Pemetaan Secara Sistematis Pada Metrik Kualitas Perangkat Lunak

. Software quality assurance is one method to increase quality of software. Improvement of software quality can be measured with software quality metric. Software quality metrics are part of software quality measurement model. Currently software quality models have a very diverse types, so that software quality metrics become increasingly diverse. The various types of metrics to measure the quality of software create proper metrics selection issues to fit the desired quality measurement parameters. Another problem is the validation need to be performed on these metrics in order to obtain objective and valid results. In this paper, a systematic mapping of the software quality metric is conducted in the last nine years. This paper brings up issues in software quality metrics that can be used by other researchers. Furthermore, current trends are introduced and discussed

Quality Assurance of Software Models - A Structured Quality Assurance Process Supported by a Flexible Tool Environment in the Eclipse Modeling Project

The paradigm of model-based software development (MBSD) has become more and more popular since it promises an increase in the efficiency and quality of software development. In this paradigm, software models play an increasingly important role and software quality and quality assurance consequently leads back to the quality and quality assurance of the involved models. The fundamental aim of this thesis is the definition of a structured syntax-oriented process for quality assurance of software models that can be adapted to project-specific and domain-specific needs. It is structured into two sub-processes: a process for the specification of project-specific model quality assurance techniques, and a process for applying them on concrete software models within a MBSD project. The approach concentrates on quality aspects to be checked on the abstract model syntax and is based on quality assurance techniques model metrics, smells, and refactorings well-known from literature. So far, these techniques are mostly considered in isolation only and therefore the proposed process integrates them in order to perform model quality assurance more systematically. Three example cases performing the process serve as proof-of-concept implementations and show its applicability, its flexibility, and hence its usefulness. Related to several issues concerning model quality assurance minor contributions of this thesis are (1) the definition of a quality model for model quality that consists of high-level quality attributes and low-level characteristics, (2) overviews on metrics, smells, and refactorings for UML class models including structured descriptions of each technique, and (3) an approach for composite model refactoring that concentrates on the specification of refactoring composition. Since manually reviewing models is time consuming and error prone, several tasks of the proposed process should consequently be automated. As a further main contribution, this thesis presents a flexible tool environment for model quality assurance which is based on the Eclipse Modeling Framework (EMF), a common open source technology in model-based software development. The tool set is part of the Eclipse Modeling Project (EMP) and belongs to the Eclipse incubation project EMF Refactor which is available under the Eclipse public license (EPL). The EMF Refactor framework supports both the model designer and the model reviewer by obtaining metrics reports, by checking for potential model deficiencies (called model smells) and by systematically restructuring models using refactorings. The functionality of EMF Refactor is integrated into standard tree-based EMF instance editors, graphical GMF-based editors as used by Papyrus UML, and textual editors provided by Xtext. Several experiments and studies show the suitability of the tools for supporting the techniques of the structured syntax-oriented model quality assurance process

High-Dimensional Software Engineering Data and Feature Selection

Software metrics collected during project development play a critical role in software quality assurance. A software practitioner is very keen on learning which software metrics to focus on for software quality prediction. While a concise set of software metrics is often desired, a typical project collects a very large number of metrics. Minimal attention has been devoted to finding the minimum set of software metrics that have the same predictive capability as a larger set of metrics – we strive to answer that question in this paper. We present a comprehensive comparison between seven commonly-used filter-based feature ranking techniques (FRT) and our proposed hybrid feature selection (HFS) technique. Our case study consists of a very highdimensional (42 software attributes) software measurement data set obtained from a large telecommunications system. The empirical analysis indicates that HFS performs better than FRT; however, the Kolmogorov-Smirnov feature ranking technique demonstrates competitive performance. For the telecommunications system, it is found that only 10% of the software attributes are sufficient for effective software quality prediction

A Graph-Based Model for Component-Based Software Development

Software metrics can be used to objectively quantify the quality of software components and systems, alleviating quality and risk concerns and raising assurance in component-based systems. In this paper, we present a graph-based model for component-based software development. We assume that a number of components have been characterized in terms of non-functional metrics of importance to the software system being developed, and that the interfaces connecting various components have been similarly characterized. The emphasis of this work is on cost and quality of the system under development, and reaching an acceptable compromise between the two

An Empirical Study on the Procedure to Derive Software Quality Estimation Models

Software quality assurance has been a heated topic for several decades. If factors that influence software quality can be identified, they may provide more insight for better software development management. More precise quality assurance can be achieved by employing resources according to accurate quality estimation at the early stages of a project. In this paper, a general procedure is proposed to derive software quality estimation models and various techniques are presented to accomplish the tasks in respective steps. Several statistical techniques together with machine learning method are utilized to verify the effectiveness of software metrics. Moreover, a neuro-fuzzy approach is adopted to improve the accuracy of the estimation model. This procedure is carried out based on data from the ISBSG repository to present its empirical value

Towards Ontology-based SQA Recommender for Agile Software Development

Agility is heavily dependent on tacit knowledge, skilled and motivated employees, and frequent communications. Although, the Agile Manifesto claims fast and light software development process while maintaining high quality, it is however not very clear how current agile practices and methods attain quality under time pressure and unstable requirements. In this paper, we present an ontological approach for process-driven Quality Assurance support for agile software development. Challenges related to the role of Quality Assurance in agile projects are addressed by developing a process-driven recommender that provides tailored resources to user’s queries. The proposed ontological model embeds both conceptual and operational SQA knowledge about software processes and their requirements, including quality attributes, SQA measurements, SQA metrics and related SQA techniques and procedures

Generalization Index: Defining a metric for the detection of smells in UML Class Diagrams in Eclipse Modeling Framework in Eclipse

In the field of Software Engineering, while designing the software design and maintaining the source code quality, a lot of good and bad practices come into being. With the continuous evolutions in the field of modeling in software development processes, Model Driven Software Development (MDSD), focuses towards the quality of software models. Unified Modeling Language (UML) is a graphical notation for expressing object-oriented designs. With its emergence as a modeling standard and being widely accepted by most software development organizations, in this research paper we focus on UML Class Diagrams. Metrics are mathematical models used for measuring. In software engineering, metrics are utilized for measuring quality aspects of software models. A manual model review is very time consuming and prone to errors, so it becomes essential to automate the tasks as effectively as possible. The Eclipse plug-in EMF Metrics supports specification and calculation of metrics wrt. specific EMF based models. A new definition technique for EMF quality assurance can be defined using Java, an OCL query or Henshin Pattern. In this paper we propose an algorithm for the calculation a new metric named Generalization Index Metric (GIX) for Java Code

An Investigation into quality assurance of the Open Source Software Development model

A thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of PhilosophyThe Open Source Software Development (OSSD) model has launched products in rapid succession and with high quality, without following traditional quality practices of accepted software development models (Raymond 1999). Some OSSD projects challenge established quality assurance approaches, claiming to be successful through partial contrary techniques of standard software development. However, empirical studies of quality assurance practices for Open Source Software (OSS) are rare (Glass 2001). Therefore, further research is required to evaluate the quality assurance processes and methods within the OSSD model. The aim of this research is to improve the understanding of quality assurance practices under the OSSD model. The OSSD model is characterised by a collaborative, distributed development approach with public communication, free participation, free entry to the project for newcomers and unlimited access to the source code. The research examines applied quality assurance practices from a process view rather than from a product view. The research follows ideographic and nomothetic methodologies and adopts an antipositivist epistemological approach. An empirical research of applied quality assurance practices in OSS projects is conducted through the literature research. The survey research method is used to gain empirical evidence about applied practices. The findings are used to validate the theoretical knowledge and to obtain further expertise about practical approaches. The findings contribute to the development of a quality assurance framework for standard OSSD approaches. The result is an appropriate quality model with metrics that the requirements of the OSSD support. An ideographic approach with case studies is used to extend the body of knowledge and to assess the feasibility and applicability of the quality assurance framework. In conclusion, the study provides further understanding of the applied quality assurance processes under the OSSD model and shows how a quality assurance framework can support the development processes with guidelines and measurements

Quality assessment technique for ubiquitous software and middleware

The new paradigm of computing or information systems is ubiquitous computing systems. The technology-oriented issues of ubiquitous computing systems have made researchers pay much attention to the feasibility study of the technologies rather than building quality assurance indices or guidelines. In this context, measuring quality is the key to developing high-quality ubiquitous computing products. For this reason, various quality models have been defined, adopted and enhanced over the years, for example, the need for one recognised standard quality model (ISO/IEC 9126) is the result of a consensus for a software quality model on three levels: characteristics, sub-characteristics, and metrics. However, it is very much unlikely that this scheme will be directly applicable to ubiquitous computing environments which are considerably different to conventional software, trailing a big concern which is being given to reformulate existing methods, and especially to elaborate new assessment techniques for ubiquitous computing environments. This paper selects appropriate quality characteristics for the ubiquitous computing environment, which can be used as the quality target for both ubiquitous computing product evaluation processes ad development processes. Further, each of the quality characteristics has been expanded with evaluation questions and metrics, in some cases with measures. In addition, this quality model has been applied to the industrial setting of the ubiquitous computing environment. These have revealed that while the approach was sound, there are some parts to be more developed in the future