An SQA e-Learning System for Agile Software Development

The intensity Modulated Radiation therapy (IMRT) is an advanced form of three-dimensional conformal radiation therapy (3-D CRT) that not only uses 3-D imaging and treatment delivery, but allows for varying radiation beam intensities to produce much more conformal dose distributions than those possible with conventional 3-D CRT. The complex nature of IMRT planning and delivery impose new requirements for quality assurance (QA) process. A comprehensive QA for IMRT must address the issues involving the verification of pre-treatment, patient-specific, delivery and post-treatment. A complete set of tools, including detectors and phantoms, and techniques are necessary to accomplish the new QA tasks. Some of the detectors used for IMRT QA include films, TLDs, EPIDs, ion chambers and gel dosimeters. Each of them has distinct characteristics and limitations. Several phantoms are also available to accomplish the verification measurements, including cylindrical or a stack of solid water. Tools also have been developed for the dosimetric analysis of the measurements and calculations. Some of these tools include isodose overlay, dose difference histograms, distance-to-agreement and gamma evaluation. This presentation will review the QA tools and techniques that are currently in use for all aspects of IMRT process. Educational Objectives: 1. To identify the QA tasks involving IMRT 2. To identify the requirements for the QA tools 3. To describe the QA tools for all aspects of IMRT process 4. To explain the limitations of the QA tools 5. To compare the IMRT QA tools and techniques

Open Source Software (OSS) is software products available to the public, with its source code to study, change, and improves its design. Open Source Software Development (OSSD) is the process by which open source software is developed within the confines of software engineering life-cycle methods. However when open source used for commercial purpose, then an open source license is required. Open source software is very often developed in a public and collaborative manner. The quality assurance principle under open source software development is an approach to improve software product quality against traditional methods and techniques. Despite the fact that the open source developments have seen remarkable successful in recent years, there are a number of product quality issues and challenges facing the open source development model. Many industries and business sectors are following or using OSSD, since they realize the benefits, but they do have some reservations concerning quality assurance in the form of program code quality, maintenance of the code and its quality, over the life-cycle of the product and third party usage. This paper reviews the literature of the process of the latest quality assurance, under open source software development methods and techniques. The result from this review is to show the process of quality assurance of open source software and that how it can affect the overall quality assurance principal.

Over the past decade or so, improvements and changes in descriptive models of systems have been occurring. This has mainly come about in the shift from a document-centered approach to an approach using a dedicated language known as the Systems Modeling Language (SysML). SysML has allowed Systems Engineers (SEs) to consolidate information about a system and even automate some tasks leaving the SEs to concentrate on the actual engineering and decision-making. Many of our quality assurance (QA) tasks either overlap or interface with systems engineering tasks, thus, it is important for quality engineers to understand and contribute to these system engineering models. We will explore some of the ways in which QA processes and products may be model within the framework of SysML. First let us look at how quality can be assured by using requirement elements in a systems model.

The main objective of the paper is to create context sensitive decision support services within flexible Quality Assurance (QA) of software development projects and their resulting products. The new QA process is supported by an Internet solution composed of several knowledge, context sensitive services based on open standards that is able to detect changes in the scope and requirements of an application (or changes in its development process) and provide the adequate set of assessments as a basis for an accurate measurement of the quality of the process and product at any time and allow for effective decision making within QA. The Internet Services monitor the different stages of the software development process, interoperating with the existing applications and systems to provide quantitative information about the quality of each phase (i.e. project management, requirements gathering, functional and technical design, development and testing), the project as a whole and the resulting product. They also monitor context under which the SW is developed and decisions on QA have to be made. Data obtained in real-time by the monitoring services are used in an indistinctive way by software engineers, designers, developers, testers and managers alike for different collaborative decision making. The paper is one of the first attempts to apply context sensitivity to support decision making in QA for SW development. The approach is assessed in 2 different business cases in order to validate the results under different conditions. The first business case belongs to a large software company developing large Internet projects based on Rational Unified Process methodology. The second business case belongs to a SME developing complex projects based on agile methodologies.

This work applied statistical process control to establish the control limits of the % gamma pass of patient-specific intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT) quality assurance (QA), and to evaluate the efficiency of the QA process by using the process capability index (Cpml). A total of 278 IMRT QA plans in nasopharyngeal carcinoma were measured with MapCHECK, while 159 VMAT QA plans were undertaken with ArcCHECK. Six megavolts with nine fields were used for the IMRT plan and 2.5 arcs were used to generate the VMAT plans. The gamma (3%/3 mm) criteria were used to evaluate the QA plans. The % gamma passes were plotted on a control chart. The first 50 data points were employed to calculate the control limits. The Cpml was calculated to evaluate the capability of the IMRT/VMAT QA process. The results showed higher systematic errors in IMRT QA than VMAT QA due to the more complicated setup used in IMRT QA. The variation of random errors was also larger in IMRT QA than VMAT QA because the VMAT plan has more continuity of dose distribution. The average % gamma pass was 93.7% ± 3.7% for IMRT and 96.7% ± 2.2% for VMAT. The Cpml value of IMRT QA was 1.60 and VMAT QA was 1.99, which implied that the VMAT QA process was more accurate than the IMRT QA process. Our lower control limit for % gamma pass of IMRT is 85.0%, while the limit for VMAT is 90%. Both the IMRT and VMAT QA processes are good quality because Cpml values are higher than 1.0.

The complexity of generating radiotherapy treatments demands a rigorous quality assurance (QA) process to ensure patient safety and to avoid clinically significant errors. Machine learning classifiers have been explored to augment the scope and efficiency of the traditional radiotherapy treatment planning QA process. However, one important gap in relying on classifiers for QA of radiotherapy treatment plans is the lack of understanding behind a specific classifier prediction. We develop explanation methods to understand the decisions of two automated QA classifiers: (1) a region of interest (ROI) segmentation/labeling classifier, and (2) a treatment plan acceptance classifier. For each classifier, a local interpretable model-agnostic explanation (LIME) framework and a novel adaption of team-based Shapley values framework are constructed. We test these methods in datasets for two radiotherapy treatment sites (prostate and breast), and demonstrate the importance of evaluating QA classifiers using interpretable machine learning approaches. We additionally develop a notion of explanation consistency to assess classifier performance. Our explanation method allows for easy visualization and human expert assessment of classifier decisions in radiotherapy QA. Notably, we find that our team-based Shapley approach is more consistent than LIME. The ability to explain and validate automated decision-making is critical in medical treatments. This analysis allows us to conclude that both QA classifiers are moderately trustworthy and can be used to confirm expert decisions, though the current QA classifiers should not be viewed as a replacement for the human QA process.

In the past decade, there have been a number of notable changes in industrial software engineering, including the movement towards agility. The Agile Manifesto characterizes the term “agile”, and lists a set of principles that form a basis for agile methodologies [1], such as Extreme Programming (XP), OpenUP, and Scrum. There is creation, communication, and consumption of knowledge during (agile) software development [2]. For the success of an agile project, it is crucial that such knowledge be managed effectively. In doing so, an appropriate selection and use of certain tools and technologies can be helpful. In the past few years, there has been a proliferation of Social Web Applications, such as Wiki [3]. Indeed, a number of noteworthy uses of Wiki in software engineering have been reported [4]. However, these studies are largely independent of any software development methodology, and are centered mostly on collaboration. The primary reasons for selecting Wiki for agile software development include the following: (1) the deployment of agile methodologies, especially XP and Scrum, with teams that are increasingly geographically-dispersed, (2) the involvement in sustainable software development by organizations with basic infrastructure and modest budgets for resources, and (3) the need of inexpensive, mature, and widely-available tools for supporting iterative development, by almost anybody, at anytime, anywhere, using almost any device. The purpose of this research is to provide a framework for integrating Wiki for the purpose of facilitating the dynamics of knowledge during agile software development.

Agile practices have recently gained popularity among large number of companies as a mechanism for reducing cost and increasing ability to handle change in dynamic market conditions. Based on the principles of the Agile manifesto [1, 2], researchers and practitioners have proposed several software development approaches such as Extreme Programming, Scrum and Feature-Driven Development. These and other agile approaches have had significant impact on industrial software development practices. However, there is also a significant concern and perplexity about the role and importance of the issues related to a system’s software architecture, which is considered one of the most important initial design artefacts. It is argued that software architecture is an effective tool to cut development cost and time and to increase the quality of a system. Many practitioners of Agile approaches appear to view software architecture in the context of the plan-driven development paradigm [3]. For them, upfront design and evaluation of software architecture requires too much work, which may have very little value to the customers of a system. Hence, they perceive architectural work as part of high ceremony processes, which usually require large amount of documentation. We maintain that these two seemingly opposing views to software engineering can be integrated but it requires that experts from both fields work together to overcome evident challenges in bridging these two paradigms together. Indeed, software architecture researchers and practitioners appear to believe that sound architectural practices cannot be followed using Agile approaches. However, these two extreme views of Agile and architecture appear to neglect that many agile experts emphasises the importance of paying attention to good design and architecture early in the development process [4, 5]. Recently, there is growing recognition of the importance of paying more attention to architectural aspects in agile approaches [3, 6, 7]. We argue that there is a vital need for devising a research agenda for identifying and dealing with architecture-centric challenges in agile software development. Such research agenda should make it possible to guide the future research on integrating architecture-centric methods in agile approaches and give advice to the software industry on dealing with architecture related challenges. Some of the questions to stimulate discussion in the workshop are: What is the role of software architecture in Agile software development? What are the key architecture-centric challenges and potential solutions in Agile software development projects? What is the strength of the evidence that attention to architectural issues can be counterproductive in Agile development or vice versa? What are the prerequisites for integrating Architecture-Centric methods in agile development and potential implications of such integration?

BackgroundThe purpose of this study is to provide a framework for the development of a quality assurance (QA) program for use in medical 3D printing applications. An interdisciplinary QA team was built with expertise from all aspects of 3D printing. A systematic QA approach was established to assess the accuracy and precision of each step during the 3D printing process, including: image data acquisition, segmentation and processing, and 3D printing and cleaning. Validation of printed models was performed by qualitative inspection and quantitative measurement. The latter was achieved by scanning the printed model with a high resolution CT scanner to obtain images of the printed model, which were registered to the original patient images and the distance between them was calculated on a point-by-point basis.ResultsA phantom-based QA process, with two QA phantoms, was also developed. The phantoms went through the same 3D printing process as that of the patient models to generate printed QA models. Physical measurement, fit tests, and image based measurements were performed to compare the printed 3D model to the original QA phantom, with its known size and shape, providing an end-to-end assessment of errors involved in the complete 3D printing process. Measured differences between the printed model and the original QA phantom ranged from -0.32 mm to 0.13 mm for the line pair pattern. For a radial-ulna patient model, the mean distance between the original data set and the scanned printed model was -0.12 mm (ranging from -0.57 to 0.34 mm), with a standard deviation of 0.17 mm.ConclusionsA comprehensive QA process from image acquisition to completed model has been developed. Such a program is essential to ensure the required accuracy of 3D printed models for medical applications.

Software engineers increasingly emphasize agility and flexibility in their designs and development approaches. They increasingly use distributed development teams, rely on component assembly and deployment rather than green field code writing, rapidly evolve the system through incremental development and frequent updating, and use flexible product designs supporting extensive end-user customization. While agility and flexibility have many benefits, they also create an enormous number of potential system configurations built from rapidly changing component implementations. Since today's quality assurance (QA) techniques do not scale to handle highly configurable systems, we are developing and validating novel software QA processes and tools that leverage the extensive computing resources of user and developer communities in a distributed, continuous manner to improve software quality significantly. This paper provides several contributions to the study of distributed, continuous QA (DCQA). First, it shows the structure and functionality of Skoll, which is an environment that defines a generic around-the-world, around-the-clock QA process and several sophisticated tools that support this process. Second, it describes several novel QA processes built using the Skoll environment. Third, it presents two studies using Skoll: one involving user testing of the Mozilla browser and another involving continuous build, integration, and testing of the ACE+TAO communication software package. The results of our studies suggest that the Skoll environment can manage and control distributed continuous QA processes more effectively than conventional QA processes. For example, our DCQA processes rapidly identified problems that had taken the ACE+TAO developers much longer to find and several of which they had not found. Moreover, the automatic analysis of QA results provided developers information that enabled them to quickly find the root causes of problems

Purpose: For shallow tumors, modulated electron radiotherapy (MERT) promises a reduction of dose to distal organs at risk. At our institution a framework was developed in order to create treatment plans for MERT employing both forward and inverse optimization. In this work, an efficient quality assurance (QA) process is established. Methods: Treatment plans for three different tumor sites were created using an inverse optimization. These plans consist of 6–12 segments and energies between 6 and 18 MeV. An already established QA process for photon IMRT plans is now extended to additionally handle MERT plans. First, the dose distributions are calculated in a homogenous water phantom. For this task a dedicated Monte Carlo (MC) framework for MERT is used. Second, the segments are applied on a stand-alone amorphous silicon electronic portal imaging device (EPID) using a source-to-surface distance of 70 cm. This device was calibrated for electron beams in a previous work. An in-house developed analysis software, is then utilized for comparisons and evaluation of the measured and calculated dose distributions. Results: For all three plans the calculated dose distributions agree well with the measured ones. Using a 2D gamma comparison (2% of dose max/2 mm and 10% dose threshold) passingmore » rates >98% are achieved.The dose calculation for each plan on the water phantom, using voxels of 0.2×0.2×0.2 cm{sup 3}, takes at maximum 30 min on a single core Pentium 2.66 GHz system with 6 GB RAM, to reach a statistical uncertainty of 2% (1 std. dev.). Conclusion: An already established QA procedure for IMRT photon plans was applied for MERT. The dedicated MC framework and the use of EPID measurements allow an efficient QA procedure in a clinical environment. This work was supported by Varian Medical Systems.« less

Purpose: Interests in electronic portal imaging devices (EPIDs) for radiation dosimetry increase over the past decade, particularly with recent technique advances in amorphous‐silicon EPID. For a clinical quality assurance (QA) program, EPIDs may provide a useful tool with benefits of reduced cost and added convenience, e.g., shortening setup time. This study is to investigate the clinical application of EPID in routine machine and IMRT QA and develop an EPID‐based QA system. Materials and Methods: EPID images were acquired using Varian aS1000 EPID (integrated mode; 6 MV beam; 600 MU/min dose rate). Signal intensity of EPID images were converted to dose maps using a calibrated linear signal‐dose relationship. An integrated EPID‐based QA system was designed, which include functions for machine QA and IMRT QA. For routine machine QA, recommendations by TG‐40 and TG‐45 reports were used. Specific EPID‐based QA procedures and image analysis algorithms were designed and developed for basic QA tasks, e.g., beam flatness/symmetry test and Winston‐Lutz isocenter test. For IMRT QA, a phantom‐less method was proposed, which used fluence maps reconstructed from EPID‐measured fluence as input to treatment plan system for dose calculation and comparison. Results: EPID‐measured machine QA results were comparable to those measured monthly using films in our institute. For example, EPID‐measured parameters were: flatness = 0.9–1.45%; symmetry = 0.48–1.31%; penumbra = 3.2–4 mm at SSD = 150 cm. Star‐shot images were well reconstructed for isocenter check from EPID images acquired at different gantry or collimator angles. The EPID‐based IMRT QA method was able to verify the treatment plan and capture the reasonable plan‐versus‐QA dose difference. Conclusion: The results show that EPID may be properly used as a tool for clinical QA tasks and the developed EPID‐based QA system may be used for machine and IMRT QA. (Research sponsored by Oncology Data Systems, Inc, Oklahoma City, OK)

Despite of many criticisms, agile software development (Beck et al., Manifesto for Agile Software Development, http://agilemanifesto.org, [1]) philosophy has been proved to be quite successful to increase the project success rate up to a significant extent. The primary reasons behind the criticism of agile are the strong violation of the traditional disciplined software engineering theories, principles and practices. The goal of this research paper is to establish the fact that agility may also be achieved by following traditional process models especially with BRIDGE (Mandal, 2009 IEEE International Advance Computing Conference (IACC 2009) Patiala, India, [2]) process model. Hence, the aim of this paper is to integrate the agile and traditional disciplined software development process models and establish the compatibility between both the approaches. At the beginning, we have explored the objectives and principles of agile software development. Next, we briefly discussed the BRIDGE process model and further justified that--following BRIDGE process model, the philosophy of agile may also be achieved and conclude that BRIDGE model has both the capability of traditional software development process model as well as of the agile process.

Effort estimation is very important for any software development organisation. A lot of work is present for effort estimation in traditional software development but, effort estimation in agile software development (ASD) poses a great research challenge as not much of work is done in this regard. This work proposes a fuzzy approach for effort estimation in ASD environment by identifying first the cost drivers affecting the effort of agile projects and then calculating the effort using fuzzified story point approach. These cost drivers are collected through meetings and by taking a web survey from the companies in Delhi-NCR which practise ASD. Statistical tests are also performed in order to show the dependency of effort on these cost drivers. Here, fuzzy interval type-2 is used which is compared with fuzzy type-1. It is found that, the effort calculated using fuzzy interval type-2 is better than fuzzy type-1.

agile information systems, flexible information systems development, distributed information systems development, global software development, software development, special issue