Measuring perceived mutuality in close relationships: Validation of the Mutual Psychological Development Questionnaire.

In an initial validation study of the Mutual Psychological Development Questionnaire (MPDQ), a measure of perceived mutuality in close relationships, 345 respondents completed the scale for spouse or partner and friend relationships. Results indicated high interitem reliability. Construct and concurrent validity were demonstrated. MPDQ ratings were correlated with adequacy of social support, relationship satisfaction, and cohesion. Ratings correlated negatively with depression. Low spouse or partner mutuality was predictive of significant depressive symptoms in women but not in men. In a 2nd study, 81 respondents completed the scale at 2 time points. Test–retest reliability was satisfactory, and high interitem consistency was replicated. The substantive meaning of these findings, gender differences, and possible future research applications of the MPDQ are disscussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Empirical validation of referential integrity metrics

Databases are the core of Information Systems (IS). It is, therefore, necessary to ensure the quality of the databases in order to ensure the quality of the IS. Metrics are useful mechanisms for controlling database quality. This paper presents two metrics related to referential integrity, number of foreign keys (NFK) and depth of the referential tree (DRT) for controlling the quality of a relational database. However, to ascertain the practical utility of the metrics, experimental validation is necessary. This validation can be carried out through controlled experiments or through case studies. The controlled experiments must also be replicated in order to obtain firm conclusions. With this objective in mind, we have undertaken different empirical work with metrics for relational databases. As a part of this empirical work, we have conducted a case study with some metrics for relational databases and a controlled experiment with two metrics presented in this paper. The detailed experiment described in this paper is a replication of the later one. The experiment was replicated in order to confirm the results obtained from the first experiment.

As a result of all the experimental works, we can conclude that the NFK metric is a good indicator of relational database complexity. However, we cannot draw such firm conclusions regarding the DRT metric.     

Do software models based on the UML aid in source-code comprehensibility? Aggregating evidence from 12 controlled experiments

In this paper, we present the results of long-term research conducted in order to study the contribution made by software models based on the Unified Modeling Language (UML) to the comprehensibility of Java source-code deprived of comments. We have conducted 12 controlled experiments in different experimental contexts and on different sites with participants with different levels of expertise (i.e., Bachelor’s, Master’s, and PhD students and software practitioners from Italy and Spain). A total of 333 observations were obtained from these experiments. The UML models in our experiments were those produced in the analysis and design phases. The models produced in the analysis phase were created with the objective of abstracting the environment in which the software will work (i.e., the problem domain), while those produced in the design phase were created with the goal of abstracting implementation aspects of the software (i.e., the solution/application domain). Source-code comprehensibility was assessed with regard to correctness of understanding, time taken to accomplish the comprehension tasks, and efficiency as regards accomplishing those tasks. In order to study the global effect of UML models on source-code comprehensibility, we aggregated results from the individual experiments using a meta-analysis. We made every effort to account for the heterogeneity of our experiments when aggregating the results obtained from them. The overall results suggest that the use of UML models affects the comprehensibility of source-code, when it is deprived of comments. Indeed, models produced in the analysis phase might reduce source-code comprehensibility, while increasing the time taken to complete comprehension tasks. That is, browsing source code and this kind of models together negatively impacts on the time taken to complete comprehension tasks without having a positive effect on the comprehensibility of source code. One plausible justification for this is that the UML models produced in the analysis phase focus on the problem domain. That is, models produced in the analysis phase say nothing about source code and there should be no expectation that they would, in any way, be beneficial to comprehensibility. On the other hand, UML models produced in the design phase improve source-code comprehensibility. One possible justification for this result is that models produced in the design phase are more focused on implementation details. Therefore, although the participants had more material to read and browse, this additional effort was paid back in the form of an improved comprehension of source code.     

An industrial case study on the use of UML in software maintenance and its perceived benefits and hurdles

UML is a commonly-used graphical language for the modelling of software. Works regarding UML’s effectiveness have studied projects that develop software systems from scratch. Yet the maintenance of software consumes a large share of the overall time and effort required to develop software systems. This study, therefore, focuses on the use of UML in software maintenance. We wish to elicit the practices of the software modelling used during maintenance in industry and understand what are perceived as hurdles and benefits when using modelling. In order to achieve a high level of realism, we performed a case study in a multinational company’s ICT department. The analysis is based on 31 interviews with employees who work on software maintenance projects. The interviewees played different roles and provided complementary views about the use, hurdles and benefits of software modelling and the use of UML. Our study uncovered a broad range of modelling-related practices, which are presented in a theoretical framework that illustrates how these practices are linked to the specific goals and context of software engineering projects. We present a list of recommended practices that contribute to the increased effectiveness of software modelling. The use of software modelling notations (like UML) is considered beneficial for software maintenance, but needs to be tailored to its context. Various practices that contribute to the effective use of modelling are commonly overlooked, suggesting that a more conscious holistic approach with which to integrate modelling practices into the overall software engineering approach is required.     

Building measure-based prediction models for UML class diagram maintainability

The usefulness of measures for the analysis and design of object oriented (OO) software is increasingly being recognized in the field of software engineering research. In particular, recognition of the need for early indicators of external quality attributes is increasing. We investigate through experimentation whether a collection of UML class diagram measures could be good predictors of two main subcharacteristics of the maintainability of class diagrams: understandability and modifiability. Results obtained from a controlled experiment and a replica support the idea that useful prediction models for class diagrams understandability and modifiability can be built on the basis of early measures, in particular, measures that capture structural complexity through associations and generalizations. Moreover, these measures seem to be correlated with the subjective perception of the subjects about the complexity of the diagrams. This fact shows, to some extent, that the objective measures capture the same aspects as the subjective ones. However, despite our encouraging findings, further empirical studies, especially using data taken from real projects performed in industrial settings, are needed. Such further study will yield a comprehensive body of knowledge and experience about building prediction models for understandability and modifiability.

Table Oriented Metrics for Relational Databases

Developing and selecting high quality software applications are fundamental. It is important that the software applications can be evaluated for every relevant quality characteristic using validated metrics. Software engineers have been putting forward hundreds of quality metrics for software programs, disregarding databases. However, software data aspects are important because the size of data and their system nature contribute to many aspects of a systems quality. In this paper, we proposed some internal metrics to measure relational databases which influence its complexity. Considering the main characteristics of a relational table, we can propose the number of attributes (NA) of a table, the depth of the referential tree (DRT) of a table, and the referential degree (RD) of a table. These measures are characterized using measurement theory, particularly the formal framework proposed by Zuse. As many important issues faced by the software engineering community can only be addressed by experimentation, an experiment has been carried out in order to validate these metrics.     

Assessing the understandability of UML statechart diagrams with composite states—A family of empirical studies

The main goal of this work is to present a family of empirical studies that we have carried out to investigate whether the use of composite states may improve the understandability of UML statechart diagrams derived from class diagrams. Our hypotheses derive from conventional wisdom, which says that hierarchical modeling mechanisms are helpful in mastering the complexity of a software system. In our research, we have carried out three empirical studies, consisting of five experiments in total. The studies differed somewhat as regards the size of the UML statechart models, though their size and the complexity of the models were chosen so that they could be analyzed by the subjects within a limited time period. The studies also differed with respect to the type of subjects (students vs. professionals), the familiarity of the subjects with the domains of the diagrams, and other factors. To integrate the results obtained from each of the five experiments, we performed a meta-analysis study which allowed us to take into account the differences between studies and to obtain the overall effect that the use of composite states has on the understandability of UML statechart diagrams throughout all the experiments. The results obtained are not completely conclusive. They cast doubts on the usefulness of composite states for a better understanding and memorizing of UML statechart diagrams. Composite states seem only to be helpful for acquiring knowledge from the diagrams. At any rate, it should be noted that these results are affected by the previous experience of the subjects on modeling, as well as by the size and complexity of the UML statechart diagrams we used, so care should be taken when generalizing our results.     

Evaluating requirements modeling methods based on user perceptions: A family of experiments

Numerous methods and techniques have been proposed for requirements modeling, although very few have had widespread use in practice. One drawback of requirements modeling methods is that they lack proper empirical evaluations. This means that there is a need for evaluation methods that consider both the theoretical and practical aspects of this type of methods and techniques. In this paper, we present a method for evaluating the quality of requirements modeling methods based on user perceptions. The evaluation method consists of a theoretical model that explains the relevant dimensions of quality for requirements modeling methods, along with a practical instrument with which to measure these quality dimensions. Basically, it allows us to predict the acceptance of a particular requirements modeling method in practice, based on the effort of applying the method, the quality of the requirements artifacts produced, and the user perceptions with regard to the quality of the method. The paper also presents an empirical test of the proposed method for evaluating a Rational Unified Process (RUP) extension for requirements modeling. That test was carried out through a family of experiments conducted with students and practitioners and provides evidence of the usefulness of the evaluation method proposed.     

Assessing the influence of import-coupling on OCL expression maintainability: A cognitive theory-based perspective

The aim of this paper is to present the definition of the measures for the import-coupling of OCL expressions, along with the empirical validation of these as early indicators of the maintainability of OCL expressions. This empirical validation has been carried out by means of an experiment and its replica, conducted with undergraduate students of Spanish and Argentinean universities, respectively. To perform this experimental activity, we have followed a cognitive theory-based approach, since the understanding of the cognitive demands that OCL expressions place on software engineers will allow us to examine in greater depth the real influence of import-coupling on the maintainability of OCL expressions. The empirical results, obtained through the analysis of the data from the experiment and its replica, first of all separately and then together after a meta-analysis study, reveal evidence suggesting that import-coupling exerts a certain amount of influence on the comprehensibility and modifiability of OCL expressions. The measures that have most influence on OCL expression comprehensibility are those related to problem objects (Number of Navigated Relationships (NNR), Weighted Number of Navigations (WNN), Depth of Navigations (DN) and Number of Attributes referred through Navigations (NAN)), relationships between problem objects (Number of Navigated Classes (NNC) and Number of Explicit Iterator variables (NEI)), as well as reified objects (Weighted Number of Collections Operations (WNCO)). On the other hand, it is only measures related to relationships between problem objects that are the main influence on OCL expression modifiability. The influence of import-coupling on the comprehensibility and modifiability of OCL expressions was reaffirmed through the cognitive complexity (i.e. we show that import-coupling affects the cognitive complexity and that the latter influences the comprehension and modification of OCL expressions). These results may have educational implications, apart from what they might mean for practitioners in the industry, as is explained in the conclusions.