Software Process Improvement Research Articles

Contributions to Systems Software and Service Process Improvement and Innovation Based on Recent Advances

Contributions to Systems Software and Service Process Improvement and Innovation Based on Recent Advances

Metrics for software process simulation modeling

AbstractSoftware process simulation (SPS) has become an effective tool for software process management and improvement. However, its adoption in industry is less than what the research community expected due to the burden of measurement cost and the high demand for domain knowledge. The difficulty of extracting appropriate metrics with real data from process enactment is one of the great challenges. We aim to provide evidence‐based support of the process metrics for software process (simulation) modeling. A systematic literature review was performed by extending our previous review series to draw a comprehensive understanding of the metrics for process modeling following our proposed ontology of metrics in SPS. We identify 131 process modeling studies that collectively involve 1975 raw metrics and classified them into 21 categories using the coding technique. We found product and process external metrics are not used frequently in SPS modeling while resource external metrics are widely used. We analyze the causal relationships between metrics. We find that the models exhibit significant diversity, as no pairwise relationship between metrics accounts for more than 10% SPS models. We identify 17 data issues may encounter in measurement and 10 coping strategies. The results of this study provide process modelers with an evidence‐based reference of the identification and the use of metrics in SPS modeling and further contribute to the development of the body of knowledge on software metrics in the context of process modeling. Furthermore, this study is not limited to process simulation but can be extended to software process modeling, in general. Taking simulation metrics as standards and references can further motivate and guide software developers to improve the collection, governance, and application of process data in practice.

Promoting social and human factors through a gamified automotive software development environment

AbstractGamification is an attractive strategy for different contexts, including software process improvement, where it presents positive results associated with increased factors such as motivation and others classified into social and human factors. Such factors are required to improve software processes in the automotive industry due to the influence of changes in the conditions and the behavior of individuals. However, the treatment of gamification strategies requires rigor at a scientific level. Therefore, it is necessary to analyze critical dimensions such as the gamification maturity level, the ability to intervene, and the influence of social and human factors. Such analysis is motivated by the relationship between social and human factors and the success of a process improvement. The above justifies the researchers' interest in this article in analyzing a gamification strategy implemented in the automotive industry from such dimensions. Therefore, this article presents the analysis from the point of view of developing software‐controlled systems in automobiles. Besides, it uses a deductive approach to conduct this analysis to abstract all the design aspects of a strategy created and implemented in a software development automotive environment. One of the most representative findings of this study is the strategy's capacity to promote SHF, which identifies motivation, commitment, team cohesion, emotional intelligence, and autonomy.

Trustworthy and collaborative traceability management: Experts’ feedback on a blockchain‐enabled framework

AbstractBlockchain technology has attracted significant attention in both academia and industry. Recently, the application of blockchain has been advocated in software engineering. The global software engineering paradigm exacerbates trust issues, as distributed and cross‐organizational teams need to share software artifacts. In such a context, there is a need for a decentralized yet reliable traceability knowledge base to keep track of what/how/when/by whom software artifacts were created or changed. This study presents a blockchain‐enabled framework for trustworthy and collaborative traceability management and identifies benefits, challenges, and potential improvements based on the feedback of software engineering experts. A qualitative approach was followed in this study through semistructured interviews with software engineering (SE) experts. Transcripts were analyzed by applying the content analysis technique. The results indicated the emergence of five categories, further grouped into three main categories: experts' perceptions, blockchain‐based software process improvement, and experts' recommendations. In addition, the findings suggested four archetypes of organizations that may be interested in blockchain technology: distributed organizations, organizations with contract‐based projects, organizations in regulated domains, and regulators who may push the use of this technology. Further efforts should be devoted to the integration of the proposal with tools used throughout the software development lifecycle and leveraging the potential of smart contracts in validating the implementation of requirements automatically.

Analysis of the use of software process improvement models in agile development

Analysis of the use of software process improvement models in agile development

Comparative Analysis of Software Process Improvement Models

This paper presents a comprehensive comparative analysis of four leading process improvement models: CMMI, ISO, Lean and Six Sigma. The objective is to evaluate and compare these models to determine their effectiveness in optimizing organizational processes. Using a qualitative method of analysis, the study breaks down each model based on standardized criteria, including complexity of implementation, performance metrics, and applicability across industries. The results highlight the unique strengths and limitations of each model and provide a nuanced understanding of their operational impact. The study provides a detailed guide for organizations to select an appropriate model tailored to their specific process improvement needs

Software Process Improvement by Managing Situational Method Engineering Knowledge

Organizational processes have been recognized as valuable knowledge assets. Situational Method Engineering (SME) processes are particularly valuable as they are used for engineering other processes: SME processes help construct bespoke Software Development Methodologies (SDMs) for specific software-engineering project situations. Every SDM has a Software Development Process (SDP) at its heart, which specifies the activities that should be performed throughout the project, the products that should be produced, and the people that should be involved. Existing SME methods suffer from certain weaknesses that are rooted in loss of knowledge within their processes; for instance, the method engineers' experience, which is a kind of tacit knowledge, is not properly captured and utilized in these processes. Managing SME process knowledge helps alleviate these weaknesses through reusing the software developers' experience and maintaining the method engineers' knowledge. We propose an evaluation framework that can be used for assessing an SME method's ability to manage process knowledge. We also provide a model that guides the improvement of existing SME methods in their support for Knowledge Management (KM), and also helps engineer new SME methods that provide adequate KM support. We have assessed the applicability of the proposed evaluation framework and improvement model by using them to enhance eight prominent SME methods, and also by applying them to four industrial case studies.

Success Factors for Conducting Software-Process Improvement in Web-Based Software Projects

Abstract Continuous Software Process Improvement (SPI) is essential for achieving and maintaining high-quality software products. Web-based software enterprises, comprising a substantial proportion of global businesses and forming a cornerstone of the world’s industrial economy, are actively pursuing SPI initiatives. While these companies recognize the critical role of process enhancement in achieving success, they face challenges in implementing SPI due to the distinctive characteristics of Web-based software projects. This study aims to identify, validate, and prioritize the sustainability success factors that positively influence SPI implementation efforts in Web-based software projects. Data have been meticulously gathered through a systematic literature review and quantitatively through a survey questionnaire. The findings of this research empower Web-based software enterprises to refine their management strategies for evaluating and bolstering SPI practices within the Web-based software projects domain.

Modeling software processes from different domains using SPEM and BPMN notations: An experience report of teaching software processes

In a current application development scenario in different environments, technologies and contexts, such as IoT, Blockchain, Machine Learning and Cloud Computing, there is a need for particular solutions for domain-specific software development processes. The proper definition of software processes requires the understanding for the involved teams and organization’s particularities and specialized technical knowledge in Software Engineering. Although it is an essential part of Software Engineering, many university curricula do not dedicate as much effort to teaching software processes, focusing more on the basic principles of Software Engineering, such as requirements, architecture and programming languages. Another important aspect of software processes is modeling. The modeling of a software process provides a basis for managing, automating and supporting the software process improvement. In this context, teaching software process modeling becomes challenging, mainly due to the great emphasis on theory and few practices. This work presents an experience report teaching the definition and modeling of software processes in different domains. In the discipline of software processes, we applied a practice for defining and modeling processes in various application domains, such as: IoT, cloud, mobile, critical systems, self-adaptive systems, machine learning, blockchain and games. The processes were modeled in the Software Systems Process Engineering Metamodel (SPEM) and Business Process Model and Notation (BPMN) notations based on references from the literature for each domain. We evaluated the process modeling practice with the SPEM and BPMN in two classes of the software processes discipline, and we had discussions about the use of the two notations applied to the different domains. In general, students reported good experiences in defining processes, highlighting the importance of practical modeling applications for professional life. As the main results of the study in teaching process modeling, we have that: (i) students accepted HEFLO tool better than EPF Composer tool; (ii) most students are not aware of specific domains and that anticipating the study of these domains in the discipline is a good strategy; and, (iii) the students also highlighted the need for more support for the two notation tools.

Trustworthy artificial intelligence: A decision‐making taxonomy of potential challenges

AbstractThe significance of artificial intelligence (AI) trustworthiness lies in its potential impacts on society. AI revolutionizes various industries and improves social life, but it also brings ethical harm. However, the challenging factors of AI trustworthiness are still being debated. This research explores the challenging factors and their priorities to be considered in the software process improvement (SPI) manifesto for developing a trustworthy AI system. The multivocal literature review (MLR) and questionnaire‐based survey approaches are used to identify the challenging factors from state‐of‐the‐art literature and industry. Prioritization based taxonomy of the challenges is developed, which reveals that lack of responsible and accountable ethical AI leaders, lack of ethics audits, moral deskilling & debility, lack of inclusivity in AI multistakeholder governance, and lack of scale training programs to sensitize the workforce on ethical issues are the top‐ranked challenging factors to be considered in SPI manifesto. This study's findings suggest revising AI‐based development techniques and strategies, particularly focusing on trustworthiness. In addition, the results of this study encourage further research to support the development and quality assessment of ethics‐aware AI systems.

The importance of theory at the Information Systems Journal

The importance of theory at the <i>Information Systems Journal</i>

Global challenges reflected in software process improvement

AbstractThis special issue comprises a selected set of high‐quality and extended articles of the 28th Systems, Software and Services Process Improvement (EuroSPI) Conference, held in 2021 in Krems, Austria.Conferences were held in Dublin (Ireland) in 1994, in Vienna (Austria) in 1995, in Brighton (UK) in 1996, in Budapest (Hungary) in 1997, in Gothenburg (Sweden) in 1998, in Pori (Finland) in 1999, in Copenhagen (Denmark) in 2000, in Limerick (Ireland) in 2001, in Nuremberg (Germany) in 2002, in Graz (Austria) in 2003, in Trondheim (Norway) in 2004, in Budapest (Hungary) in 2005, in Joensuu (Finland) in 2006, in Potsdam (Germany) in 2007, in Dublin (Ireland) in 2008, in Alcala (Spain) in 2009, in Grenoble (France) in 2010, in Roskilde (Denmark) in 2011, in Vienna (Austria) in 2012, in Dundalk (Ireland) in 2013, in Luxembourg in 2014, in Ankara (Turkey) in 2015, in Graz (Austria) in 2016, in Ostrava (Czech Republic) in 2017, in Bilbao (Spain) in 2018, in Edinburgh (UK) in 2019, in Düsseldorf (Germany) in 2020, and in Krems (Austria) in 2021.

Investigating acceptance behavior in software engineering—Theoretical perspectives

Background:Software engineering research aims to establish software development practice on a scientific basis. However, the evidence of the efficacy of technology is insufficient to ensure its uptake in industry. In the absence of a theoretical frame of reference, we mainly rely on best practices and expert judgment from industry-academia collaboration and software process improvement research to improve the acceptance of the proposed technology. Objective:To identify acceptance models and theories and discuss their applicability in the research of acceptance behavior related to software development. Method:We analyzed literature reviews within an interdisciplinary team to identify models and theories relevant to software engineering research. We further discuss acceptance behavior from the human information processing perspective of automatic and affect-driven processes (“fast” system 1 thinking) and rational and rule-governed processes (“slow” system 2 thinking). Results:We identified 30 potentially relevant models and theories. Several of them have been used in researching acceptance behavior in contexts related to software development, but few have been validated in such contexts.They use constructs that capture aspects of (automatic) system 1 and (rational) system 2 oriented processes. However, their operationalizations focus on system 2 oriented processes indicating a rational view of behavior, thus overlooking important psychological processes underpinning behavior. Conclusions:Software engineering research may use acceptance behavior models and theories more extensively to understand and predict practice adoption in the industry. Such theoretical foundations will help improve the impact of software engineering research. However, more consideration should be given to their validation, overlap, construct operationalization, and employed data collection mechanisms when using these models and theories.

A Novel model to adapt CMMI Level 2 by Assessing the Local SMEs of Bangladesh

While software process improvement (SPI) aims at optimizing software processes to produce high-quality software, SPI efforts in software development are still inert in practice, especially in developing countries. In this work, we make an experimental investigation aiming at developing a model for applying SPI of CMMI level 2 practice based on the views and experiences of small and medium-sized software firms in Bangladesh. The primary goal of this study is to determine how commonly a given CMMI practice is adopted to build a new maturity model within specific exercises. We use questionnaire-based survey sessions as the main tool to collect data from 9 SMEs in Bangladesh. Practitioners were asked to choose and rank CMMI level 2 practices based on the five classes of evaluations. Afterward, based on CMMI Level 2 practices from the acquired data, we develop a maturity model for adopting SPI.The paper proposes a model to improve those particular practices to build successful CMMI-based SPI and increase the success rate of CMMI-based SPI initiatives.

КРИТЕРІЇ ISO 21434 ДЛЯ ФОРМУВАННЯ СИСТЕМНИХ СПЕЦИФІКАЦІЙ У ПРОЦЕСАХ A-SPICE ДЛЯ АВТОМОБІЛІВ

With the increasing presence of electronics and autonomous systems in modern automobiles, cybersecurity has become a critical concern. Automotive manufacturers and other stakeholders are actively seeking ways to ensure reliable protection against cyber attacks. One approach involves the utilization of ISO 21434, a standard designed to enhance cybersecurity in the automotive industry. This research article investigates the ISO 21434 standard and its application in the field of automotive production, specifically in software development under the A-SPICE standard. The publication describes the methods and concepts used to enhance cybersecurity in the automotive industry and establishes the role of ISO 21434 within the A-SPICE model. The study's findings are valuable for companies and professionals involved in the development and implementation of cybersecurity measures in the automotive sector. Implementing the ISO 21434 standard can mitigate the risk of cyber attacks and improve the quality and reliability of automobiles, thus making the automotive industry safer and more trustworthy for consumers. The article provides an overview of key cybersecurity standards in the automotive industry. ISO 26262 sets out processes and requirements for functional safety in automotive systems, including cybersecurity considerations. SAE J3061 focuses on cybersecurity management in electronic systems of vehicles and is widely used in the industry. ISO/SAE 21434, introduced in 2020, replaces the previous ISO 26262 standard and specifies cybersecurity requirements in the automotive industry. These standards are closely related as they aim to ensure the safety and security of automotive products. Furthermore, the Automotive SPICE (Software Process Improvement and Capability Determination) framework is widely employed for evaluating and enhancing software development processes in the automotive sector. A-SPICE, a specific variant of Automotive SPICE, provides a framework for improving software development processes in automotive organizations. ISO 21434 guides cybersecurity activities within the A-SPICE framework, emphasizing the importance of a systematic and standardized approach to cybersecurity. To effectively implement cybersecurity in automotive products developed under A-SPICE, compliance with the ISO 21434 standard is crucial. However, mere adherence to the standard may be insufficient for achieving a high level of cybersecurity. Additional tools such as risk analysis methodologies and cybersecurity management can be employed to ensure robust cybersecurity measures. Risk analysis results can help identify vulnerabilities in the security system, enabling the development of effective mitigation measures. Cybersecurity management ensures compliance with the standard throughout the product development lifecycle. ISO 21434 can be applied at various stages of the V-model software development process, including requirements definition, design, and testing. During requirements definition, cybersecurity requirements are identified and incorporated into the system or software specifications. In the design phase, architectures are developed considering the cybersecurity requirements outlined in the standard. The testing phase addresses the fulfillment of cybersecurity requirements and evaluates the effectiveness of cybersecurity measures. In conclusion, the inclusion of ISO 21434 criteria in the development process of automotive software significantly impacts the quality and safety of products. The research demonstrates that applying ISO 21434 criteria allows for a systematic and structured approach to software development, ensuring the reliability, safety, and compliance of software products with regulatory requirements in the automotive industry. The article presents an analysis of standards, methods, and approaches used in the automotive industry and highlights the influence of ISO 21434 on the A-SPICE framework, defining its position within the model. Ultimately, this publication contributes to the advancement of knowledge in automotive cybersecurity.

An Analysis of Demotivators for the Standardized Software Process Improvement

전세계 많은 기업들은 소프트웨어 품질문제를 해결하기 위해 많은 시간과 노력을 투입하고 있다. 하지만, 소프트웨어 프로세스 개선을 추진함에도 불구하고 자신들이 기대했던 성과를 거두지 못하고 있는 실정이다. 소프트웨어 프로세스 개선을 위해서는 장기적인 계획과 비용이 소요되지만 제한된 성공이라는 결과는 장기적이고 체계적인 소프트웨어 프로세스 개선을 추진하는데 어려움을 가중시키는 요인으로 작동하고 있다. 본 연구에서는 소프트웨어 프로세스 개선에 영향을 미치는 요인들에 대한 실증데이터 분석을 진행하였다. 선행연구를 통해 기업 내부에서 소프트웨어 프로세스 개선을 수행하고 있는 기업 관리자들에게 성공적인 프로세스 개선을 위한 통찰력을 제공하고자 한다. 또한 기업의 규모에 따라 소프트웨어 프로세스 개선의 저해요인들이 다르게 나타나는지를 분석하였다, 분석 결과를 살펴보면, 협의없는 프로세스 개선, 조직적 저항, 조직요구와 동떨어진 소프트웨어 프로세스목표 설정, 모범사례 공유체계 부족, 개선실패 경험 등에 있어 조직의 크기간 차이가 있는 것으로 나타났다.

A software process improvement framework based on best practices

AbstractSoftware process improvement requires significant effort related not only to the identification of relevant issues and providing an adequate response to them, but also to the implementation and adoption of the changes. Best practices provide recommendations to software teams on how to address identified objectives in practice, based on aggregated experience and knowledge. In the paper, we present the GÉANT SPI framework based on best practices, together with the collected experience from the process of adopting the best practices.

Role of Capability Maturity Model Integration (CMMI) in Software Process Improvement

Role of Capability Maturity Model Integration (CMMI) in Software Process Improvement

Application of a Gamified Approach to Learning in the Treatment of Problems in Software Process Improvement: Analysis and Discussion of Results

The specialized literature defines Software Process Improvement (SPI) as the fundamental approach to improving software products in software development organizations. In this context, studies report several problems and difficulties that organizations face during the implementation of improvements. Although there are studies that address the problems highlighted in improvement programs, few studies still seek to identify practices in order to mitigate the negative effects of critical factors. Thus, the objective of this work is to discuss and analyze the results obtained in an Experience Report that consisted of a dynamic application with gamification elements in an SPI context related to learning in the treatment of recurring problems or difficulties in the implementation of improvements. It is noteworthy that the dynamics can be developed in organizations (commercial and academic) regardless of the improvement model or standard desired, since it was elaborated in relation to common problems experienced and identified in the SPI implementations scenario. The analysis of the obtained data was performed using an Evaluation Framework for Gamification in Software Engineering, which provided a standard structure for the design of evaluation studies for gamification cases.

Towards the sustainability of small and medium software enterprises through the implementation of software process improvement: Empirical investigation

AbstractTo improve and sustain the quality of software products, software process improvement (SPI) is needed. Currently, small and medium software enterprises (SMSEs) represent a high proportion of companies around the world and become a cornerstone in the worldwide industry economy. These companies have realized that improving their process is crucial for success, but they are facing difficulties to implement it due to limited resources, limited knowledge, and time constraints. This study aimed to identify the sustainability success factors (SSFs) that have a positive impact on implementing SPI efforts in SMSEs. Data were collected through a systematic literature review (SLR) approach and quantitatively through a survey questionnaire. A list of 44 SSFs was identified during SLR and empirical study. Results illustrate that there is a positive correlation between the ranks obtained from both dataset (rs (44) = .548, ρ = .001). Therefore, there would be significant differences between the SSFs identified in both datasets. In conclusion, the top‐ranked factors can then be used to guide the SPI coordinators on where they should focus their attention to reach the desired SPI goals, which is crucial to deliver the software products and also facilitates in development of model for SPIs in the future.