Defining and validating metrics for assessing the understandability of entity–relationship diagrams

Database and data model evolution cause significant problems in the highly dynamic business environment that we experience these days. To support the rapidly changing data requirements of agile companies, conceptual data models, which constitute the foundation of database design, should be sufficiently flexible to be able to incorporate changes easily and smoothly. In order to understand what factors drive the maintainability of conceptual data models and to improve conceptual modelling processes, we need to be able to assess conceptual data model properties and qualities in an objective and cost-efficient manner. The scarcity of early available and thoroughly validated maintainability measurement instruments motivated us to define a set of metrics for Entity–Relationship (ER) diagrams. In this paper we show that these easily calculated and objective metrics, measuring structural properties of ER diagrams, can be used as indicators of the understandability of the diagrams. Understandability is a key factor in determining maintainability as model modifications must be preceded by a thorough understanding of the model. The validation of the metrics as early understandability indicators opens up the way for an in-depth study of how structural properties determine conceptual data model understandability. It also allows building maintenance-related prediction models that can be used in conceptual data modelling practice.     

Measuring software product quality: a survey of ISO/IEC 9126

To address the issues of software product quality, the Joint Technical Committee 1 of the International Organization for Standardization and International Electrotechnical Commission published a set of software product quality standards known as ISO/IEC 9126. These standards specify software product quality's characteristics and subcharacteristics and their metrics. Based on a user survey, this study of the standard helps clarity quality attributes and provides guidance for the resulting standards.     

MOD2-SCM: A model-driven product line for software configuration management systems

ContextSoftware Configuration Management (SCM) is the discipline of controlling the evolution of large and complex software systems. Over the years many different SCM systems sharing similar concepts have been implemented from scratch. Since these concepts usually are hard-wired into the respective program code, reuse is hardly possible.ObjectiveOur objective is to create a model-driven product line for SCM systems. By explicitly describing the different concepts using models, reuse can be performed on the modeling level. Since models are executable, the need for manual programming is eliminated. Furthermore, by providing a library of loosely coupled modules, we intend to support flexible composition of SCM systems.MethodWe developed a method and a tool set for model-driven software product line engineering which we applied to the SCM domain. For domain analysis, we applied the FORM method, resulting in a layered feature model for SCM systems. Furthermore, we developed an executable object-oriented domain model which was annotated with features from the feature model. A specific SCM system is configured by selecting features from the feature model and elements of the domain model realizing these features.ResultsDue to the orthogonality of both feature model and domain model, a very large number of SCM systems may be configured. We tested our approach by creating instances of the product line which mimic wide-spread systems such as CVS, GIT, Mercurial, and Subversion.ConclusionThe experiences gained from this project demonstrate the feasibility of our approach to model-driven software product line engineering. Furthermore, our work advances the state of the art in the domain of SCM systems since it support the modular composition of SCM systems at the model rather than the code level.     

The impact of feature selection on maintainability prediction of service-oriented applications

Service-oriented development methodologies are very often considered for distributed system development. The quality of service-oriented computing can be best assessed by the use of software metrics that are considered to design the prediction model. Feature selection technique is a process of selecting a subset of features that may lead to build improved prediction models. Feature selection techniques can be broadly classified into two subclasses such as feature ranking and feature subset selection technique. In this study, eight different types of feature ranking and four different types of feature subset selection techniques have been considered for improving the performance of a prediction model focusing on maintainability criterion. The performance of these feature selection techniques is evaluated using support vector machine with different types of kernels over a case study, i.e., five different versions of eBay Web service. The performances are measured using accuracy and F-measure value. The results show that maintainability of the service-oriented computing paradigm can be predicted by using object-oriented metrics. The results also show that it is possible to find a small subset of object-oriented metrics which helps to predict maintainability with higher accuracy and also reduces the value of misclassification errors.     

基于多源特征空间的微服务可维护性评估

软件企业实践将遗留软件系统解耦成基于微服务架构的系统,以提高软件的可维护性,达到较快市场交付.评估微服务开发阶段的代码可维护性是一个关键问题,其面临数据多源化、可维护性关注点多样化的难点.通过分析源代码、代码运行轨迹、代码修订历史,提出一种多源特征空间模型以统一表示软件多源数据,并基于该模型,从功能性、模块性、可修改性...     

Multi-purpose,multi-level feature modeling of large-scale industrial software systems

Feature models are frequently used to capture the knowledge about configurable software systems and product lines. However, feature modeling of large-scale systems is challenging as models are needed for diverse purposes. For instance, feature models can be used to reflect the perspectives of product management, technical solution architecture, or product configuration. Furthermore, models are required at different levels of granularity. Although numerous approaches and tools are available, it remains hard to define the purpose, scope, and granularity of feature models. This paper first reports results and experiences of an exploratory case study on developing feature models for two large-scale industrial automation software systems. We report results on the characteristics and modularity of the feature models, including metrics about model dependencies. Based on the findings from the study, we developed FORCE, a modeling language, and tool environment that extends an existing feature modeling approach to support models for different purposes and at multiple levels, including mappings to the code base. We demonstrate the expressiveness and extensibility of our approach by applying it to the well-known Pick and Place Unit example and an injection molding subsystem of an industrial product line. We further show how our approach supports consistency between different feature models. Our results and experiences show that considering the purpose and level of features is useful for modeling large-scale systems and that modeling dependencies between feature models is essential for developing a system-wide perspective.     

A Controlled Expeniment on the Impact of Software Structure on Maintainability

This paper describes a study on the impact of software structure on maintainability aspects such as comprehensibility, locality, modifiability, and reusability in a distributed system environment. The study was part of a project at the University of Kaiserslautern, West Germany, to design and implement LADY, a LAnguage for Distributed systems. The study addressed the impact of software structure from two perspectives. The language designer's perspective was to evaluate the general impact of the set of structural concepts chosen for LADY on the maintainability of software systems implemented in LADY. The language user's perspective was to derive structural criteria (metrics), measurable from LADY systems, that allow the explanation or prediction of the software maintenance behavior. A controlled maintenance experiment was conducted involving twelve medium-size distributed software systems; six of these systems were implemented in LADY, the other six systems in an extended version of sequential Pascal. The benefits of the structural LADY concepts were judged based on a comparison of the average maintenance behavior of the LADY systems and the Pascal systems; the maintenance metrics were derived by analyzing the interdependence between structure and maintenance behavior of each individual LADY system.     

Predicting high-risk program modules by selecting the right software measurements

A timely detection of high-risk program modules in high-assurance software is critical for avoiding the high consequences of operational failures. While software risk can initiate from external sources, such as management or outsourcing, software quality is adversely affected when internal software risks are realized, such as improper practice of standard software processes or lack of a defined software quality infrastructure. Practitioners employ various techniques to identify and rectify high-risk or low-quality program modules. Effectiveness of detecting such modules is affected by the software measurements used, making feature selection an important step during software quality prediction. We use a wrapper-based feature ranking technique to select the optimal set of software metrics to build defect prediction models. We also address the adverse effects of class imbalance (very few low-quality modules compared to high-quality modules), a practical problem observed in high-assurance systems. Applying a data sampling technique followed by feature selection is a relatively unique contribution of our work. We present a comprehensive investigation on the impact of data sampling followed by attribute selection on the defect predictors built with imbalanced data. The case study data are obtained from several real-world high-assurance software projects. The key results are that attribute selection is more efficient when applied after data sampling, and defect prediction performance generally improves after applying data sampling and feature selection.     

基于源代码的面向对象软件可维护性度量模型

针对当前软件可维护性的度量难度大的突出问题,在详细阐述软件可维护性的概念和内涵的基础上,以ISO/IEC9126为指导,建立基于源代码的面向对象软件的可维护性度量模型。该模型主要包括可维护性的4个子特性模型和一个对子特性的综合模型,能够客观定量地计算出软件的可维护性水平。最后通过一个实例,验证该模型具有一定的科学性和合理性,在实际应用中有一定的指导意义。     

An approach to quality engineering of TTCN-3 test specifications

Experience with the development and maintenance of large test suites specified using the Testing and Test Control Notation (TTCN-3) has shown that it is difficult to construct tests that are concise with respect to quality aspects such as maintainability or usability. The ISO/IEC standard 9126 defines a general software quality model that substantiates the term “quality” with characteristics and subcharacteristics. The domain of test specifications, however, requires an adaption of this general model. To apply it to specific languages such as TTCN-3, it needs to be instantiated. In this paper, we present an instantiation of this model as well as an approach to assess and improve test specifications. The assessment is based on metrics and the identification of code smells. The quality improvement is based on refactoring. Example measurements using our TTCN-3 tool TRex demonstrate how this procedure is applied in practise. B. Zeiss is supported by a Ph.D. scholarship from Siemens AG, Corporate Technology.     

Mapping feature models onto domain models: ensuring consistency of configured domain models

We present an approach to model-driven software product line engineering which is based on feature models and domain models. A feature model describes both common and varying properties of the instances of a software product line. The domain model is composed of a structural model (package and class diagrams) and a behavioral model (story diagrams). Features are mapped onto the domain model by annotating elements of the domain model with features. An element of a domain model is specific to the features included in its feature annotation. An instance of the product line is defined by a set of selected features (a feature configuration). A configuration of the domain model is built by excluding all elements whose feature set is not included in the feature configuration. To ensure consistency of the configured domain model, we define constraints on the annotations of inter-dependent domain model elements. These constraints guarantee that a model element may be selected only when the model elements are also included on which it depends. Violations of dependency constraints may be removed automatically with the help of an error repair tool which propagates features to dependent model elements.     

Testing variability-intensive systems using automated analysis: an application to Android

Software product lines are used to develop a set of software products that, while being different, share a common set of features. Feature models are used as a compact representation of all the products (e.g., possible configurations) of the product line. The number of products that a feature model encodes may grow exponentially with the number of features. This increases the cost of testing the products within a product line. Some proposals deal with this problem by reducing the testing space using different techniques. However, a daunting challenge is to explore how the cost and value of test cases can be modeled and optimized in order to have lower-cost testing processes. In this paper, we present TESting vAriAbiLity Intensive Systems (TESALIA), an approach that uses automated analysis of feature models to optimize the testing of variability-intensive systems. We model test value and cost as feature attributes, and then we use a constraint satisfaction solver to prune, prioritize and package product line tests complementing prior work in the software product line testing literature. A prototype implementation of TESALIA is used for validation in an Android example showing the benefits of maximizing the mobile market share (the value function) while meeting a budgetary constraint.     

基于面向对象系统的质量度量模型PMMSQ的设计和实现

本文首先从软件质量度量的角度出发,阐述了软件质量度量的理论与方法,介绍了ISO9126模型;针对已有软件质量度量模型中存在的问题,提出了一个适合于软件质量度量实践的实用软件质量度量模型（PMMSQ）,并详细介绍了面向对象系统软件质量度量的步骤;最后,根据PMMSQ模型完成了软件度量活动的核心工作--对象特征集存储库的设
计和实现。     

Ordering Fault-Prone Software Modules

Software developers apply various techniques early in development to improve software reliability, such as extra reviews, additional testing, and strategic assignment of personnel. Due to limited resources and time, it is often not practical to enhance the reliability of all modules. Our goal is to target reliability enhancement activities to those modules that would otherwise have problems later. Prior research has shown that a software quality model based on software product and process metrics can predict which modules are likely to have faults.A module-order model is a quantitative software quality model that is used to predict the rank-order of modules according to a quality factor, such as the number of faults. The contribution of this paper is definition of module-order models and a method for their evaluation and use. Two empirical case studies of full-scale industrial software systems provide empirical evidence of the usefulness of module-order models for targeting reliability enhancement.     

An effective fault prediction model developed using an extreme learning machine with various kernel methods

System analysts often use software fault prediction models to identify fault-prone modules during the design phase of the software development life cycle. The models help predict faulty modules based on the software metrics that are input to the models. In this study, we consider 20 types of metrics to develop a model using an extreme learning machine associated with various kernel methods. We evaluate the effectiveness of the mode using a proposed framework based on the cost and efficiency in the testing phases. The evaluation process is carried out by considering case studies for 30 object-oriented software systems. Experimental results demonstrate that the application of a fault prediction model is suitable for projects with the percentage of faulty classes below a certain threshold, which depends on the efficiency of fault identification (low: 47.28%; median: 39.24%; high: 25.72%). We consider nine feature selection techniques to remove the irrelevant metrics and to select the best set of source code metrics for fault prediction.     

面向代码设计质量监控的软件度量指标集研究

随着软件的演化,软件规模和复杂性的上升往往会造成代码设计质量的退化,进而导致代码可维护性下降。已有大量软件度量指标用于量化代码设计质量,但是由于数量众多,不同指标体系度量结果可比性较差,使得开发人员难以找到存在设计质量问题的模块。系统调研并整理归类了现有的规模、耦合、内聚、封装、继承和多态等6方面软件度量指标。结合度量指标关系以及实验分析,从每个方面的指标集中发现了与代码设计质量关联度最高的6个指标,从而提出一种面向代码设计质量监控的软件度量指标集。实验表明,该指标集可以有效挑选出存在代码设计质量问题的类,可作为开发人员监控和定位代码设计问题的重点关注指标。     

基于特征分解模式的软件产品线参考设计方法

基于特征的领域分析与建模技术是软件产品线开发中较为主流的需求建模方法,为描述产品线共性和可变性及其之间的关系提供了良好的支持。然而在现有特征模型基础上,如何指导系统开发人员进行软件系统的详细设计是亟待解决的问题。该问题主要体现在特征之间的结构与语义关系,以及特征的可变性如何映射为合理的系统设计模型这两个方面。针对上述问题,提出一种基于特征分解模式的软件产品线参考设计方法。该方法为特征模型中具有不同结构、不同语义的特征分解模式提供参考的详细设计方案,并提出相关聚类准则以支持对应全局特征模型的设计模型优化。最后,通过成绩录入软件产品线对该方法的有效性进行验证。     

Standardized code quality benchmarking for improving software maintainability

We provide an overview of the approach developed by the Software Improvement Group for code analysis and quality consulting focused on software maintainability. The approach uses a standardized measurement model based on the ISO/IEC 9126 definition of maintainability and source code metrics. Procedural standardization in evaluation projects further enhances the comparability of results. Individual assessments are stored in a repository that allows any system at hand to be compared to the industry-wide state of the art in code quality and maintainability. When a minimum level of software maintainability is reached, the certification body of TüV Informationstechnik GmbH issues a Trusted Product Maintainability certificate for the software product.     

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.