communication level, take advantage of a static lock-set based pruning, and finally, employ precise and relaxed constraint solving techniques that use an SMT solver to predict schedules. We realize our techniques in a tool, ExceptioNULL, and evaluate it over 13 benchmark programs and find scores of nullpointer dereferences by using only a single test run as the prediction seed for each benchmark.
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