An Improved & Adaptive Software Development Methodology

The methods of software development have increased a lot from the beginning. From the first waterfall to current agile methodology there still have some drawbacks. For this reason, the software delivery is still a very challenging and heavy-duty work. In this paper, we proposed a new software development methodology which is easy to implement and will help software development companies a secure and robust software releases. The proposed SDLC process is known as 4A. The empirical result shows that the proposed methodology is more adaptive and flexible for developers and project managers

Learning-dependent structural plasticity of intracortical and sensory connections to functional domains of the olfactory tubercle

The olfactory tubercle (OT), which is a component of the olfactory cortex and ventral striatum, has functional domains that play a role in odor-guided motivated behaviors. Learning odor-guided attractive and aversive behavior activates the anteromedial (am) and lateral (l) domains of the OT, respectively. However, the mechanism driving learning-dependent activation of specific OT domains remains unknown. We hypothesized that the neuronal connectivity of OT domains is plastically altered through olfactory experience. To examine the plastic potential of synaptic connections to OT domains, we optogenetically stimulated intracortical inputs from the piriform cortex or sensory inputs from the olfactory bulb to the OT in mice in association with a food reward for attractive learning and electrical foot shock for aversive learning. For both intracortical and sensory connections, axon boutons that terminated in the OT domains were larger in the amOT than in the lOT for mice exhibiting attractive learning and larger in the lOT than in the amOT for mice exhibiting aversive learning. These results indicate that both intracortical and sensory connections to the OT domains have learning-dependent plastic potential, suggesting that this plasticity underlies learning-dependent activation of specific OT domains and the acquisition of appropriate motivated behaviors

Development of efficient t-way test data generation algorithm and execution strategies

For a typical software product, it is desired to test all possible combinations of input data in various configurations, Exhaustive testing is impossible to execute prior to release in the market. The lack of resources, cost factors and tight deadlines to market are some of the main factors that prevent this consideration. In current practice, usually the test-data are selected and executed randomly. Many useful strategies (2-Way and TWay sampling) were developed to generate test-data and facilitate smooth testing process. Comprehensive test data generation is nondeterministic polynomial hard problem (NP-complete). Hence, optimization in terms of number of generated test-data and execution time is in demand. Motivated by these, this thesis addresses the design, implementation and validation of four effective test data generation strategies in terms of 2-way and T-way as follows: (I) PS2Way (Pairwise Search for 2-way Test Data Generation) strategy is based on parameters pair technique. This strategy is able to reduce the number of test data, but the execution time is not optimized. (II) EasyA (Easy Algorithm for 2-way Test Data Generation) is developed based on matrix based calculation to overcome the time constrains by keeping the number of test data in an acceptable range. This strategy is unable to support non uniform values. (III) R2Way (Random Search for 2-way Test Data Generation) with execution tool is developed to support both uniform and non-uniform values using search based software engineering. R2Way outperforms other existing strategies but cannot support higher interaction level (T > 2). And finally, (IV) MTTG (Multi-Tuple based T-way Test Data Generation) strategy is developed inspiring kids “Card Game” to overcome the limitations of interaction strength. An executable prototype tool is also developed for auto test execution besides efficient test data generation. Empirical data shows that MTTG is effective and outperforms other strategies in terms of number of test data generation time (more than 74% improvement), maintaining a tolerable test data size. All the proposed strategies are simpler to implement and handle. They are also efficient in terms of execution time and able to generate highly reduced test data suites to fulfil the current demand (easy and faster process) by software development companies

MaxD K-Means: A clustering algorithm for auto-generation of centroids and distance of data points in clusters

K-Means is one of the unsupervised learning and partitioning clustering algorithms. It is very popular and widely used for its simplicity and fastness. The main drawback of this algorithm is that user should specify the number of cluster in advance. As an iterative clustering strategy, K-Means algorithm is very sensitive to the initial starting conditions. In this paper, we propose a clustering technique called MaxD K-Means clustering algorithm. MaxD K-Means algorithm auto generates initial k (the desired number of cluster) without asking for input from the user. MaxD K-means also used a novel strategy of setting the initial centroids. The experiment of the Max-D means has been conducted using synthetic data, which is taken from the Llyod’s K-Means experiments. The results from the new algorithm show that the number of iteration improves tremendously, and the number of iterations is reduced by confirming an improvement rate is up to 78%

MT2Way: A novel strategy for pair-wise test data generation

Reducing the number of test cases by utilizing minimum possible amount of time during the testing process of software and hardware is highly desirable. For ensuring the reliability of the method the combination of a complete set of available inputs is recommended to be executed. But generally an exhaustive numbers of test cases are hard to execute. Besides, test data generation is an NP-hard (non-deterministic polynomial-time hard) problem. This is likely to present considerable difficulties in defining the best possible method for generating the test data. The reduction of test cases depends on the interaction level, 2-way interaction or pair-wise test data can reduce high number of test cases and it efficiently addresses most of the software errors. This paper presents MT2Way, an effective 2-way interaction algorithm to generate the test data which is more acceptable in terms of the number of test cases and execution time. The performance tests show that MT2Way achieve better results in terms of system configuration, generated test size, and executing time as compared to other techniques

Framework of Persistence Layer Synchronous Replication to Improve Data Availability into a Heterogeneous System

Data replication is an important technique in peer to peer network, data grid architecture, clustering and distributed system, where it increases data availability and enhances data access and reliability and minimizes the cost of data transmission. In this paper, we proposed a framework and structure of synchronous replication from the persistence layer that supports heterogeneous system. In this framework, we developed the multithreading based persistence layer. Our objective is to make the persistence layer more adaptive. In this adaptive persistency system, the replication server will not depend on the main server, so forth, adding a new replication server will be easier than ever, easy to cope with heterogeneous system, cost minimizing and finally there will be no down time

EasyA: Easy and effective way to generate pairwise test data

Testing is a very important task to build error free software. As the resources and time to market is limited for a software product, it is impossible to perform exhaustive test i.e., to test all combinations of input data. To reduce the number of test cases in an acceptable level, it is preferable to use higher interaction level (t way, where t = 2). Pairwise (2- way or t = 2) interaction can find most of the software faults. This paper proposes a matrix based calculation for pairwise test data generation algorithm named EasyA to optimize the number of test cases. Java program has been used to test the performance of the algorithm. The performance is better than the existing algorithms/tools in terms of number of generated test cases and time consumption

Evaluation of Recently Developed Regression Equation with Direct Measurement of Low-density Lipoprotein Cholesterol in a Bangladeshi Population

Background: Meaningful underestimation of low-density lipoprotein (LDL) cholesterol is an important shortcoming of Friedewald’s formula (FF) at higher triglyceride (TG) levels. Recently a regression equation (RE) has been developed using lipid profiles in one setting and validated externally for the calculation of LDL cholesterol. This newly developed RE requires more studies in different settings. Objective: The aim of this study was to evaluate the performance of the regression equation against direct measurement. Materials and Methods: Lipid profiles of 600 subjects attending a tertiary healthcare center were included in this study. Specimens were collected and lipid profiles were measured by standard methods. Sixty two lipid profiles with TG above 400 mg/dL were excluded. Calculated LDL cholesterol values using FF and RE were compared with measured LDL cholesterol by Pearson’s correlation test, Passing & Bablok regression, accuracy within ±5% and ±12% of measured LDL cholesterol and two-tailed paired t test at various TG ranges. Results: The mean value of LDL cholesterol was 148.6 ± 37.2 mg/dL for direct measurement, 146.9 ± 42.4 mg/dL for FF and 148.6 ± 34.7 mg/dL for RE. The correlation coefficients of calculated LDL cholesterol values with measured LDL cholesterol were 0.949 (p<0.001) for FF and 0.959 (p<0.001) for RE. Passing & Bablok regression equation against measured LDL cholesterol was y = 0.897x + 16.2 for FF and y = 1.0842x – 13.1 for RE. Accuracy within ±5% of measured LDL cholesterol was 45% for FF, 57% for RE and within ±12% of measured LDL cholesterol was 84% for FF, 93% for RE. When calculated LDL cholesterol was compared with measured LDL cholesterol at different TG ranges, FF significantly underestimated LDL cholesterol at TG concentrations above 200 mg/dL whereas no significant difference was observed for RE. Conclusion: This study reveals that RE equation has similar performance to direct measurement for calculation of LDL cholestero

Hepatitis B Vireamia in Hepatitis B Surface Antigenemic Patients in Bangladesh

Abstract Objectives: This study evaluates the distribution of hepatitis B vireamia in patients with hepatitis B virus (HBV) infection. Methods: HBV-infected patients were enrolled in this study. HBV DNA tests were carried out using Smart Cycler II to detect HBV DNA level in serum samples of all HBsAg-positive patients. Results: The distribution of HBV DNA level was found significantly related to age groups (p&lt;0.05), gender group (p&lt;0.05), ALT group (p&lt;0.05), and HBeAg group (p&lt;0.05). The HBV DNA level was recorded to be significantly higher in the HBeAg-positive group (p&lt;0.05) in compared to the HBeAg-negative group. Conclusions: A low level of viral replication may persevere in chronic HBV-infected patients who are HBeAg-negative, and the level of HBV DNA was higher in the HBeAg-positive group