Towards a Formal Approach for Assessing the Design Quality of Object-Oriented Systems

Background: Using design metrics to predict fault-prone elements of a software design can help to focus attention on classes that need redesign and more extensive testing. However, some design metrics have been pointed out to be theoretically invalid, and the usefulness of some metrics is questioned. Aim: To identify a set of object-oriented metrics that are theoretically valid, and useful for identifying fault-prone classes in a design. Method: Drawing on four well-known sets of design metrics (CK, LK, MOOD and QMOOD), we propose a consolidated set of metrics that covers many aspects of object-oriented software design. We conduct two experiments, first using a single large system and then considering successive releases of that system, to compare the usefulness of the consolidated set with the other four sets for within-project prediction of fault-prone classes. Results: Both experiments suggest the consolidated set is effective at identifying fault-prone classes, outperforming the other metric sets (though at a cost of more false alarms). Conclusion: This paper adds to knowledge about the usefulness of existing sets of design metrics for within-project defect prediction, and identifies a consolidated set of metrics that is more effective than the existing sets at identifying fault-prone classes.

Object-oriented software metrics are important in software engineering field for measurement of the software quality, size estimation, complexity and effort. Object oriented software development is the most popular and best practice in software development. Object oriented software metrics can be used for measuring extend of object orientedness of a program. These quantities are important information indicators, that can be helpful for a software developer in take decisions for designing good software. It is proven that the software metrics provide quantitative information about the structure of the code, which can be used to determine the reliability of software. The design of the software is highly recommended to be object oriented in the software development environment. Software metrics specific to programs that have object oriented design can be used to measure the quality of the software like inheritance, assessing the effects of coupling, the complexity of the code, size aspects, etc, of the software developed in such an environment. Software measurement is a way for assessing the quality of software. Many attributes can define quality of a software, internal (size, complexity) as well as external (reliability)[14]. Often internal attributes are contributing factors to external attributes. Reliability as a term means the degree to which a component, product or system executes specified functions for a specific period of time under specified conditions. Software reliability is the software being trustworthy of the specifications. The aim of the work is to model the relationship between reliability of object oriented software to the object oriented design metrics and predict reliability of software.

An alternative approach for measuring object-oriented (OO) software quality has been proposed by applying the Analytic Hierarchy Process (AHP) scheme. This approach is effective in defining the rank of software quality over a number of Java applications based on two sets of metric values representing main OO structural properties. The Metrics for Object-Oriented Software Engineering (MOOSE) and Metrics for Object-Oriented Design (MOOD) that have been describing individual characteristic of OO property now are integrated by means of AHPs pairwise comparison to deliver an estimate quantitative value of OO software design quality. A series of experiments were conducted by applying the approach to students works in Fundamental of Programming class. The results of applying AHP scheme were compared to experts judgments for verification. The result demonstrates the solidity of AHP mechanism for the intended purpose of measuring OO design quality.

There are many tools and methodologies are available for the development of software. The development consists of activities such as analyze, design, code, test, implement and maintenance. This paper provides the information about measuring the metrics of Object Oriented Software (OOS) development and proposed a Metric Measurement Model (MMM) to ensure that metrics of quality attributes are very important in Object Oriented Software improvement. OOS is a system to enlarge objects that are easily reused, modified and replaced. All objects have attributes and methods, so it works at a privileged level of generalization. Objects are collected to outline a class. The quality of OOS design can be improved by measuring the object oriented design metrics. The OO design is done by UML diagrams; particularly class diagram holds the important part of designing in the development process. Early measurement of metrics will leads to good quality software.

Presents a novel way of using object-oriented design metrics to support the incremental development of object-oriented programs. Based on a quality model (the factor-criteria-metrics model), so-called multi-metrics relate a number of simple structural measurements to design principles and rules. Single components of an object-oriented program like classes or subsystems are analyzed to determine whether they conform to specific design goals. Concise measurement reports, together with detailed explanations of the obtained values, identify problem spots in system design and give hints for improvement. This allows the designer to measure and evaluate programs at an appropriate level of abstraction. This paper details the use of the multi-metrics approach for the design and improvement of a framework for industry and its use for graphical applications. Multi-metrics tools were used with several versions of the framework. The measurement results were used in design reviews to quantify the effects of efforts to reorganize the framework. The results showed that this approach was very effective at giving good feedback, even to very experienced software developers. It helped them to improve their software and to create stable system designs.

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.

A comparison of sixteen quality metrics for object-oriented design

As software systems continue to grow more complex, evaluating software quality becomes increasingly critical. This study analyzes existing software quality models, including McCall, Boehm, FURPS, and ISO Systems and Software Engineering – Systems and Software Quality Requirements and Evaluation (SQuaRE), with a specific focus on the ISO/IEC 25010:2023 standard. The research aims to assess the completeness of these models and explore interdependencies among key quality attributes relevant to software requirements engineering. The paper identifies key characteristics and associated metrics based on ISO/IEC standards using comparative analysis and a literature review. Findings show that ISO/IEC 25010:2023 provides the most comprehensive structure, with Functional Suitability and Compatibility identified as essential due to their universally recommended metrics. Survey data from 328 practicing analysts in Ukraine and internationally demonstrate a gap between theoretical models and real-world requirements documentation practices, particularly for non-functional requirements. The identified dependencies between quality attributes enable a more integrated and structured approach to identifying and analyzing non-functional requirements in IT projects. The study emphasizes that software quality models must be tailored to project-specific goals and constraints, with attention to trade-offs and stakeholder needs during the requirements specification, prioritization, and validation processes. The findings support the adaptation of quality models to specific project constraints and emphasize the business analyst’s role in tailoring quality criteria for practical use in software development.

Software design is one of the most important and key activities in the system\ndevelopment life cycle (SDLC) phase that ensures the quality of software.\nDifferent key areas of design are very vital to be taken into consideration\nwhile designing software. Software design describes how the software system is\ndecomposed and managed in smaller components. Object-oriented (OO) paradigm has\nfacilitated software industry with more reliable and manageable software and\nits design. The quality of the software design can be measured through\ndifferent metrics such as Chidamber and Kemerer (CK) design metrics, Mood\nMetrics & Lorenz and Kidd metrics. CK metrics is one of the oldest and most\nreliable metrics among all metrics available to software industry to evaluate\nOO design. This paper presents an evaluation of CK metrics to propose an\nimproved CK design metrics values to reduce the defects during software design\nphase in software. This paper will also describe that whether a significant\neffect of any CK design metrics exists on total number of defects per module or\nnot. This is achieved by conducting survey in two software development\ncompanies.\n

Software maintenance is a vital component that every company has to face when their product is delivered to the stakeholders. This task may span for more than ten years at the customer site.The cost of maintenance or keeping software operational consumes 60-70% of its entire life cycle cost. Definingmaintainability at the design stage of the software development life cycle (SDLC) will result in a cost effective product. In this paper, we proposed a design time relationship model between design properties and the maintainability of the software. This analysis is performed based on the influence of object oriented design metrics on software maintainability

Developing a good software system is a very complex task. In order to produce a good software product, several measures for software quality attributes need to be taken into account. System complexity measurement plays a vital role in controlling and managing software quality because it generally affects the software quality attributes like software reliability, software testability and software maintainability. Thus, software quality assurance (SQA) needs to be addressed keeping in view the new strategies, tool, methodologies and techniques applicable to software development life cycle.This paper is primarily aimed at revisiting and examining peculiar aspects of software development process that affect software quality management process. These aspects of software development process include software reliability measurement, ISO approach applicable to software quality and some aspects related to software testing improvement. Software testing and evaluation methods/tools/techniques do not guarantee effective testing and ensure high software quality. The way to improve the effectiveness of testing is to improve the attitude of software developers towards testing.In this paper, all these factors affecting software quality management have been discussed as well as all the possible improvements have been suggested. The results of this paper may be quite helpful to the researchers in quantifying the specific measuring tools for these software quality attributes.

Identifying objects in legacy systems using design metrics

Existing software quality definition models often fall short in addressing the dynamic and evolving requirements of Healthcare Information Systems (HIS), particularly the unique regulatory and infrastructural challenges inherent to healthcare environments. This poster introduces the Healthcare Data Quality Language (HDQL), a novel framework designed to bridge the gap between HIS requirements and software quality attributes. HDQL enables healthcare professionals to intuitively define software features tailored to their needs, fostering improved system acceptance, enhanced performance, and system evolution.

Software architecture forms the cornerstone for achieving and ensuring various software quality attributes. It encompasses the collected requirements of the product, serving as a blueprint that delineates quality features for all project stakeholders, along with methods for measurement and control. Despite the significant increase in IoT-based agricultural systems, there is a dearth of studies on the quality elements of their software architecture. To address this need, this study offers an overview of components and services tailored to address specific quality attributes pertinent to agriculture systems. It identifies, investigates, and presents quality attributes influencing the design of software architecture for IoT-based agriculture systems. This paper identified and discussed several quality attributes, including performance, scalability, flexibility, interoperability, productivity, extensibility, and security, and mapped them to corresponding components of the IoT-based agriculture software architecture. Also, several issues were identified and discussed for the software architecture quality of IoT-based agriculture systems, such as real-time processing and interoperability due to the various devices and protocols utilized in these systems. The findings of this study offer valuable insights for developing, executing, and refining IoT-based agricultural systems to fulfill the changing requirements of the agriculture industry.

Software Quality Attributes (QAs) can be categorised as either internal to the system as experienced by the developers or external to the system perceived by the end users. These QA categories have trade-off among them - an emphasis on internal QA may result in a compromise of an external QA. For example, there is a trade-off between maintainability and performance. Model-driven development approaches manage this trade-off and increase the degree of internal QA maintainability. In this work, we propose an ontology-based communication mechanism among software components to handle the trade-off. The approach increases the degree of internal QAs such as modifiability, maintainability, testability during the design and development phases without compromising the external QAs for the end users during the operation phase. We also evaluate a prototype system to validate the proposed approach using Software Architecture Analysis Method (SAAM). It is also easier to integrate into the software development life cycle as compared to existing model-driven approaches.