Minimizing total completion time on batch processing machines

We study the problem of minimizing total completion time on single and parallel batch processing machines. A batch processing machine is one which can process up to B jobs simultaneously. The processing time of a batch is equal to the largest processing time among all jobs in the batch. This problem is motivated by burn-in operations in the final testing stage of semiconductor manufacturing and is expected to occur in other production environments. We provide an exact solution procedure for the single-machine problem and heuristic algorithms for both single and parallel machine problems. While the exact algorithms have limited applicability due to high computational requirements, extensive experiments show that the heuristics are capable of consistently obtaining near-optimal solutions in very reasonable CPU times.

Checking Completeness of Tests for Finite State Machines

In testing from a Finite State Machine (FSM), the generation of test suites which guarantee full fault detection, known as complete test suites, has been a long-standing research topic. In this paper, we present conditions that are sufficient for a test suite to be complete. We demonstrate that the existing conditions are special cases of the proposed ones. An algorithm that checks whether a given test suite is complete is given. The experimental results show that the algorithm can be used for relatively large FSMs and test suites.

Towards Centrifugal Compressor Stages Virtual Testing

Flow features inside centrifugal compressor stages are very complicated to simulate with numerical tools due to the highly complex geometry and varying gas conditions all across the machine. For this reason, a big effort is currently being made to increase the fidelity of the numerical models during the design and validation phases. Computational Fluid Dynamics (CFD) plays an increasing role in the assessment of the performance prediction of centrifugal compressor stages. Historically, CFD was considered reliable for performance prediction on a qualitatively level, whereas tests were necessary to predict compressors performance on a quantitatively basis. In fact "standard" CFD with only the flow-path and blades included into the computational domain is known to be weak in capturing efficiency level and operating range accurately due to the under-estimation of losses and the lack of secondary flows modeling. This research project aims to fill the gap in accuracy between "standard" CFD and tests data by including a high fidelity reproduction of the gas domain and the use of advanced numerical models and tools introduced in the author's OEM in-house CFD code. In other words, this thesis describes a methodology by which virtual tests can be conducted on single stages and multistage centrifugal compressors in a similar fashion to a typical rig test that guarantee end users to operate machines with a confidence level not achievable before. Furthermore, the new "high fidelity" approach allowed understanding flow phenomena not fully captured before, increasing aerodynamicists capability and confidence in designing high efficiency and high reliable centrifugal compressor stages.

Testing a Cloud Provider Network for Hybrid P2P and Cloud Streaming Architectures

The number of online real-time streaming services deployed over network topologies like P2P or centralized ones has remarkably increased in the recent years. This has revealed the lack of networks that are well prepared to respond to this kind of traffic. A hybrid distribution network can be an efficient solution for real-time streaming services. This paper contains the experimental results of streaming distribution in a hybrid architecture that consist of mixed connections among P2P and Cloud nodes that can interoperate together. We have chosen to represent the P2P nodes as Planet Lab machines over the world and the cloud nodes using a Cloud provider's network. First we present an experimental validation of the Cloud infrastructure's ability to distribute streaming sessions with respect to some key streaming QoS parameters: jitter, throughput and packet losses. Next we show the results obtained from different test scenarios, when a hybrid distribution network is used. The scenarios measure the improvement of the multimedia QoS parameters, when nodes in the streaming distribution network (located in different continents) are gradually moved into the Cloud provider infrastructure. The overall conclusion is that the QoS of a streaming service can be efficiently improved, unlike in traditional P2P systems and CDN, by deploying a hybrid streaming architecture. This enhancement can be obtained by strategic placing of certain distribution network nodes into the Cloud provider infrastructure, taking advantage of the reduced packet loss and low latency that exists among its datacenters.

Application of user-centered design in the development of an atomated/assisted testing system for self-service devices

Automated Teller Machines (ATMs) are sensitive self-service systems that require important investments in security and testing. ATM certifications are testing processes for machines that integrate software components from different vendors and are performed before their deployment for public use. This project was originated from the need of optimization of the certification process in an ATM manufacturing company. The process identifies compatibility problems between software components through testing. It is composed by a huge number of manual user tasks that makes the process very expensive and error-prone. Moreover, it is not possible to fully automate the process as it requires human intervention for manipulating ATM peripherals. This project presented important challenges for the development team. First, this is a critical process, as all the ATM operations rely on the software under test. Second, the context of use of ATMs applications is vastly different from ordinary software. Third, ATMs’ useful lifetime is beyond 15 years and both new and old models need to be supported. Fourth, the know-how for efficient testing depends on each specialist and it is not explicitly documented. Fifth, the huge number of tests and their importance implies the need for user efficiency and accuracy. All these factors led us conclude that besides the technical challenges, the usability of the intended software solution was critical for the project success. This business context is the motivation of this Master Thesis project. Our proposal focused in the development process applied. By combining user-centered design (UCD) with agile development we ensured both the high priority of usability and the early mitigation of software development risks caused by all the technology constraints. We performed 23 development iterations and finally we were able to provide a working solution on time according to users’ expectations. The evaluation of the project was carried out through usability tests, where 4 real users participated in different tests in the real context of use. The results were positive, according to different metrics: error rate, efficiency, effectiveness, and user satisfaction. We discuss the problems found, the benefits and the lessons learned in the process. Finally, we measured the expected project benefits by comparing the effort required by the current and the new process (once the new software tool is adopted). The savings corresponded to 40% less effort (man-hours) per certification. Future work includes additional evaluation of product usability in a real scenario (with customers) and the measuring of benefits in terms of quality improvement.

Effects of GeneXpert MTB/RIF Testing and GxAlert eHealth Platforms on MDR-TB Diagnosis and Linkage to Care in Sofala Province, Mozambique

Thesis (Master's)--University of Washington, 2016-06

Software Testing and Documenting Automation

This article describes some approaches to problem of testing and documenting automation in information systems with graphical user interface. Combination of data mining methods and theory of finite state machines is used for testing automation. Automated creation of software documentation is based on using metadata in documented system. Metadata is built on graph model. Described approaches improve performance and quality of testing and documenting processes.

Algorithms for scheduling parallel batch processing machines with non-identical job ready times

This research is motivated by a practical application observed at a printed circuit board (PCB) manufacturing facility. After assembly, the PCBs (or jobs) are tested in environmental stress screening (ESS) chambers (or batch processing machines) to detect early failures. Several PCBs can be simultaneously tested as long as the total size of all the PCBs in the batch does not violate the chamber capacity. PCBs from different production lines arrive dynamically to a queue in front of a set of identical ESS chambers, where they are grouped into batches for testing. Each line delivers PCBs that vary in size and require different testing (or processing) times. Once a batch is formed, its processing time is the longest processing time among the PCBs in the batch, and its ready time is given by the PCB arriving last to the batch. ESS chambers are expensive and a bottleneck. Consequently, its makespan has to be minimized. ^ A mixed-integer formulation is proposed for the problem under study and compared to a formulation recently published. The proposed formulation is better in terms of the number of decision variables, linear constraints and run time. A procedure to compute the lower bound is proposed. For sparse problems (i.e. when job ready times are dispersed widely), the lower bounds are close to optimum. ^ The problem under study is NP-hard. Consequently, five heuristics, two metaheuristics (i.e. simulated annealing (SA) and greedy randomized adaptive search procedure (GRASP)), and a decomposition approach (i.e. column generation) are proposed—especially to solve problem instances which require prohibitively long run times when a commercial solver is used. Extensive experimental study was conducted to evaluate the different solution approaches based on the solution quality and run time. ^ The decomposition approach improved the lower bounds (or linear relaxation solution) of the mixed-integer formulation. At least one of the proposed heuristic outperforms the Modified Delay heuristic from the literature. For sparse problems, almost all the heuristics report a solution close to optimum. GRASP outperforms SA at a higher computational cost. The proposed approaches are viable to implement as the run time is very short. ^

"Stress" testing for women

General note: Title and date provided by Bettye Lane.

An effective energy testing framework for cloud workflow activities

Cloud computing as the latest computing paradigm has shown its promising future in business workflow systems facing massive concurrent user requests and complicated computing tasks. With the fast growth of cloud data centers, energy management especially energy monitoring and saving in cloud workflow systems has been attracting increasing attention. It is obvious that the energy for running a cloud workflow instance is mainly dependent on the energy for executing its workflow activities. However, existing energy management strategies mainly monitor the virtual machines instead of the workflow activities running on them, and hence it is difficult to directly monitor and optimize the energy consumption of cloud workflows. To address such an issue, in this paper, we propose an effective energy testing framework for cloud workflow activities. This framework can help to accurately test and analyze the baseline energy of physical and virtual machines in the cloud environment, and then obtain the energy consumption data of cloud workflow activities. Based on these data, we can further produce the energy consumption model and apply energy prediction strategies. Our experiments are conducted in an OpenStack based cloud computing environment. The effectiveness of our framework has been successfully verified through a detailed case study and a set of energy modelling and prediction experiments based on representative time-series models.