Object-oriented cohesion as a surrogate of software comprehension: An empirical study

The concept of software cohesion in both the procedural and object-oriented paradigm is well known and documented. What is not so well known or documented is the perception of what empirically constitutes a cohesive 'unit' by software engineers. In this paper, we describe an empirical investigation using object-oriented (OO) classes as a basis. Twenty-four subjects (drawn from IT experienced and IT inexperienced groups) were asked to rate ten classes sampled from two industrial systems in terms of their overall cohesiveness; a class environment was used to carry out the study. Four key results were observed. Firstly, class size (when expressed in terms of number of methods) did not tend to influence the perception of cohesion by any subjects. Secondly, well-commented classes were rated most highly amongst both IT experienced and inexperienced subjects. Thirdly, the empirical study suggests that cohesion comprises a combination of various class factors including low coupling, small numbers of attributes and well-commented methods, rather than any single, individual class feature per se. Finally, the research supports the view that cohesion is a subjective concept reflecting a cognitive combination of class features; as such it is a surrogate for class comprehension

Intelligent software quality model: The theoretical framework

Globally, software quality issues has increasingly been seen as a common strategic response for achieving competitiveness in business.It has been seen very important as the usage of software become very demanding.Software quality includes quality control tests, quality assurance and quality management.Currently, software quality models available were built based on static measurements of attributes and measures.Previous study has indicated that to ensure the quality of software meets the future requirements and needs, the new dynamic and intelligent software quality model has to be developed.This paper discusses the development of intelligent software quality model based on behavioral and human perspectives approach which enhances from Pragmatic Quality Factor (PQF) model as a benchmark of the quality assessment

Analyzing the Importance of Learnability and Understandability Quality Attributes in Reference to SPL Feature Models

The modeling foundation of SPL is promoting software reuse by segregation of variant features of all the products whi ch belong to a family. The analysis of various quality attribute s is very important in reference to SPL feature models. Identifying whether a feature model is easy to use and learn will help develop a successful product line. Two important quality sub factors of usability i.e. understandability and communicativeness play a great role in development of successful product line feature model. If the understanding of any feature model is low, it will result in lesser use of that feature model. Same applies to communicativeness , the more the communicativeness of a feature model, the more the usability. In other words, the successful reuse of any feature model will depend on the degree of its understa nding and communicativeness. C urrent analysis methods usually focus only on functional requirements of the product lines and do not focus on product quality. Whereas, non functional requirement s like maintainability, dependability and usability etc are essential dimensions of variability. This paper is intended to study the role of understandability and communicativeness over feature models. It also throws light on t he effect of these quality su b factors on SPL feature models and suggests ways to improve their degr

An Empirical Validation of Object-Oriented Design Metrics for Fault Prediction

Object-oriented design has become a dominant method in software industry and many design metrics of object-oriented programs have been proposed for quality prediction, but there is no well-accepted statement on how significant those metrics are. In this study, empirical analysis is carried out to validate object-oriented design metrics for defects estimation. Approach: The Chidamber and Kemerer metrics suite is adopted to estimate the number of defects in the programs, which are extracted from a public NASA data set. The techniques involved are statistical analysis and neuro-fuzzy approach. Results: The results indicate that SLOC, WMC, CBO and RFC are reliable metrics for defect estimation. Overall, SLOC imposes most significant impact on the number of defects. Conclusions/Recommendations: The design metrics are closely related to the number of defects in OO classes, but we can not jump to a conclusion by using one analysis technique. We recommend using neuro-fuzzy approach together with statistical techniques to reveal the relationship between metrics and dependent variables, and the correlations among those metrics also have to be considered

Environmental Modeling Framework Invasiveness: Analysis and Implications

Environmental modeling frameworks support scientific model development by providing an Application Programming Interface (API) which model developers use to implement models. This paper presents results of an investigation on the framework invasiveness of environmental modeling frameworks. Invasiveness is defined as the quantity of dependencies between model code and the modeling framework. This research investigates relationships between invasiveness and the quality of modeling code. Additionally, we investigate the relationship between invasiveness and two common framework designs (lightweight vs. heavyweight). Five metrics to measure framework invasiveness were proposed and applied to measure invasiveness between model and framework code of several implementations of Thornthwaite and the Precipitation-Runoff Modeling System (PRMS), two hydrological models. Framework invasiveness measurements were compared with existing software metrics including size (lines of code), cyclomatic complexity, and object-oriented coupling with generally positive correlations being found. We found that models with lower framework invasiveness tended to be smaller, less complex, and have lower coupling. In addition, the lightweight framework implementations of the Thornthwaite and PRMS models were less invasive than the heavyweight framework model implementations. Our initial results suggest that framework invasiveness is undesirable for model code quality and that lightweight frameworks may help reduce invasiveness

An Exploratory Investigation on the Invasiveness of Environmental Modeling Frameworks

Environmental modeling frameworks provide an array of useful features that model developers can harness when implementing models. Each framework differs in how it provides features to a model developer via its Application Programming Interface (API). Environmental modelers harness framework features by calling and interfacing with the framework API. As modelers write model code, they make framework-specific function calls and use framework specific data types for achieving the functionality of the model. As a result of this development approach, model code becomes coupled with and dependent on a specific modeling framework. Coupling to a specific framework makes migration to other frameworks and reuse of the code outside the original framework more difficult. This complicates collaboration between model developers wishing to share model code that ma y have been developed in a variety of languages and frameworks. This paper provides initial results of an exploratory investigation on the invasiveness of environmental modeling frameworks. Invasiveness is defined as th e coupling between application (i.e., model) and framework code used to implement the model. By comparing the implementation of an environmental model across several modeling frameworks, we aim to better understand the consequences of framework design. How frameworks present functionality to modelers through APIs can lead to consequences with respect to model development, model maintenance, reuse of model code, and ultimately collaboration among model developers. By measuring framework invasiveness, we hope to provide environmental modeling framework developers and environmental modelers with valuable in formation to assist in future development efforts. Eight implementations (six framework-based) of Thornthwaite, a simple water balance model, were made in a variety of environmental modeling frameworks and languages. A set of software metrics were proposed and applied to measure invasiveness between model implementation code and framework code. The metrics produced a rank ordering of invasiveness for the framework-based implementations of Thornthwaite. We compared model invasiveness results with several popular software metrics including size in lines of code (LOC), cyclomatic complexity, and object oriented coupling. To investigate software quality implications of framework invasiveness we checked for relationships between the Chidamber and Kemerer (1994) object oriented software metrics and our framework invasiveness measures. For the six framework-based implementations of Thornthwaite we found a five-fold variation in code size (LOC). We observed up to a seven-fold variation in total cyclomatic complexity, and a two to three-fold variation in object oriented coupling. For the model implementations we found that total size, total complexity, and total coupling all had a significant positive correlation. The raw count version of our invasiveness measures correlated with application size (LOC), total cyclomatic complexity, total efferent coupling (fan out) and total afferent coupling (fan in). Large size, complexity, and high levels of coupling between units (classes, modules) in a software system are often cited in software engineering as causes of high maintenance costs due to poor understandability and flexibility of the code. This study provides initial results but further investigation is desired to evaluate the utility of our invasiveness measurement approach as well as the software quality implications of framework invasiveness