435,281 research outputs found
Fully Employing Software Inspections Data
Software inspections provide a proven approach to quality assurance for software products of all kinds, including requirements, design, code, test plans, among others. Common to all inspections is the aim of finding and fixing defects as early as possible, and thereby providing cost savings by minimizing the amount of rework necessary later in the lifecycle. Measurement data, such as the number and type of found defects and the effort spent by the inspection team, provide not only direct feedback about the software product to the project team but are also valuable for process improvement activities. In this paper, we discuss NASA's use of software inspections and the rich set of data that has resulted. In particular, we present results from analysis of inspection data that illustrate the benefits of fully utilizing that data for process improvement at several levels. Examining such data across multiple inspections or projects allows team members to monitor and trigger cross project improvements. Such improvements may focus on the software development processes of the whole organization as well as improvements to the applied inspection process itself
Software quality attribute measurement and analysis based on class diagram metrics
Software quality measurement lies at the heart of the quality engineering process. Quality measurement for object-oriented artifacts has become the key for ensuring high quality software. Both researchers and practitioners are interested in measuring software product quality for improvement. It has recently become more important to consider the quality of products at the early phases, especially at the design level to ensure that the coding and testing would be conducted more quickly and accurately. The research work on measuring quality at the design level progressed in a number of steps. The first step was to discover the correct set of metrics to measure design elements at the design level. Chidamber and Kemerer (C&K) formulated the first suite of OO metrics. Other researchers extended on this suite and provided additional metrics. The next step was to collect these metrics by using software tools. A number of tools were developed to measure the different suites of metrics; some represent their measurements in the form of ordinary numbers, others represent them in 3D visual form. In recent years, researchers developed software quality models which went a bit further by computing quality attributes from collected design metrics. In this research we extended on the software quality modelers’ work by adding a quality attribute prioritization scheme and a design metric analysis layer. Our work is all focused on the class diagram, the most fundamental constituent in any object oriented design. Using earlier researchers’ work, we extract a class diagram’s metrics and compute its quality attributes. We then analyze the results and inform the user. We present our figures and observations in the form of an analysis report. Our target user could be a project manager or a software quality engineer or a developer who needs to improve the class diagram’s quality. We closely examine the design metrics that affect quality attributes. We pinpoint the weaknesses in the class diagram, based on these metrics, inform the user about the problems that emerged from these classes, and advice him/her as to how he/she can go about improving the overall design quality. We consider the six basic quality attributes: “Reusability”, “Functionality”, “Understandability”, “Flexibility”, “Extendibility”, and “Effectiveness” of the whole class diagram. We allow the user to set priorities on these quality attributes in a sequential manner based on his/her requirements. Using a geometric series, we calculate a weighted average value for the arranged list of quality attributes. This weighted average value indicates the overall quality of the product, the class diagram. Our experimental work gave us much insight into the meanings and dependencies between design metrics and quality attributes. This helped us refine our analysis technique and give more concrete observations to the user
SOFTWARE TESTABILITY MEASURE FOR SAE ARCHITECTURE ANALYSIS AND DESIGN LANGUAGE (AADL)SOFTWARE TESTABILITY MEASURE FOR SAE ARCHITECTURE ANALYSIS AND DESIGN LANGUAGE (AADL)
Testability is an important quality attribute of software, especially for critical systems such as avionics, medical, and automotive. Improvement in the early testability of software architecture, the first artifact of the software system, will help reduce issues and costs later in the development process. AADL, an architecture analysis description language suitable for critical embedded, real-time systems, can be used for design documentation, analysis and code generation. Because the capability of AADL can be extended, it is possible to add new analyses to its core language. Tools such as the Open Source AADL Tool Environment (OSATE) provide plugins for processing AADL models. Although adding new plugins in OSATE extends AADL, there currently exists no AADL extension for testability measurement. The purpose of this thesis is to propose such a method to measure the testability of AADL models as well as to develop a testability plugin in OSATE. Much research has been conducted on testability of hardware, software and embedded systems, resulting in several approaches for measuring this quality attribute. Among them, the approach measuring testability as a product of controllability and observability using information transfer graph (ITG) is the most applicable for measuring the testability of AADL models. This thesis proposes a method applying this approach to AADL models. A complete testability measure plugin for OSATE was developed based on this approach and detailed examples are given in this thesis to demonstrate its applicability
Quality modelling and metrics of Web-based information systems
In recent years, the World Wide Web has become a major platform for software
applications. Web-based information systems have been involved in many areas of
our everyday life, such as education, entertainment, business, manufacturing,
communication, etc. As web-based systems are usually distributed, multimedia,
interactive and cooperative, and their production processes usually follow ad-hoc
approaches, the quality of web-based systems has become a major concern.
Existing quality models and metrics do not fully satisfy the needs of quality
management of Web-based systems. This study has applied and adapted software
quality engineering methods and principles to address the following issues, a quality
modeling method for derivation of quality models of Web-based information systems;
and the development, implementation and validation of quality metrics of key quality
attributes of Web-based information systems, which include navigability and
timeliness.
The quality modeling method proposed in this study has the following strengths. It is
more objective and rigorous than existing approaches. The quality analysis can be
conducted in the early stage of system life cycle on the design. It is easy to use and
can provide insight into the improvement of the design of systems. Results of case
studies demonstrated that the quality modeling method is applicable and practical.
Practitioners can use the modeling method to develop their own quality models.
This study is amongst the first comprehensive attempts to develop quality
measurement for Web-based information systems. First, it identified the relationship
between website structural complexity and navigability. Quality metrics of
navigability were defined, investigated and implemented. Empirical studies were
conducted to evaluate the metrics. Second, this study investigated website timeliness
and attempted to find direct and indirect measures for the quality attribute. Empirical
studies for validating such metrics were also conducted.
This study also suggests four areas of future research that may be fruitful
An investigation into telecommunications billing system testing processes
Testing is an important part of the software development process, since it ultimately determines the quality of the product or service that the end user is provided. As error correction costs increase exponentially with time, it is important to resolve software defects as early as possible. The same applies to telecommunications billing software, where the level of competitiveness demands that the testing process be both accurate and efficient. The investigation undertaken aimed to evaluate and improve the testing process of a company that develops telecommunications billing software, Nokia Siemens Networks (NSN). The methodology used to perform the study involved the use of the Goal Question Metric (GQM) approach, which has been used extensively for process measurement and improvement. A research model was developed which derived process goals from the key research questions, ensuring that the research questions could be answered from the goal results. Four goals were determined using this method. These goals were to improve defect detection accuracy, defect correction accuracy, defect detection efficiency and defect correction efficiency. This led to 14 questions and 95 metrics in total. Defect detection accuracy was found to be insufficient, defect correction accuracy was determined to be satisfactory, defect detection efficiency was a key goal, and it was found to be unsatisfactory, while defect correction efficiency was acceptable, however there were many cases where error resolution was slow. Several specific proposals for improvement are suggested, as well as general process improvement suggestions. The process can be improved overall by using the agile Scrum approach. Scrum's cross-functional teams coupled with development testing through Test-driven Development will ensure that detection accuracy and efficiency are improved. The study found that because the process is more traditional than agile and separates testing and development, it is not well suited to the size of the projects and their timelines. In order to meet the needs of the industry and release quality services competitively, a more agile approach needs to be taken. The research conducted provides a contribution to a field where research is scarce, and provides evidence of the insufficiency of traditional development processes in small telecommunications projects, while motivating the use of agile methodologies to meet organisational goals
Driving continuous improvement
The quality of improvement depends on the quality of leading and lagging performance indicators. For this reason, several tools, such as process mapping, cause and effect analysis and FMEA, need to be used in an integrated way with performance measurement models, such as balanced scorecard, integrated performance measurement system, performance prism and so on. However, in our experience, this alone is not quite enough due to the amount of effort required to monitor performance indicators at operational levels. The authors find that IT support is key to the successful implementation of performance measurement-driven continuous improvement schemes
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