Factors In Software Engineering Research Articles

Perceived Technology Acceptance and Software Engineering Factors Towards Intention to Use Web-based Health Information Service (WBHIS)

The article investigates the intentional use of a Web-based Health Information Service (WBHIS) through multi-factors influencing the use of a national, MyHEALTH Portal (MHP). The study utilised an online web-survey incorporates three interrelated aspects of investigation; acceptance influence, socio-cognitive, and software engineering factors (user interface and data quality), to investigate deeper on Malaysian health consumers’ intent to adopt the portal. Findings have shown health consumers’ intention to use MHP is positively influenced by the positive behavioural attitude of health consumers’ towards the portal. The study also supported the significant role played by software engineering factors; user interface design and data quality towards health consumers’ attitude of the portal. The results would assist Malaysia Health Education Division in gaining better insights into the design of a well-accepted WBHIS where specifically, the findings would improve the presence and functions of the MHP. This effort is evidently significant in helping the country to reach the 11th Malaysia Plan through its strategy to encourage health awareness and healthy lifestyle activities among its citizens.

A Quantitative Assessment of the Impact of Homogeneity in Personality Traits on Software Quality and Team Productivity

Software industry is increasingly focusing on the improvement of software quality and team performance to survive in a competitive and rapidly growing environment. Previous studies reveal the importance of social and human factors in software engineering. Despite the importance of these personality factors, only a handful of empirical studies have quantitatively evaluated the impact of personality traits on software quality and effectiveness of software engineering teams. This study quantifies the abstract notion of trait-wise team homogeneity based on the Five-Factor Model (FFM). Additionally, this study also aims to measure its impact on team productivity and software quality. Trait-wise team homogeneity measures the Team Homogeneity Index (THI) for each of the five personality traits of FFM. Therefore, five new metrics i.e. Openness THI (O-THI), Conscientiousness THI (C-THI), Extraversion THI (E-THI), Agreeableness THI (A-THI), and Neuroticism THI (N-THI) are proposed. The utility of these five metrics is evaluated by conducting experiments in academic and industrial environments for three different phases of the Software Development Life Cycle (SDLC) i.e. analysis and design, implementation, and testing. During the analysis and design phase, it was observed that teams (composed of either students or professionals) with greater values of C-THI and A-THI produced better quality design models and teams with greater values of C-THI were more productive. In the implementation phase, teams with higher values of O-THI, C-THI, and E-THI were noticeably more productive and produced better quality code. For the testing phase, teams with greater values of C-THI and A-THI produced better quality test cases and were more productive. Results obtained so far indicate that the newly proposed five metrics – O-THI, C-THI, E-THI, A-THI, and N-THI – appear to have the potential to aid managers and academics alike in building productive teams which can produce better quality software.

The effects of applying filters on EEG signals for classifying developers’ code comprehension

EEG signals are a relevant indicator for measuring aspects related to human factors in Software Engineering. EEG is used in software engineering to train machine learning techniques for a wide range of applications, including classifying task difficulty, and developers’ level of experience. The EEG signal contains noise such as abnormal readings, electrical interference, and eye movements, which are usually not of interest to the analysis, and therefore contribute to the lack of precision of the machine learning techniques. However, research in software engineering has not evidenced the effectiveness when applying these filters on EEG signals. The objective of this work is to analyze the effectiveness of filters on EEG signals in the software engineering context. As literature did not focus on the classification of developers’ code comprehension, this study focuses on the analysis of the effectiveness of applying EEG filters for training a machine learning technique to classify developers' code comprehension. A Random Forest (RF) machine learning technique was trained with filtered EEG signals to classify the developers' code comprehension. This study also trained another random forest classifier with unfiltered EEG data. Both models were trained using 10-fold cross-validation. This work measures the classifiers' effectiveness using the f-measure metric. This work used the t-test, Wilcoxon, and U Mann Whitney to analyze the difference in the effectiveness measures (f-measure) between the classifier trained with filtered EEG and the classifier trained with unfiltered EEG. The tests pointed out that there is a significant difference after applying EEG filters to classify developers' code comprehension with the random forest classifier. The conclusion is that the use of EEG filters significantly improves the effectivity to classify code comprehension using the random forest technique.

A large-scale, in-depth analysis of developers’ personalities in the Apache ecosystem

Context: Large-scale distributed projects are typically the results of collective efforts performed by multiple developers with heterogeneous personalities. Objective: We aim to find evidence that personalities can explain developers' behavior in large scale-distributed projects. For example, the propensity to trust others - a critical factor for the success of global software engineering - has been found to influence positively the result of code reviews in distributed projects. Method: In this paper, we perform a quantitative analysis of ecosystem-level data from the code commits and email messages contributed by the developers working on the Apache Software Foundation (ASF) projects, as representative of large scale-distributed projects. Results: We find that there are three common types of personality profiles among Apache developers, characterized in particular by their level of Agreeableness and Neuroticism. We also confirm that developers' personality is stable over time. Moreover, personality traits do not vary with their role, membership, and extent of contribution to the projects. We also find evidence that more open developers are more likely to make contributors to Apache projects. Conclusion: Overall, our findings reinforce the need for future studies on human factors in software engineering to use psychometric tools to control for differences in developers' personalities.

The Human Factor

This installment reports on five papers from the 39th International Conference on Software Engineering and its collocated events. These papers focus on human factors in software engineering, with the last three dealing with open source software.

3LRM-3 Layer Risk Mitigation Modelling of ICT Software Development Projects

With the adoption of new technology and quality standards, the software development firms are still encountering the critical issues of risk modelling. With the changing dynamics of customer needs, potential competition has being mushrooming in the global IT markets to relay a new standard of software engineering which has higher capability of sustaining risk. However, till date, it is still theoretical to large extent from research viewpoint. Hence, this paper presents a mathematical model called as 3LRM that is designed with the simple approach keeping in mind the real-time issues of risk factors in software engineering for ICT software development project. The study has also identified requirement volatility as one of the prominent source of risk and hence, the framework intends to identify a risk as well as mitigating the risk to a large extent. The paper is illustrated with some of the simple statistical approaches of random probability.

3LRM-3 Layer Risk Mitigation Modelling of ICT Software Development Projects

With the adoption of new technology and quality standards, the software development firms are still encountering the critical issues of risk modelling. With the changing dynamics of customer needs, potential competition has being mushrooming in the global IT markets to relay a new standard of software engineering which has higher capability of sustaining risk. However, till date, it is still theoretical to large extent from research viewpoint. Hence, this paper presents a mathematical model called as 3LRM that is designed with the simple approach keeping in mind the real-time issues of risk factors in software engineering for ICT software development project. The study has also identified requirement volatility as one of the prominent source of risk and hence, the framework intends to identify a risk as well as mitigating the risk to a large extent. The paper is illustrated with some of the simple statistical approaches of random probability.

Confounding parameters on program comprehension: a literature survey

Program comprehension is an important human factor in software engineering. To measure and evaluate program comprehension, researchers typically conduct experiments. However, designing experiments requires considerable effort, because confounding parameters need to be controlled for. Our aim is to support researchers in identifying relevant confounding parameters and select appropriate techniques to control their influence. To this end, we conducted a literature survey of 13 journals and conferences over a time span of 10 years. As result, we created a catalog of 39 confounding parameters, including an overview of measurement and control techniques. With the catalog, we give experimenters a tool to design reliable and valid experiments.

Team building criteria in software projects: A mix-method replicated study

ContextThe internal composition of a work team is an important antecedent of team performance and the criteria used to select team members play an important role in determining team composition. However, there are only a handful of empirical studies about the use of team building criteria in the software industry. ObjectiveThe goal of this article is to identify criteria used in industrial practice to select members of a software project team, and to look for relationships between the use of these criteria and project success. In addition, we expect to contribute with findings about the use of replication in empirical studies involving human factors in software engineering. MethodOur research was based on an iterative mix-method, replication strategy. In the first iteration, we used qualitative research to identify team-building criteria interviewing software project managers from industry. Then, we performed a cross-sectional survey to assess the correlations of the use of these criteria and project success. In the second iteration, we used the results of a systematic mapping study to complement the set of team building criteria. Finally, we performed a replication of the survey research with variations to verify and improve the results. ResultsOur results showed that the consistent use team building criteria correlated significantly with project success, and the criteria related to human factors, such as personality and behavior, presented the strongest correlations. The results of the replication did not reproduce the results of the original survey with respect to the correlations between criteria and success goals. Nevertheless, the variations in the design and the difference in the sample of projects allowed us to conclude that the two results were compatible, increasing our confidence on the existence of the correlations. ConclusionOur findings indicated that carefully selecting team member for software teams is likely to positively influence the projects in which these teams participate. Besides, it seems that the type of development method used can moderate (increase or decrease) this influence. In addition, our study showed that the choice of sampling technique is not straightforward given the many interacting factors affecting this type of investigation.

Evolution of software engineers' personality profile

The Myers-Briggs Type Indicator (MBTI) has been applied to several studies that explore various dimensions of human factors in software engineering. Accordingly, this work reviews the results of these studies to explore existing trends. In order to attain a greater understanding of human resources in the software industry, we have reviewed sixteen studies that had been performed between 1985 and 2011. This review concludes that the changes in the complexity of software processes and products have created new roles and demanded new skills for software engineers.

Trustworthy systems through quantitative software engineering

Trustworthy systems through quantitative software engineering

Human and social factors of software engineering

Software is developed for people and by people. Human and social factors have a very strong impact on the success of software development endeavours and the resulting system. Surprisingly, much of software engineering research in the last decade is technical, quantitative and deemphasizes the people aspect. The workshop on Human and Social Factors in Software Engineering has been picking up on the some of the soft aspects in software development that was highlighted in the early days of software engineering. It also follows a recent trend in the software industry, namely the introduction of agile methods, and provides a scientific perspective on these. Including and combining approaches of software engineering with social science, the workshop looked at software engineering from a number of perspectives, including those of agile methods and communication theory, in order to point out solutions and conditions for human-centred software engineering.

Software Engineering for Portability

AbstractEducational software portability is discussed from a variety of historical and technical perspectives, including the need to devise a procedure to measure the portability of a product and how the roles of different specialists contributing to design teams can be better focused on appropriate portability considerations. The phases of educational software design are also analyzed relative to enhancing the subsequent portability of the product. Software engineering factors related to portability—such as factors related to the student-computer interface, authoring, and choice of design model—are also discussed. The article concludes with four suggestions for further research within the context of software engineering and educational software portability.

Human factors in software engineering: A review of the literature

A critical factor in the increased utilization of computer technology is the availability of software. Techniques must be developed to reduce the effort required to develop and maintain software and the availability of software developers must be increased. Both of these approaches could benefit from significant input from the human factors engineering community. Where should our efforts be focused? This paper will: 1. (1) provide a framework for studying human factors in software engineering; 2. (2) summarize the literature on human factors in software engineering; and 3. (3) identify some research areas that should be addressed.

Human Factors in Software Engineering

Software engineering is an effort to reduce the cost of producing software by raising programming productivity and lowering maintenance effort and to increase the benefits of software by extending application areas and improving service. Human factors considerations can have a major impact on the software development process and the quality of the software produced. High-level languages have increased programmer productivity by removing from the programmer the burden of remembering what values are in what register and placing it on a software system which is much more suited to managing detail. Other programming methodologies and tools have been developed to reduce the cost of producing software: design methodologies, structured programming, chief programmer teams, disciplined coding conventions, etc. The efficacy of these software aids has been demonstrated mostly by case studies. The articles in this issue of Computer analyze some of these methodologies and tools from a human factors viewpoint, using the tools of human factors engineering to determine if the use of a particular aid increases programming performance or the quality of the resulting software.