Intelligent software quality model: The theoretical framework

Globally, software quality issues has increasingly been seen as a common strategic response for achieving competitiveness in business.It has been seen very important as the usage of software become very demanding.Software quality includes quality control tests, quality assurance and quality management.Currently, software quality models available were built based on static measurements of attributes and measures.Previous study has indicated that to ensure the quality of software meets the future requirements and needs, the new dynamic and intelligent software quality model has to be developed.This paper discusses the development of intelligent software quality model based on behavioral and human perspectives approach which enhances from Pragmatic Quality Factor (PQF) model as a benchmark of the quality assessment

A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment

Software quality is an important research area and has gain considerable attention from software engineering community in identification of priority quality attributes in software development process. This thesis describes original research in the field of software quality model by presenting a Feature Ranking Algorithm (FRA) for Pragmatic Quality Factor (PQF) model. The proposed algorithm is able to improve the weaknesses in PQF model in updating and learning the important attributes for software quality assessment. The existing assessment techniques lack of the capability to rank the quality attributes and data learning which can enhance the quality assessment process. The aim of the study is to identify and propose the application of Artificial Intelligence (AI) technique for improving quality assessment technique in PQF model. Therefore, FRA using FRT was constructed and the performance of the FRA was evaluated. The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. The result shows that the performance of FRA correlates strongly to PQF model with 98% correlation compared to the Kolmogorov-Smirnov Correlation Based Filter (KSCBF) algorithm with 83% correlation. Statistical significance test was also performed with score of 0.052 compared to the KSCBF algorithm with score of 0.048. The result shows that the FRA was more significant than KSCBF algorithm. The main contribution of this research is on the implementation of FRT with proposed Most Priority of Features (MPF) calculation in FRA for attributes assessment. Overall, the findings and contributions can be regarded as a novel effort in software quality for attributes selection

Software Ageing Measurement Model (SAMM): An Instrument Development

The rapid expansion in software development forced the owners and developers of a software to develop a good quality software and relevant for use in a long period of time without affecting the operation and high maintenance cost. There should be a standard measurement or indicator to monitor relevance level of the software from internal and external views of the product. Software ageing measurement is an effort to help the owners of the software to monitor the level of relevance of the application software that has been developed and operated in certain environment. This study aims to develop software ageing measurement model and therefore, the instrument for measuring the ageing should be developed as the input to identify the quality status and relevancy of the measured software. There are 3 phases in developing software ageing measurement instrument: development of measurement requirement, development of the instrument items and instrument validation. After all the processes have been implemented, the instrument is finalized and readied to be used in software ageing measurement model. In this study, the instrument was developed based on the Software Ageing Factors Hierarchical (SAFH) Framework. The measurement in the instrument uses Likert scales as the numerical values

Software quality and certification: Perception and practices in Malaysia

Recently, there has been an increasing amount of literature on software quality and at the same time complaints are reported widely on the quality status of software products. In the past few years, we have seen a tremendous growth of companies and agencies involved in the software industries not only in Malaysia but also in the entire world. The emergence of Multimedia Super Corridor (MSC) in Malaysia in 1996 was the starting point for the blooming of software and ICT related companies. Despite that, not much attention is given to the quality of software product that is being developed by various categories of companies. These companies could not justify the quality of their products to users and these users are left with uncertainties on the quality of software. This study was conducted to investigate the current practice and perception on software quality and assessment in Malaysian industries. A total of 43 organizations were surveyed to answer several issues on quality and certification. Some of the important findings from this survey were the need for standard and mechanism in software assessment, and the need for independent party certification to justify the quality status of software products. This paper discusses more findings of this survey

Towards a self-evolving software defect detection process

Software defect detection research typically focuses on individual inspection and testing techniques. However, to be effective in applying defect detection techniques, it is important to recognize when to use inspection techniques and when to use testing techniques. In addition, it is important to know when to deliver a product and use maintenance activities, such as trouble shooting and bug fixing, to address the remaining defects in the software.To be more effective detecting software defects, not only should defect detection techniques be studied and compared, but the entire software defect detection process should be studied to give us a better idea of how it can be conducted, controlled, evaluated and improved.This thesis presents a self-evolving software defect detection process (SEDD) that provides a systematic approach to software defect detection and guides us as to when inspection, testing or maintenance activities are best performed. The approach is self-evolving in that it is continuously improved by assessing the outcome of the defect detection techniques in comparison with historical data.A software architecture and prototype implementation of the approach is also presented along with a case study that was conducted to validate the approach. Initial results of using the self-evolving defect detection approach are promising

Software certification from process and product perspectives

Previous studies by other researchers in this discipline provide a set of axiom and supporting models for software assessment and quality but are not extended to a practical and well accepted model of certification. During the last five years, two preliminary works was undertaken in this research group to study issues of certification and these works are still continuing. Recently, this initial work was completed and extended. Two software certification models have been developed using requirements-designimplementation strategy to ensure that it meets the needs of a number of different interest groups in the industry.The two models focused on certifying software by development process and product quality approaches. The models have been tested by case study, which was launched collaboratively with industry in Malaysia.Further analysis has demonstrated feasibility and practicality of the models in a real environment. This paper discusses the implementation of these two models(SCfM_prod & SPAC) and their underlying results. The certification models defined in this research do not only offering a mechanism for assessment and certification, but also providing an alternative mechanism for monitoring of quality and continuous improvement of software quality throughout its life span

Software quality from behavioural and human perspectives

Software quality is evolving beyond static assessment to include behavioural attributes and human aspects.These two groups of attributes are vital and necessary to balance between technical and non-technical (human) aspects in software assessment. PQM or Pragmatic Quality Model is a proposed model of quality, which composes of behavioural and human perspectives in assessment. This model provides opportunity to give priority or contribution of quality attributes to reflect the business requirement. Therefore, it is more practical that can suit different users and purposes. As for our research, PQM is used for assessment of software for certification process. This paper explains in detail this model of PQM

Intelligent software quality and assessment model based on software behavioral and human factor approach

Software quality is a research area that falls in the nich of cyberspace security in the National Strategic Information and Communication Technology (ICT) Roadmap.This roadmap indicates that the cyberspace encompases not only the use of Internet but also less visible systems and infrastructures.The growing dependence of these systems brings about the critical need to protect sotware from destruction and incapacitation.Previous research has identified factors and attributes for static quality model.This research report discussess the construction of a dynamic software quality model for effective software assessment that assists in the development of quality software in the organisations. The proposed model consists of two main software quality attributes: the behavioral and the human aspect.These two components of quality produce a balance model between technical requirement and human factor.The available software quality model does not accommodate all the aspects of software quality requirements.The proposed dynamic model is capable to identify and recommend to the environment if there are any new attributes to be included in the model.This c an be done using filter wrapper based feature ranking technique.The objectives of this research are; to investigate the quality and assessment problems in software product; to develop a theoritical framework for intelligent software quality model ; to propose feature ranking technique for software quality and assessment; and to construct an intelligent software quality and assessment model. The research is conducted in five main phases which include: 1) the theoretical study; 2) design of formal framework on intelligent software quality and assessment; 3) model the software quality using Artificial Intelligence technique; 4) construction of intelligent model of software quality and assessment and; 5) conformation study.With respect to other ranking technique for software quality attribute, the proposed technique depicted a higher correlation with human experts.The model provides a way to assess software product using intelligent technique, which is useful for organization in selection and assessment of software as well as to integrate in future researches as a quality benchmark. This also ensure that the quality of the software meets the nation’s and organisation’s requirements and standards in current and future time

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