Software Quality Attributes Research Articles

Empirical Evaluation of a New Coupling Metric: Combining Structural and Semantic Coupling

Coupling, a measure of the interdependence among software entities, is an important property for which many software metrics have been defined. It is widely agreed that the extent of coupling in an object-oriented system has implications for its external quality. Structural and semantic relations between classes can be measured directly from static source code. However, both have limitations. In order to understand which aspects of coupling affect quality or other external attributes of software, this paper presents a new coupling metric for object-oriented systems that analyze structural and semantic relationships between methods and classes. The paper investigates the use of the new proposed coupling metric during change impact analysis, predicting fault-prone and maintainable classes. By comparing the new metric to other coupling metrics, we show that the new metric is a better predictor for classes impacted by changes. The new metric also shows good promise in predicting both external qualities (fault proneness and maintainability).

Students' evaluation of learning management systems in the personal computer and smartphone computing environments

The objective of this study is twofold: 1) to investigate an impact of software quality attributes of a learning management system (LMS) on students' satisfaction in both the personal computer and the smartphone settings; 2) to examine whether LMS quality factors have different impacts in the smartphone context and the PC context. We explore five quality attributes of LMS (capability, usability, performance, reliability and documentation). Data from a survey of 193 students were analysed using ordered logit regression. Findings showed that while only usability and reliability significantly affected user satisfaction in the PC context; all the quality attributes except documentation had a significant influence on user satisfaction in the smartphone setting. We also found that reliability was twice as important to user satisfaction in the smartphone context as in the PC context. The results imply that LMS quality attributes have different impacts on students' satisfaction in the smartphone context from the PC context.

On the relationships between QoS and software adaptability at the architectural level

Modern software operates in highly dynamic and often unpredictable environments that can degrade its quality of service. Therefore, it is increasingly important having systems able to adapt their behavior. However, the achievement of software adaptability can influence other software quality attributes, such as availability, performance or cost. This paper proposes an approach for analyzing tradeoffs between the system adaptability and its quality of service. The proposed approach is based on a set of metrics that allow the system adaptability evaluation. The approach can help software architects to guide decisions on system adaptation for fulfilling system quality requirements. The application and effectiveness of the approach are illustrated through examples and a wide set of experiments carried out with a tool we have developed.

Improving Fault Prediction using ANN-PSO in Object Oriented Systems

oriented software metrics are computed and used in predicting software quality attributes of object oriented systems. Mapping software metrics to software quality attributes like fault prediction is a complex process and requires extensive computations. Many models have been proposed for fault prediction. Since accuracy is of prime importance in prediction models they are being constantly improved through various research studies. Artificial Neural network (ANN) has gained immense popularity due to its adaptability to the problem at hand by training with known data. Back propagation is a widely used ANN training technique. However the back propagation technique leads to slow convergence rate and an impending threat of getting caught in local minima. In this paper we explore the Particle Swarm Optimization (PSO) technique as an alternative to optimize the weights of ANN for fault prediction in object oriented systems. We evaluate the effect on prediction accuracy that PSO brings to ANN compared to other techniques like BP and Genetic Algorithm (GA). We also evaluate prediction accuracy improvements by optimizing the various parameters of PSO.

Research state of the art on GoF design patterns: A mapping study

Design patterns are used in software development to provide reusable and documented solutions to common design problems. Although many studies have explored various aspects of design patterns, no research summarizing the state of research related to design patterns existed up to now. This paper presents the results of a mapping study of about 120 primary studies, to provide an overview of the research efforts on Gang of Four (GoF) design patterns. The research questions of this study deal with (a) if design pattern research can be further categorized in research subtopics, (b) which of the above subtopics are the most active ones and (c) what is the reported effect of GoF patterns on software quality attributes. The results suggest that design pattern research can be further categorized to research on GoF patterns formalization, detection and application and on the effect of GoF patterns on software quality attributes. Concerning the intensity of research activity of the abovementioned subtopics, research on pattern detection and on the effect of GoF patterns on software quality attributes appear to be the most active ones. Finally, the reported research to date on the effect of GoF patterns on software quality attributes are controversial; because some studies identify one pattern's effect as beneficial whereas others report the same pattern's effect as harmful.

Software Reverse Engineering Tool for Object Oriented Programming

Software quality metrics plays the vital role in the process of assessing software as in qualitative and quantitative terms. Basically, software quality metrics determines specific but some important properties, attributes or characteristics of software in terms of numbers, values or some symbols. This type of assessment should be occurred according the some welldefined measurement rules. Software quality metrics are not only the static measurement state of project but also it will help in assessing the behavior, size, quality and complexity etc, of software. Evaluation of software quality metrics is used to predict the fault-prone area and components of software in early stage of reengineering process of existing software as quality indicators. These software quality metrics helps to identify the problem from software in early stages of the reengineering of existing software. Therefore, this paper deals with automate software quality metrics tool namely Software Reverse Engineering Tool (SRET) which should be developed to determine the different software quality metrics and attributes of object oriented programming. Hence these metrics measures the complexity, effectiveness, efficiency of software and these metrics should be save time and cost of software analyzer, developer, tester etc., for reengineering the existing software with less effort.

Improvement in Quality of Software Architecture via Enhanced-Pattern Driven Architecture (EPDA)

No doubt software plays an important role in improvement of our lives. Great demand of software makes software architecture more complex. Flaws in any software have direct impact on diverse fields of life (such as business, science, engineering etc). The main reason of any software failure is due to poor software architecture or quality attributes. This paper focuses on factors that affect the quality of software architectures and highlighted the major reason of the defects through questionnaire and survey. In the light of this survey a technique is proposed to improve the quality of any software architecture. The proposed architecture is Enhanced-Pattern driven architecture (EPDA). This architecture focuses on the improvement of design phase in any architecture. This will also help in resolving lots of problems which arise due to usage of different traditional architectural styles.

Using Software Quality Attributes to Classify Refactoring to Patterns

Refactoring to patterns allows software designers to safely move their designs towards specific design patterns by applying multiple low-level refactorings. There are many different refactoring to pattern techniques, each with a particular purpose and a varying effect on software quality attributes. Thus far, software designers do not have a clear means to choose refactoring to pattern techniques to improve certain quality attributes. This paper takes the first step towards a classification of refactoring to pattern techniques based on their measurable effect on software quality attributes. This classification helps software designers in selecting the appropriate refactoring to pattern techniques that will improve the quality of their design based on their design objectives. It also enables them to predict the quality drift caused by using specific refactoring to pattern techniques.

Software Requirements Management through the Lenses of People, Organizational and Technological Dimensions

The inadequate specification of requirements remains being indicated as one of the main reasons for the failure of software development projects. A possible explanation for this failure is that requirements management tends to overvalue the technology side of requirements. However, the requirements management depends on other important issues beyond technology which are sometimes neglected. Good requirements are only assured by the right balance of three dimensions: people, organization and technology. Through the lens of each of these three dimensions, this paper reviews significant literature, identifying some of the key issues and concerns about the management of software requirements, particularly the software requirements specification. Major software quality attributes, like clearness, completeness, correctness, understandability, verifiability or validity, consistency and feasibility, are used to analyse several important facets of software requirements management. Implications for future research are discussed.

A Discrete Event Simulation Model for the Analysis of Software Quality Attributes


 
 
 A discrete event simulation model for evaluating quality attributes, employing the software architecture, is proposed in this work. A metamodel of the software architecture domain that includes the concepts required for measuring quality attributes at runtime is specified. So, a simulation model is built from it, following the principles of hierarchy and modularity, assembling simple blocks to obtain complex blocks. DEVS framework is applied to obtain a decoupled model from the simulator, and the DEVS formalism is used to specify the elements of the simulation model.
 The objective of this approach is to provide information about the quality attributes that can be measured at runtime, introducing the discrete event simulation in the context of the software architecture design. This quantitative information will assist the architect to make decisions about the design of the system.
 
 

A Classification of Refactoring Methods Based on Software Quality Attributes

Refactoring is the process of improving the design of existing code by changing its internal structure without affecting its external behavior. Refactoring tends to improve software quality by improving design, improving readability and reducing ‘bugs’. There are many different refactoring methods, each having a particular purpose and effect. Consequently, the effect of refactoring methods on software quality attributes may vary. Moreover, it is often unclear to software designers how to use refactoring methods to improve specific quality attributes. In this paper, we propose a classification of refactoring methods based on their measurable effect on software quality attributes. This, in turn, helps software designers choose appropriate refactoring methods that will improve the quality of their designs, based on the design objectives. It also enables them to predict the quality drift caused by using particular refactoring methods.

The Impact of Refactoring to Patterns on Software Quality Attributes

The search for techniques to improve software quality and achieve robust, reliable, and maintainable software is ongoing. Refactoring, an approach that improves the internal structure of software without affecting its external behavior, is one method that aims to achieve better quality. Refactoring to patterns is another. The goal of this paper is to investigate whether refactoring to patterns improves software quality. This is done empirically by examining the metric values of external quality attributes for different software systems before and after refactoring to patterns is applied. We found no consistent improvement trends in the software quality attributes. This is because each refactoring to patterns technique has a particular purpose and effect, and hence affects software quality attributes differently.

Integrated Software Quality Evaluation: A Fuzzy Multi-Criteria Approach

Software measurement is a key factor in managing, controlling, and improving the software development processes. Software quality is one of the most important factors for assessing the global competitive position of any software company. Thus the quantification of quality parameters and integrating them into quality models is very essential. Software quality criteria are not very easily measured and quantified. Many attempts have been made to exactly quantify the software quality parameters using various models such as ISO/IEC 9126 Quality Model, Boehm's Model, McCall's model, etc. In this paper an attempt has been made to provide a tool for precisely quantifying software quality factors with the help of quality factors stated in ISO/IEC 9126 model. Due to the unpredictable nature of the software quality attributes, the fuzzy multi criteria approach has been used to evolve the quality of the software.

On the relationship of concern metrics and requirements maintainability

Context Maintainability has become one of the most essential attributes of software quality, as software maintenance has shown to be one of the most costly and time-consuming tasks of software development. Many studies reveal that maintainability is not often a major consideration in requirements and design stages, and software maintenance costs may be reduced by a more controlled design early in the software life cycle. Several problem factors have been identified as harmful for software maintainability, such as lack of upfront consideration of proper modularity choices. In that sense, the presence of crosscutting concerns is one of such modularity anomalies that possibly exert negative effects on software maintainability. However, to the date there is little or no knowledge about how characteristics of crosscutting concerns, observable in early artefacts, are correlated with maintainability. Objective In this setting, this paper introduces an empirical analysis where the correlation between crosscutting properties and two ISO/IEC 9126 maintainability attributes, namely changeability and stability, is presented. Method This correlation is based on the utilization of a set of concern metrics that allows the quantification of crosscutting, scattering and tangling. Results Our study confirms that a change in a crosscutting concern is more difficult to be accomplished and that artefacts addressing crosscutting concerns are found to be less stable later as the system evolves. Moreover, our empirical analysis reveals that crosscutting properties introduce non-syntactic dependencies between software artefacts, thereby decreasing the quality of software in terms of changeability and stability as well. These subtle dependencies cannot be easily detected without the use of concern metrics. Conclusion The correlation provides evidence that the presence of certain crosscutting properties negatively affects to changeability and stability. The whole analysis is performed using as target cases three software product lines, where maintainability properties are of upmost importance not only for individual products but also for the core architecture of the product line.

Empirical comparison of three metrics suites for fault prediction in packages of object-oriented systems: A case study of Eclipse

► We empirically compared three suites of package-level metrics (Martin, MOOD and CK). ► We evaluated their accuracy in fault prediction in packages of Eclipse system. ► Seven prediction models were built using different combinations of the three suites. ► Prediction models that include subset of Martin metrics outperform the others. Packages are important high-level organizational units for large object-oriented systems. Package-level metrics characterize the attributes of packages such as size, complexity, and coupling. There is a need for empirical evidence to support the collection of these metrics and using them as early indicators of some important external software quality attributes. In this paper, three suites of package-level metrics (Martin, MOOD and CK) are evaluated and compared empirically in predicting the number of pre-release faults and the number of post-release faults in packages. Eclipse, one of the largest open source systems, is used as a case study. The results indicate that the prediction models that are based on Martin suite are more accurate than those that are based on MOOD and CK suites across releases of Eclipse.

Using structural and textual information to capture feature coupling in object-oriented software

Previous studies have demonstrated the relationship between coupling and external software quality attributes, such as fault-proneness, and the application of coupling to software maintenance tasks, such as impact analysis. These previous studies concentrate on class coupling. However, there is a growing focus on the study of features in software, and features are often implemented across multiple classes, meaning class-level coupling measures are not applicable. We ask the pertinent question, “Is measuring coupling at the feature-level also useful?” We define new feature coupling metrics based on structural and textual source code information and extend the unified framework for coupling measurement to include these new metrics. We also conduct three extensive case studies to evaluate these new metrics and answer this research question. The first study examines the relationship between feature coupling and fault-proneness, the second assesses feature coupling in the context of impact analysis, and the third study surveys developers to determine if the metrics align with what they consider to be coupled features. All three studies provide evidence that feature coupling metrics are indeed useful new measures that capture coupling at a higher level of abstraction than classes and can be useful for finding bugs, guiding testing effort, and assessing change impact.

A fuzzy group analytical hierarchy process approach for software quality assurance management: Fuzzy logarithmic least squares method

This paper proposes a Fuzzy Group Analytical Hierarchy Process approach for assessing the quality of software, with judgments by a group of experts at different levels. The international standard of software quality attributes, ISO/IEC9126-1:2001 which comprises of 6 criteria with 27 subcriteria, is applied as the attributes of software quality. Regarding the prioritization method, the modified fuzzy Logarithmic Least Squares Method (LLSM) is applied to derive the importance weight vectors. The Fuzzy Prioritization Programming for Direct Rating Scales (FPP-DRS) on the basis of the modified fuzzy LLSM and the rescaling functions is proposed to design the direct rating scales in fuzzy number. The Fuzzy Synthesis Programming for Absolute Measurement (FSPAM) including Integrated Fuzzy Scores of Individual Expert (IFSIE) and Group Integrated Fuzzy Score (GIFS) is proposed to aggregate the criteria values from various experts. The proposed approach can help a group of various experts including developers, testers and purchasers, to measure the level of the software quality of the in-house development or the third party development.

Investigation of Aspect-Oriented Metrics for Stability Assessment: A Case Study

Stability assessment provides software managers with early insight into trends in software evolution, and thus assists them in managing and controlling long-lived software systems. However, there are few empirical studies that have been conducted to relate software metrics with external quality attributes of aspect-oriented software in general, and metrics have not been evaluated as indicators of aspect stability in particular. This paper investigates the relationships between 13 aspect-oriented metrics and aspect stability. These metrics measure different structural properties of an aspect: size, coupling, cohesion, and inheritance. A case study was conducted using an open source aspect-oriented software consisting of 76 aspects. The results obtained from this study indicate statistically significant correlation between most of the size metrics and aspect stability. The cohesion metric was also found to be significantly correlated with aspect stability. In addition, different prediction models were built using different combinations of metrics’ categories. It was observed that the best accuracy was achieved as a function of some of the size and inheritance metrics.

Assessing Internal Software Quality Attributes of the Object-Oriented and Service-Oriented Software Development Paradigms: A Comparative Study

Service-Oriented Architecture (SOA) is becoming the dominant approach for developing and organizing distributed enterprise-wide applications. Although the concepts of SOA have been extensively described in the literature and in-dustry, the effects of adopting SOA on software quality are still unclear. The aim of the paper is to analyze how adopt-ing SOA can affect software quality as opposed to the Object-Oriented (OO) paradigm and expose the differential implications of adopting both paradigms on software quality. The paper provides a brief introduction of the architectural differences between the Service-Oriented (SO) and OO paradigms and a description of internal software quality metrics used for the comparison. The effects and differences are exposed by providing a case study architected for both paradigms. The quantitative measure concluded in the paper showed that a software system developed using SOA approach provides higher reusability and lower coupling among software modules, but at the same time higher complexity than those of the OO approach. It was also found that some of the existing OO software quality metrics are inapplicable to SOA software systems. As a consequence, new metrics need to be developed specifically to SOA software systems.

Improvement of Software Quality Attributes in Object Oriented Analysis and Design Phase Using Goal-Question-Metric Paradigm

In a competitive business landscape, large organizations such as insurance companies and banks are under high pres-sure to innovate, improvise and distinguish their products and services while continuing to reduce the time-to market for new product introductions. Traditional approaches to software reliability modeling for such software are black box-based. Bad structure or model again can lead us to lower down these non functional properties. The basic constructs of the model are objects. We will not deal about the identification of the objects, as may be referred in many books, but how to model those objects. The objective of this paper is to provide a philosophical approach, using Goal-Question-Metric paradigm, to structure or model the identified objects of software system, in better way to improve the quality of the software.