Models of motivation in software engineering

Motivation in software engineering is recognized as a key success factor for software projects, but although there are many papers written about motivation in software engineering, the field lacks a comprehensive overview of the area. In particular, several models of motivation have been proposed, but they either rely heavily on one particular model (the job characteristics model), or are quite disparate and difficult to combine. Using the results from our previous systematic literature review (SLR), we constructed a new model of motivation in software engineering. We then compared this new model with existing models and refined it based on this comparison. This paper summarises the SLR results, presents the important existing models found in the literature and explains the development of our new model of motivation in software engineering

The Impact of Feedback on the Motivation of Software Engineers

This research investigates how feedback affects the motivation of software engineers and develops a model of feedback in software engineering. Motivation has been reported as having an impact on software engineers’ productivity, the quality of the software they produce, the overall success of a software development project, and on the retention of software engineers. Findings from the last 30 years of research investigating motivation in software engineering have identified several factors that influence the motivation of software engineers, but the impact of each individual factor remains unclear. Feedback was identified as a factor affecting motivation by several studies investigating motivation in software engineering. Several theories of motivation exist which identify factors affecting motivation and models of how motivation is affected. Feedback is identified as a factor in four theories of motivation. In 2008 a systematic literature review identified that the majority of previous studies investigating motivation in software engineering were not grounded in motivation theory. This suggests that the majority of previous research investigating motivation in software engineering has not adequately considered theories of motivation and their relevance in software engineering. This research explored the importance of feedback and the effect of the characteristics of feedback on the motivation of software engineers, collecting their thoughts, perceptions, reflections and reactions to feedback using a range of different research methods. The research began with a preliminary study investigating how software engineers perceived feedback, and if the characteristics they identified were comparable to those identified in other disciplines, notably clinical education. Further studies followed by investigating feedback in software engineering, the short-term impact of received feedback, and the effect of the ‘source’ and ‘medium’ feedback characteristics. The findings of the preliminary study were that software engineers identified characteristics of feedback comparable to those found in clinical education, which gave a basis for further studies. Software engineers reported that feedback was the most common method of tracking their individual progress in a software project. A diary study collecting instances of feedback reported by software engineers found that positive feedback typically increased the engineers’ job satisfaction, and that negative feedback typically led to a change in their behaviour. Building on the earlier findings of this research, a scenario study and an online survey combining both scenarios and questions investigated the effect of the source and medium feedback characteristics. The findings of the four studies identified that the feedback recipient’s values and perceptions of the feedback source, and any preference they had to the medium used to send the feedback, affected the impact of received feedback. The findings suggested that the feedback software engineers report as the most valuable is not the same as feedback reported as having the most impact. The findings suggest that in software engineering, theories of motivation do not adequately consider the impact of the characteristics of feedback and the effect of different forms of feedback on motivation. A model of feedback in software engineering was identified by combining the findings of the four empirical studies and relevant literature. The model captures how feedback is experienced by software engineers. Software engineers perceive the characteristics of the received feedback, which provides information that is used to make several assessments about the feedback. Each engineer’s individual value set influences their assessments, and their current state of mind / mood / emotions affect the engineer’s perceptions, assessments, and individual value set. The assessments of the feedback then result in the impact of the received feedback, which can have an effect on the engineer’s attitude, behaviour, motivation, performance, job satisfaction, and feelings

End User Perception and Software Quality Assessment

The topic of software quality assessment is at the forefront of the software engineering movement. Many models of organization and quality control exist which serve to foster software quality and reliability (Bloom, McPheters & Tsiang, 1973; Brandl, 1990; Comer, 1988; Dunn, 1990; Kaplan, Clark & Tang, 1994; Livson, 1988; Musa, lannino & Okumoto, 1987). Some models now consider the software engineering project team and end users, but most still treat them as static contributors to the system. Major factors often ignored in most conventional models include the cybernetics of the process, and human factors which have a significant impact on the assessment of the quality of the software. Software environment, adaptability, and motivation have all been discussed as essential in creating a superior product. Yet, the factor of human perception has been either overlooked or avoided in the ensuing discussions. In software development the software engineers\u27 perceptions as well as those of all potential end users, must be considered in order to ensure software quality and reliability.End User Perception and Software Quality Assessmen

Maturity Models for Managing People in Software Development Teams: A Systematic Literature Review

Human factors are fundamental to software development, hence the need to understand people-oriented maturity models in development teams. This article aims to identify the maturity models for people management in software development teams cited in the literature, in order to identify evidence about their use, benefits and limitations, and the human aspects involved. A systematic literature review (SLR) was carried out, where automatic searches were done in four search engines, congresses in the area of ​​human factors within software engineering, in addition to a manual search. Evidence indicates that there are numerous models aimed at developing people in development teams, but few are applied. Models based on observation and informal discussion were found, as well as non-validated models, indicating the scarcity of models applicable to people in software engineering. However, complete but complex models were also found, indicating that a more transparent, dynamic and simple process is needed for people's development. In the observed human factors, emphasis is placed on communication, collaboration, knowledge, learning, self-management, motivation and skills in general. Keywords: Maturity models; Human Factors; Software Development Teams; Teams; People DOI: 10.7176/RHSS/12-14-02 Publication date:July 31st 202

Prompt Sapper: LLM-Empowered Software Engineering Infrastructure for AI-Native Services

Foundation models, such as GPT-4, DALL-E have brought unprecedented AI "operating system" effect and new forms of human-AI interaction, sparking a wave of innovation in AI-native services, where natural language prompts serve as executable "code" directly (prompt as executable code), eliminating the need for programming language as an intermediary and opening up the door to personal AI. Prompt Sapper has emerged in response, committed to support the development of AI-native services by AI chain engineering. It creates a large language model (LLM) empowered software engineering infrastructure for authoring AI chains through human-AI collaborative intelligence, unleashing the AI innovation potential of every individual, and forging a future where everyone can be a master of AI innovation. This article will introduce the R\&D motivation behind Prompt Sapper, along with its corresponding AI chain engineering methodology and technical practices

Analyzing Multi-Dimensional Programming in AOP and Composition Filters

In this paper, we investigate the meaning and impact of multi-dimensional construction of software, as exemplified by Aspect-Oriented Programming and Composition Filters. A simple application is introduced to illustrate the discussion topics. We conclude with a number of requirements for multidimensional programming. Lately, the software engineering field is increasingly becoming aware of the need for better modeling techniques to be able to design systems as compositions of independent concerns. Various models such as Adaptive [Mezini 98], AspectOriented Programming [Kiczales 97], Subject-Oriented Programming [Harrison 93] and Composition Filters [Aksit 88, 92, 94] have triggered and/or addressed these needs. In particular Aspect-Oriented Programming is gaining much interest recently. Previously, we have argued for extending AOP towards -- more generic-- mechanisms for multi-dimensional decomposition [Bergmans 96a]. The motivation behind this idea was that the concept of cross-c..

Report on the 2nd Workshop on Human Centric Software Engineering & Cyber Security (HCSE&CS 2021)

As the creators, designers, coders, testers, users, and occasional abusers of all software systems-including cyber security systems - humans should be at the centre of all design and development efforts. Despite this, most software engineering and cyber security research and practices tend to be function, data, or process oriented. In contrast, human-centric software engineering focuses on the human-centric issues critical to successful software systems' engineering. The aim of the International Workshop on Human Centric Software Engineering & Cyber Security (HCSE&CS) was to provide a venue for sharing research ideas and outcomes on enhanced theory, models, tools, and capability for next-generation human-centric software engineering and cyber security. The Second HCSE&CS Workshop was held on 15 November 2021 in conjunction with ASE 2021, the 36th IEEE/ACM International Conference on Automated Software Engineering. It was originally intended to be held in Melbourne, Australia but was instead held virtually due to the COVID-19 pandemic. This post-workshop report provides an overview of the aims and motivation of the workshop as well as a summary of the presentations and discussions that took place during the workshop

Implementing Bluebeam Software in Architectural Engineering Design Courses

A critical aspect of structural engineering education is helping students develop effective electronic graphical communication skills to convey their design solutions. Many undergraduate civil and architectural engineering programs address this at the document creation stage by teaching Autodesk AutoCAD or Revit to create 2-D or 3-D structural design files. However, students tend to have limited exposure to commercial software for document management and markup that allows for coordination between the engineer, architect, and contractor teams. Bluebeam Revu is one such software that has emerged as an industry standard for annotation and markup of engineering design documents. Previous educational studies on the use of Bluebeam have been in construction management courses where students practice plan reading. The main motivation for instructors to incorporate this software in their classes is to expose students to technology they will encounter as practitioners, especially significant since contractors view these drawings as a legal description of their scope of work. Therefore, the production and interpretation of the documents requires that they exhibit a high level of accuracy, specificity, and clarity. This paper focuses on the use of Bluebeam markup and grading in architectural engineering courses to enable communication between faculty and students during the iterative structural design process. The paper provides sample student hand calculations, sketches, and CAD structural drawings with Bluebeam markups provided by practitioner faculty. This markup describes and models how the student might implement necessary design changes. Feedback collected via interviews of course graders, surveys of students, and faculty co-authors is included and illustrates that the use of Bluebeam markup in architectural engineering courses provides a meaningful and efficient review during the development of a structural design solution. The goal of this paper is to show instructors how to integrate Bluebeam into a course, beyond plan reading activities. Faculty will thus be equipped to educate students on a software commonly used in structural design firms for quality assurance/quality control (QA/QC) and communication between the design and construction disciplines