The use of Bayesian networks to determine software inspection process efficiency

Adherence to a defined process or standards is necessary to achieve satisfactory software quality. However, in order to judge whether practices are effective at achieving the required integrity of a software product, a measurement-based approach to the correctness of the software development is required. A defined and measurable process is a requirement for producing safe software productively. In this study the contribution of quality assurance to the software development process, and in particular the contribution that software inspections make to produce satisfactory software products, is addressed. I have defined a new model of software inspection effectiveness, which uses a Bayesian Belief Network to combine both subjective and objective data to evaluate the probability of an effective software inspection. Its performance shows an improvement over the existing published models of inspection effectiveness. These previous models made questionable assumptions over the distribution of errors and were essentially static. They could not make use of experience both in terms of process improvement and the increased experience of the inspectors. A sensitivity analysis of my model showed that it is consistent with the attributes which were thought important by Michael Fagan in his research into the software inspection method. The performance of my model show that it is an improvement over published models and over a multiple logistic regression model, which was formed using the same calibration data. By applying my model of software inspection effectiveness before the inspection takes place, project managers will be able to make better use of inspection resource available. Applying the model using data collected during the inspection will help in estimation of residual errors in a product. Decisions can then be made if further investigations are required to identify errors. The modelling process has been used successfully in an industrial application

FABASOFT BEST PRACTICES AND TEST METRICS MODEL

Software companies have to face serious problems about how to measure the progress of test activities and quality of software products in order to estimate test completion criteria, and if the shipment milestone will be reached on time. Measurement is a key activity in testing life cycle and requires established, managed and well documented test process, defined software quality attributes, quantitative measures, and using of test management and bug tracking tools. Test metrics are a subset of software metrics (product metrics, process metrics) and enable the measurement and quality improvement of test process and/or software product. The goal of this paper is to briefly present Fabasoft best practices and lessons learned during functional and system testing of big complex software products, and to describe a simple test metrics model applied to the software test process with the purpose to better control software projects, measure and increase software quality

Software process quality models: a comparative evaluation

Numerous software processes are implemented by software organisations in the production and maintenance of software products. Varying levels of success are observed in their execution, as processes vary in content and quality. A number of quality models for software processes have been published, each of which is intended to encompass the totality of quality factors and issues relevant to a specific notion of process quality. These quality models may be used to develop a new process, measure the quality of existing processes, or guide improvement of existing processes. It is therefore desirable that mechanisms exist to select the model of highest intrinsic quality and greatest relevance. In this thesis, mechanisms are proposed for the comparative evaluation of software process quality models. Case studies are performed in which existing software process quality models are applied to existing software processes. Case study results are used in empirical evaluation of models to augment theoretical evaluation results. Specific recommendations are made for selection of models against typical selection criteria. Assessment is performed of the assessment procedures against defined success criteria. Theoretical evaluation procedures are developed to measure process quality models against defined quality criteria. Measurements are performed of conformance of models to the requirements set for an ideal process quality model, and the relevance of model content to defined stakeholders in software processes. Comparison is also made of the scope and size of models. Empirical evaluation procedures are developed to assess model performance in the context of application to real software processes. These procedures assess the extent to which the results of process measurement using process quality models are observed to differ, and hence the importance of selecting one model in preference to others. Measurement is also performed of the extent of difference in the software processes evaluated in the case studies

Criteria for the evaluation of business process simulation tools

This paper focuses on a process of simulation software packages selection in the context of business process change projects. The paper presents discrete event simulation, its relation to business process modelling and examples of its practical applications in business process change projects. Features of business process simulation tools are examined, the most important simulation features are identified and the criteria for their evaluation are defined. The guidelines that could help managers in the selection of business process simulation tools are proposed. The discussion addresses the limitations of the proposed guidelines. Finally, based on the conducted research and the evaluation criteria defined within the guidelines, some directions for the further improvement of business process simulation tools are given

Virtualising Process Assessments to Facilitate Continual Service Improvement in IT Service Management

The IT Service Management (ITSM) industry has defined processes as best practices in the widely-accepted IT Infrastructure Library (ITIL) framework. However, studies on the measurement of ITSM process improvement are scant. Our research addressed the dual problems of the lack of transparency and the need for efficiency in ITSM process assessment. Using the Design Science Research methodology, we developed a Software-mediated Process Assessment (SMPA) approach that enables assessment of ITSM processes. The SMPA approach includes process selection; an online survey to collect assessment data; measurement of process capability; and reporting of process improvement recommendations. We implemented a decision support system (DSS) to automate the SMPA approach and evaluated it at two IT service providers. The evaluations indicated that the SMPA approach supports decision-making on process improvements. The findings provided design knowledge of virtualisation in ITSM process assessment and how this may facilitate continual service improvement

Virtualising process assessments to facilitate continual service improvement in IT service management

The IT Service Management (ITSM) industry has defined processes as best practices in the widely accepted IT Infrastructure Library (ITIL) framework. However, studies on the measurement of ITSM process improvement are scant. Our research addressed the dual problems of the lack of transparency and the need for efficiency in ITSM process assessment. Using the Design Science Research methodology, we developed a Software-mediated Process Assessment (SMPA) approach that enables assessment of ITSM processes. The SMPA approach includes process selection; an online survey to collect assessment data; measurement of process capability; and reporting of process improvement recommendations. We implemented a decision support system (DSS) to automate the SMPA approach and evaluated it at two IT service providers. The evaluations indicated that the SMPA approach supports decision-making on process improvements. The findings provided design knowledge of virtualisation in ITSM process assessment and how this may facilitate continual service improvement

Fuzzy logic particle tracking velocimetry

Fuzzy logic has proven to be a simple and robust method for process control. Instead of requiring a complex model of the system, a user defined rule base is used to control the process. In this paper the principles of fuzzy logic control are applied to Particle Tracking Velocimetry (PTV). Two frames of digitally recorded, single exposure particle imagery are used as input. The fuzzy processor uses the local particle displacement information to determine the correct particle tracks. Fuzzy PTV is an improvement over traditional PTV techniques which typically require a sequence (greater than 2) of image frames for accurately tracking particles. The fuzzy processor executes in software on a PC without the use of specialized array or fuzzy logic processors. A pair of sample input images with roughly 300 particle images each, results in more than 200 velocity vectors in under 8 seconds of processing time

A software process improvement lifecycle framework for the medical device industry

This paper describes a software process improvement framework to ensure regulatory compliance for the software developed in medical devices. Software is becoming an increasingly important aspect of medical devices and medical device regulation. Medical devices can only be marketed if compliance and approval from the appropriate regulatory bodies of the Food and Drug Administration (FDA) [1] (US requirement), and the European Commission under its Medical Device Directives (MDD) [2] (CE marking requirement) is achieved. Integrated into the design process of medical devices, is the requirement of the production and maintenance of a device technical file, incorporating a design history file. Design history illustrates the well documented, defined and controlled processes and outputs, undertaken in the development of medical devices and for our particular consideration with this framework - the software components

The maturing of the quality improvement paradigm in the SEL

The Software Engineering Laboratory uses a paradigm for improving the software process and product, called the quality improvement paradigm. This paradigm has evolved over the past 18 years, along with our software development processes and product. Since 1976, when we first began the SEL, we have learned a great deal about improving the software process and product, making a great many mistakes along the way. Quality improvement paradigm, as it is currently defined, can be broken up into six steps: characterize the current project and its environment with respect to the appropriate models and metrics; set the quantifiable goals for successful project performance and improvement; choose the appropriate process model and supporting methods and tools for this project; execute the processes, construct the products, and collect, validate, and analyze the data to provide real-time feedback for corrective action; analyze the data to evaluate the current practices, determine problems, record findings, and make recommendations for future project improvements; and package the experience gained in the form of updated and refined models and other forms of structured knowledge gained from this and prior projects and save it in an experience base to be reused on future projects

Improving the effectiveness of FMEA analysis in automotive − a case study

Many industries, for example automotive, have well defined product development process definitions and risk evaluation methods. The FMEA (Failure Mode and Effects Analysis) is a first line risk analysis method in design, which has been implemented in development and production since decades. Although the first applications were focusing on mechanical and electrical design and functionalities, today, software components are implemented in many modern vehicle systems. However, standards or industry specific associations do not specify any “best practice” how to design the interactions of multiple entities in one model. This case study focuses on modelling interconnections and on the improvement of the FMEA modelling process in the automotive. Selecting and grouping software components for the analysis is discussed, but software architect design patterns are excluded from the study