title: Predicting regression test failures using genetic algorithm-selected dynamic performance analysis metrics

authors: Mayo, Michael

subjects: computer science

abstract: A novel framework for predicting regression test failures is proposed. The basic principle embodied in the framework is to use performance analysis tools to capture the runtime behaviour of a program as it executes each test in a regression suite. The performance information is then used to build a dynamically predictive model of test outcomes. Our framework is evaluated using a genetic algorithm for dynamic metric selection in combination with state-of-the-art machine learning classifiers. We show that if a program is modified and some tests subsequently fail, then it is possible to predict with considerable accuracy which of the remaining tests will also fail which can be used to help prioritise tests in time constrained testing environments.

text: Predicting regression test failures using genetic algorithm-selected dynamic performance analysis metrics A novel framework for predicting regression test failures is proposed. The basic principle embodied in the framework is to use performance analysis tools to capture the runtime behaviour of a program as it executes each test in a regression suite. The performance information is then used to build a dynamically predictive model of test outcomes. Our framework is evaluated using a genetic algorithm for dynamic metric selection in combination with state-of-the-art machine learning classifiers. We show that if a program is modified and some tests subsequently fail, then it is possible to predict with considerable accuracy which of the remaining tests will also fail which can be used to help prioritise tests in time constrained testing environments.

year: 2013

title: Hardware in the loop evaluation of a hybrid heating system for increased energy efficiency and management

authors: Schumm, Gregor

abstract: This study presents the tests of a hybrid heating prototype, designed for retrofitting thermal treatment plants like pasteurization, to use hot water and steam in controlled ratios. In the food industry, steam with a temperature above 140°C usually supplies the thermal production processes. The majority of processes require temperatures below 100°C and could be supplied more eficiently by cogeneration, heat recovery or heat pumps. These low temperature heat sources can only be combined with the rigid steam system if the demand structure is changed to a hybrid use of hot water below 100°C and steam. The hybrid heating system (H2S) increases the energy efficiency by integrating the highest possible amount of low temperature heat and responds to sudden changes in the supply structure, like demand response strategies on intermittent renewable energies and the changing availability of hot water and steam. The technical implementation is realised by a hydraulic interconnection of heat exchangers and valves. A smart algorithm controls the integration of hot water and steam into the thermal process. For reasons of food safety and product quality defined process temperatures have to be met. Prerequisite for functional verification on a laboratory scale is a simulation of the process heat demand and potential of hot water during the entire production cycle. The load profiles and relevant process parameters are passed in real time to a hardware-in-the loop (HIL) test-bed and returned to the simulation respectively. Two scenarios, hot water integration from heat pump and demand response management with a gas engine CHP and an electrical steam generator, were evaluated and the functionality of the H2S was proved. Up to 78 % of the final energy demand can be reduced by the H2S based implementation of a heat pump. The control response of the system, even with fluctuating hot water potential and temperature, met the requirements of the dairy industry.

text: Hardware in the loop evaluation of a hybrid heating system for increased energy efficiency and management This study presents the tests of a hybrid heating prototype, designed for retrofitting thermal treatment plants like pasteurization, to use hot water and steam in controlled ratios. In the food industry, steam with a temperature above 140°C usually supplies the thermal production processes. The majority of processes require temperatures below 100°C and could be supplied more eficiently by cogeneration, heat recovery or heat pumps. These low temperature heat sources can only be combined with the rigid steam system if the demand structure is changed to a hybrid use of hot water below 100°C and steam. The hybrid heating system (H2S) increases the energy efficiency by integrating the highest possible amount of low temperature heat and responds to sudden changes in the supply structure, like demand response strategies on intermittent renewable energies and the changing availability of hot water and steam. The technical implementation is realised by a hydraulic interconnection of heat exchangers and valves. A smart algorithm controls the integration of hot water and steam into the thermal process. For reasons of food safety and product quality defined process temperatures have to be met. Prerequisite for functional verification on a laboratory scale is a simulation of the process heat demand and potential of hot water during the entire production cycle. The load profiles and relevant process parameters are passed in real time to a hardware-in-the loop (HIL) test-bed and returned to the simulation respectively. Two scenarios, hot water integration from heat pump and demand response management with a gas engine CHP and an electrical steam generator, were evaluated and the functionality of the H2S was proved. Up to 78 % of the final energy demand can be reduced by the H2S based implementation of a heat pump. The control response of the system, even with fluctuating hot water potential and temperature, met the requirements of the dairy industry.

year: 2016

title: Monitoring first year Maori students enrolled in selected Faculty of Arts and Social Sciences courses: A report prepared for the Dean of the Faculty of Arts and Social Sciences

authors: Levy, Michelle Patricia

subjects: maori students

abstract: Monitoring first year Maori Students Enrolled in Selected Faculty of Arts andSocial Sciences Courses. The total number of Maori students targeted by this project was 182, representing 93% of the total number of Maori students enrolled in Semester B level one courses. The majority of students participating in this initiative were first year students, although a small number of students taking 100 level courses were second, third or graduate year students. 11 Student views on the monitoring and support initiative Students were provided with the opportunity to comment on the monitoring and support initiative. All students contacted (49) recommended that this intervention continue for future first year Maori students enrolled in FASS.

text: Monitoring first year Maori students enrolled in selected Faculty of Arts and Social Sciences courses: A report prepared for the Dean of the Faculty of Arts and Social Sciences Monitoring first year Maori Students Enrolled in Selected Faculty of Arts andSocial Sciences Courses. The total number of Maori students targeted by this project was 182, representing 93% of the total number of Maori students enrolled in Semester B level one courses. The majority of students participating in this initiative were first year students, although a small number of students taking 100 level courses were second, third or graduate year students. 11 Student views on the monitoring and support initiative Students were provided with the opportunity to comment on the monitoring and support initiative. All students contacted (49) recommended that this intervention continue for future first year Maori students enrolled in FASS.

year: 2003-03-01