An empirical investigation into contributory factors of change and fault propensity in large-scale commercial object-oriented software

This thesis was submitted for the degree of Doctor of Philosophy and was awarded by Brunel UniversityObject-Oriented design and development dominates both commercial and open source software projects. One of the principal goals of object-oriented design is to aid reuse, and hence, reduce future maintenance efforts of software systems. However, the on-going maintenance of large-scale software systems (both changes and faults) continues to be a significant proportion of the lifecycle of the system and the total investment cost. Understanding and thus being able to predict - or even reduce - the impact of the contributing factors of future maintenance efforts of a software system is thus highly beneficial to software practitioners. In this Thesis we empirically study a large, commercial software system with the principal aim to determine the contributing factors to the change and fault propensity over a three-year period. We consider the object-oriented design context of the software, specifically its inheritance characteristics, coupling and cohesion properties, object-oriented design pattern participation, and size. We also explore the effect of refactoring and test classes in the software. Our results show that several aspects of the design context of a class have an impact to the change and fault-proneness of the software. Specifically, we show that classes with high afferent or efferent coupling are more change and fault-prone; we also identify a number of design patterns whose participants tend to have a higher change and fault propensity than non-participants and we identify a range of inheritance characteristics (in terms of depth of inheritance and number of children) that result in an increase to change and fault-proneness. Furthermore we show that refactoring is a commonly occurring maintenance activity, although it is largely limited to simpler types of refactorings. Finally, we provide some insight into the co-evolution of production and test code during refactoring

A COUPLING AND COHESION METRICS SUITE FOR

The increasing need for software quality measurements has led to extensive research into software metrics and the development of software metric tools. To maintain high quality software, developers need to strive for a low-coupled and highly cohesive design. One of many properties considered when measuring coupling and cohesion is the type of relationships that made up coupling and cohesion. What these specific relationships are is widely understood and accepted by researchers and practitioners. However, different researchers base their metrics on a different subset of these relationships. Studies have shown that because of the inclusion of multiple subsets of relationships in one measure of coupling and cohesion metrics, the measures tend to correlate among each other. Validation of these metrics against maintainability index of a Java program suggested that there is high multicollinearity among coupling and cohesion metrics. This research introduces an approach of implementing coupling and cohesion metrics. Every possible relationship is considered and, for each, addressed the issue of whether or not it has significant effect on maintainability index prediction. Validation of orthogonality of the selected metrics is assessed by means of principal component analysis. The investigation suggested that some of the metrics are independent set of metrics, while some are measuring similar dimension

Class movement and re-location: An empirical study of Java inheritance evolution

This is the post-print version of the final paper published in Journal of Systems and Software. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2009 Elsevier B.V.Inheritance is a fundamental feature of the Object-Oriented (OO) paradigm. It is used to promote extensibility and reuse in OO systems. Understanding how systems evolve, and specifically, trends in the movement and re-location of classes in OO hierarchies can help us understand and predict future maintenance effort. In this paper, we explore how and where new classes were added as well as where existing classes were deleted or moved across inheritance hierarchies from multiple versions of four Java systems. We observed first, that in one of the studied systems the same set of classes was continuously moved across the inheritance hierarchy. Second, in the same system, the most frequent changes were restricted to just one sub-part of the overall system. Third, that a maximum of three levels may be a threshold when using inheritance in a system; beyond this level very little activity was observed, supporting earlier theories that, beyond three levels, complexity becomes overwhelming. We also found evidence of ‘collapsing’ hierarchies to bring classes up to shallower levels. Finally, we found that larger classes and highly coupled classes were more frequently moved than smaller and less coupled classes. Statistical evidence supported the view that larger classes and highly coupled classes were less cohesive than smaller classes and lowly coupled classes and were thus more suitable candidates for being moved (within an hierarchy)

Testability Assessment Model for Object Oriented Software based on Internal and External Quality Factors

Software testability is coming out to be most frequent talked about subject then the underrated and unpopular quality factor it used to be in past few years. The correct and timely assessment of testability can lead to improvisation of software testing process. Though many researchers and quality controllers have proved its importance, but still the research has not gained much momentum in emphasizing the need of making testability analysis necessary during all software development phases. In this paper we review and analyse the factors affecting testability estimation of object oriented software systems during design and analysis phase of development life cycle. These factors are then linked together in the form of new assessment model for object oriented software testability. The proposed model will be evaluated using analytical hierarchical process (AHP)

Intelligent Data-Driven Reverse Engineering of Software Design Patterns

Recognising implemented instances of Design Patterns (DPs) in software design discloses and recovers a wealth of information about the intention of the original designers and the rationale for their design decisions. Because it is often the case that the documentation available for software systems, if any, is poor and/or obsolete, recovering such information can be of great help and importance for maintenance tasks. However, since DPs are abstractly and vaguely defined, a set of software classes with exactly the same relationships as expected for a DP instance may actually be only accidentally similar. On the other hand, a set of classes with relationships that are, to an extent, different from those typically expected can still be a true DP instance. The deciding factor is mainly concerned with whether or not the set of classes is actually intended to solve the design problem addressed by the DP, thus making the intent a fundamental and defining characteristic of DPs. Discerning the intent of potential instances requires building complex models that cannot be built using only the descriptions of DPs in books and catalogues. Accordingly, a paradigm shift in DP recognition towards fully machine learning based approaches is required. The problem is that no accurate and sufficiently large DP datasets exist, and it is difficult to manually construct one. Moreover, there is a lack of research on the feature set that should be used in DP recognition. The main aim of this thesis is to enable the required paradigm shift by laying down an accurate, comprehensive and information-rich foundation of feature and data sets. In order to achieve this aim, a large set of features is developed to cover a wide range of design aspects, with particular focus on design intent. This set serves as a global feature set from which different subsets can be objectively selected for different DPs. A new and feasible approach to DP dataset construction is designed and used to construct training datasets. The feature and data sets are then used experimentally to build and train DP classifiers. The results demonstrate the accuracy and utility of the sets introduced, and show that fully machine learning based approaches are capable of providing appropriate and well-equipped solutions for the problem of DP recognition.Saudi Cultural Burea

An empirical investigation of inheritance trends in JAVA OSS evolution

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Inheritance is a salient feature of Object-Oriented (OO) paradigm which facilitates reuse and improves system comprehensibility in OO systems. The overall aim of inheritance is to model classes in a structured hierarchy where classes residing lower in the hierarchy (subclasses) can inherit the pre-existing functionality in the classes located higher up (superclasses) in the same line of hierarchy. Software maintenance and evolution are the process of making any modifications to a software system and upgrading its dynamic behaviour. In this Thesis, we empirically investigate the trends of evolution of eight Java Open-Source Systems (OSS) from an inheritance perspective and model the propensity for changes of inheritance in those systems. The systems used as testbed in this Thesis represent a variety of application domains with varying sizes and amount of inheritance employed. There are several levels of granularity for inheritance evolution that may manifest a particular trend. This starts from the highest level (package) to lower class, method an attribute levels; and each level may show a different and yet an important pattern of evolution. We empirically investigate the changes of inheritance in the form of increases (additions) and decreases (deletions) in number of classes, methods and attributes. Our analysis also includes the movement of classes within and across an inheritance hierarchy which is another compelling facet of evolution of inheritance and may not be extrapolated through incremental changes only. It requires a finer-grained scrutiny of evolutionary traits of inheritance. In addition, the Thesis also explores the trends of class interaction within and across an inheritance hierarchy and problems embedded in a system that may lead to faults, from an inheritance perspective. The results demonstrate how inheritance is used in practice, problems associated with inheritance and how inheritance hierarchies evolve as opposed to that of a ‘system’. Overall results informed our understanding of the trends in changes of inheritance in the evolution of Java systems

Software metric for Java and C++ practices (Workpackage 1.1)

The objective of this deliverable is to define a catalog of software met- rics. In particular we analyze the metrics used in the Squale Model and tool. In addition it offers a coherent set of software metrics for object-oriented languages on top of which Squale practices will be based. There is a plethora of software metrics and a large amount of research articles. Still there is a lack for a serious and practically-oriented evaluation of metrics. Often metrics lacks the property that the software reengineer or quality expert can easily understand the situation summa- rized by the metrics. In particular since the exact notion of coupling and cohesion is complex, a particular focus on such point is important