A Critical Analysis of PSP Data Quality: Results from a Case Study

The Personal Software Process (PSP) is used by software engineers to gather and analyze data about their work. Published studies typically use data collected using the PSP to draw quantitative conclusions about its impact upon programmer behavior and product quality. However, our experience using PSP led us to question the quality of data both during collection and its later analysis. We hypothesized that data quality problems can make a significant impact upon the value of PSP measures—significant enough to lead to incorrect conclusions regarding process improvement. To test this hypothesis, we built a tool to automate the PSP and then examined 89 projects completed by ten subjects using the PSP manually in an educational setting. We discovered 1539 primary errors and categorized them by type, subtype, severity, and age. To examine the collection problem we looked at the 90 errors that represented impossible combinations of data and at other less concrete anomalies in Time Recording Logs and Defect Recording Logs. To examine the analysis problem we developed a rule set, corrected the errors as far as possible, and compared the original and corrected data. We found significant differences for measures such as yield and the cost-performance ratio, confirming our hypothesis. Our results raise questions about the accuracy of manually collected and analyzed PSP data, indicate that integrated tool support may be required for high quality PSP data analysis, and suggest that external measures should be used when attempting to evaluate the impact of the PSP upon programmer behavior and product quality.     

Automation and ISO 17025 test validation of a Toxoplasma Gondii antibodies enzyme-linked immunosorbent assay

The authors automated an enzyme-linked immunosorbent assay to detect porcine serum antibodies to Toxoplasma gondii. Two thousand swine sera can be assayed in two eight-hour shifts using a robotic workstation. The automated-ELISA programming is not complex and the test configuration is flexible. This high-throughput screening (HTS) a-ELISA can achieve a 10-fold increase (100→1000 tests) in test capacity over the manual method. The assay has been validated according to the requirements of the ISO/IEC 17025 standard. These include repeatability, reproducibility, and optimal threshold value studies. Other requirements are proficiency panel testing, analyst training, standard operation procedure, and equipment certifications.     

基于SVM的大样本集系统辨识与函数拟合仿真

支持向量机是一种优秀的学习方法,也是具有很好泛化性能的回归方法。但由于支持向量机算法实习复杂,效率低,严格限制了其应用,SMO算法的提出大大提高了支持向量机的学习效率。因此,借助SMO算法,便可以实现大样本集的非线性系统辨识和函数拟合。文中对回归问题的SMO算法作了详细介绍,并对其进行改进。然后研究了利用改进SMO算法的非线性系统辨识方法,给出了非线性系统的辨识的仿真结果,和一维二维函数的拟合仿真。并通过仿真,与原始算法进行了比较,显示了改进SMO算法的快速性。     

Design and development of a technology enhanced hybrid instruction based on MOLTA model: Its effectiveness in comparison to traditional instruction

Using the model for learning and teaching activities (MOLTA), a new technology enhanced hybrid instruction was designed, developed and implemented. The effectiveness of the hybrid instruction in regard to students’ achievement, knowledge retention, attitudes towards the subject, and course satisfaction was evaluated in comparison to traditional classroom instruction. Experimental study with pre-test, post-test control group design was carried out. The sample of the study consisted of 50 university students enrolled in “Computer Networks and Communication” course. The control and experimental groups composed of 24 and 26 students respectively, and the experiment lasted 14 weeks. The findings of the study indicated no significant difference between the hybrid course and the traditional course in students’ achievement, knowledge retention, satisfaction, and attitude.