Abstract-Software testing is the process to uncover requirement, design and coding errors in the program. It is used to identify the correctness, completeness, security and quality of software products against a specification. Software testing is the process used to measure the quality of developed computer software. It exhibits all mistakes, errors and flaws in the developed software. There are many approaches to software testing, but effective testing of complex product is essentially a process of investigation, not merely a matter of creating and following route procedure. It is not possible to find out all the errors in the program. This fundamental problem in testing thus throws an open question, as to what would be the strategy we should adopt for testing. In our paper, we have described and compared the three most prevalent and commonly used software testing techniques for detecting errors, they are: white box testing, black box testing and grey box testing.
Using surplus production model packages of ASPIC (a stock-production model incorporating covariates) and CEDA (Catch effort data analysis), we analyzed the catch and effort data of Sillago sihama fishery in Pakistan. ASPIC estimates the parameters of MSY (maximum sustainable yield), F msy (fishing mortality), q (catchability coefficient), K (carrying capacity or unexploited biomass) and B1/K (maximum sustainable yield over initial biomass). The estimated non-bootstrapped value of MSY based on logistic was 598 t and that based on the Fox model was 415 t, which showed that the Fox model estimation was more conservative than that with the logistic model. The R 2 with the logistic model (0.702) is larger than that with the Fox model (0.541), which indicates a better fit. The coefficient of variation (cv) of the estimated MSY was about 0.3, except for a larger value 88.87 and a smaller value of 0.173. In contrast to the ASPIC results, the R 2 with the Fox model (0.651 -0.692) was larger than that with the Schaefer model (0.435 -0.567), indicating a better fit. The key parameters of CEDA are: MSY, K, q, and r (intrinsic growth), and the three error assumptions in using the models are normal, log normal and gamma. Parameter estimates from the Schaefer and Pella-Tomlinson models were similar. The MSY estimations from the above two models were 398 t, 549 t and 398 t for normal, log-normal and gamma error distributions, respectively. The MSY estimates from the Fox model were 381 t, 366 t and 366 t for the above three error assumptions, respectively. The Fox model estimates were smaller than those for the Schaefer and the Pella-Tomlinson models. In the light of the MSY estimations of 415 t from ASPIC for the Fox model and 381 t from CEDA for the Fox model, MSY for S. sihama is about 400 t. As the catch in 2003 was 401 t, we would suggest the fishery should be kept at the current level. Production models used here depend on the assumption that CPUE (catch per unit effort) data used in the study can reliably quantify temporal variability in population abundance, hence the modeling results would be wrong if such an assumption is not met. Because the reliability of this CPUE data in indexing fish population abundance is unknown, we should be cautious with the interpretation and use of the derived population and management parameters.
In this paper, the effects of carbon nanotubes (CNT) implantation and sisal fibre size on the electrical properties of sisal fibre-reinforced epoxy composites are reported. For this purpose, the epoxy composites reinforced with CNT-implanted sisal fibre of 5 mm and 10 mm lengths were prepared by hand moulding and samples characterized for their electrical properties, such as dielectric constant (ε′), dielectric dissipation factor (tan δ) and AC conductivity (σ ac ) at different temperatures and frequencies. It was observed that the dielectric constant increases with increase in temperature and decreases with increase in frequency from 500 Hz to 5 KHz. Interestingly, the sample having CNT-implanted sisal fibre of 5 mm length exhibited the highest value of dielectric constant than the one with length 10 mm. This is attributed to the increased surface area of sisal fibre and enhancement of the interfacial polarization. At a constant volume and a length of 5 mm of the fibres, the number of interfaces per unit volume element is high and results in a higher interfacial polarization. The interfaces decrease as the fibre length increases, and therefore, the value of ε′ decreases at 10 mm fibre length. The peak value of the dielectric constant decreases with increasing frequency. A continuous decrease in dissipation factor (tan δ) with increasing frequency for all samples was observed, while at lower temperatures, the values of tan δ remains approximately same. The AC conductivity for 5 mm length sisal epoxy composite and 10 mm length sisal fibre-epoxy composites is higher than that of pure epoxy at all the frequencies.
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