Collaborative Model-Driven Software Engineering: A Classification Framework and a Research Map

This proposal is about a study we recently published in the IEEE Transaction of Software Engineering journal [4]. Context: Collaborative software engineering (CoSE) deals with methods, processes and tools for enhancing collaboration, communication, and co-ordination (3C) among team members [5]. CoSE can be employed to conceive different kinds of artifacts during the development and evolution of software systems. For instance, when focusing on software design, multiple stakeholders with different expertise and responsibility collaborate on the system design. Model-Driven Software Engineering (MDSE) provides suitable techniques and tools for specifying, manipulating, and analyzing modeling artifacts including metamodels, models, and transformations [1]. Collaborative MDSE consists of methods or techniques in which multiple stakeholders manage, collaborate, and are aware of each others' work on a set of shared models. A collaborative MDSE approach is composed of three main complementary dimensions: (i) a model management infrastructure for managing the life cycle of the models, (ii) a set of collaboration means for allowing involved stakeholders to work on the modelling artifacts collaboratively, and (iii) a set of communication means for allowing involved stakeholders to exchange, share, and communicate information within the team. Collaborative MDSE is attracting several research efforts from different research areas (e.g., model-driven engineering, global software engineering, etc.), resulting in a variegated scientific body of knowledge on the topic. Objective: In this study we aim at identifying, classifying, and understanding existing collaborative MDSE approaches. More specifically, our goal is to assess (i) the key characteristics of collaborative MDSE approaches (e.g., model editing environments, model versioning mechanisms, model repositories, support for communication and decision making), (ii) their faced challenges and limitations, and (iii) the interest of researchers in collaborative MDSE approaches over time and their focus on the three dimensions of collaborative MDSE. Method: In order to achieve this, we designed and conducted a systematic mapping study [6] on collaborative MDSE. Starting from over 3,000 potentially relevant studies, we applied a rigorous selection procedure [3] resulting in 106 selected papers, further clustered into 48 primary studies, along a time span of nineteen years. A suitable classification framework has been empirically defined and rigorously applied for extracting key information from each selected study. We collated, summarized, and analyzed extracted data by applying scientifically sound data synthesis techniques. Results: In addition to a number of specific insights, our analysis revealed the following key findings: (i) there is a growing scientific interest on collaborative MDSE in the last years; (ii) multi-view modeling, validation support, reuse, and branching are more rarely covered with respect to other aspects about collaborative MDSE; (iii) different primary studies focus differently on individual dimensions of collaborative MDSE (i.e., model management, collaboration, and communication); (iv) most approaches are language-specific, with a prominence of UML-based approaches; (v) few approaches support the interplay between synchronous and asynchronous collaboration. Conclusion: This study gives a solid foundation for a thorough identification and comparison of existing and future approaches for collaborative MDSE [2]. Those results can be used by both researchers and practitioners for identifying existing research/technical gaps to attack, better scoping their own contributions to the field, or better understanding or refining existing ones.

Model-Driven Software Engineering (MDSE) is a development method in which models are used to generate software. Despite documented advantages, projects employing MDSE may fail due to development challenges. In this paper, we study and document these challenges by conducting an up-to-date systematic mapping that goes beyond reviewing MDSE studies: we also include two derived paradigms (Model-Oriented Programming and Models at Run-time). Therefore, we present a systematic mapping with two objectives: The first objective was to identify specific domains in which MDSE is successful, while the second objective was to identify what are the challenges to apply this methodology to general purpose development processes. Following the review of 4859 studies (3727 are unique), we have identified the application and technological domains in which MDSE projects are more likely to succeed. We also discuss challenges presented by 17 primary studies. The analysis of the results indicate that MDSE application is consolidated in specific domains. A common feature identified among studies related to general purpose MDSE processes is that, initially, authors reported lack of proper methods and training. After new techniques have risen, it has been pointed that MDSE projects still face maintenance problems that can discourage their usage in other domains.

Model Driven Software Engineering (MDSE) promotes the use of models, rather than code, as the primary development artifacts. Models tend to be more understandable than code and can represent systems are variable levels of abstraction. MDSE promises improved code quality and engineers’ productivity. Many of those benefits have been well examined and evaluated. However, the potential implications of MDSE on software security and reliability is not well understood. Model-Driven Security (MDS) is an approach that can support the process of modeling security requirements at a high level of abstraction in the early stage of software development. In this paper, we conduct a systematic study on MDS methodologies and concepts. The scope of the review is ten years from 2008 to 2018. The study reports on the frequencies of publication over this time period to identify the MDS forums based on seven classifications: online databases, year of publications, type of publication (journal or conference paper), the geographical distribution of the researchers, the main contribution of each paper, MDS approaches, and the security concepts. The majority of studies focused on extensions to existing UML languages suggesting some limitations in the current UML standard support for security. Most studies report on empirical evaluations, and UML Class Diagrams were the most extended language.

SummaryContext: Software performance is crucial for ensuring the quality of software products. As one of the non‐functional requirements, the few efforts devoted to software performance have often been neglected until a later phase in the software development life cycle (SDLC). The lack of clarity of what software performance research literature is available prevents researchers from understanding what software performance research fields are available. It also creates difficulty for practitioners to adopt state‐of‐the‐art software performance techniques. Software performance research is not as organized as other established research topics such as software testing. Thus, it is essential to conduct a systematic mapping study as a first step to provide an overview of the latest research literature available in software performance. Objective: The objective of this systematic mapping study is to survey and map software performance research literature into suitable categories and to synthesize the literature data for future access and reference. Method: This systematic mapping study conducts a manual examination by querying research literature in noble journals and proceedings in software engineering in the past decade. We examine each paper manually and identify primary studies for further analysis and synthesis according to the pre‐defined inclusion criteria. Lastly, we map the primary studies based on their corresponding classification category. Results: This systematic mapping study provides a state‐of‐the‐art literature mapping in software performance research. We have carefully examined 222 primary studies out of 2000+ research literature. We have identified six software performance research categories and 15 subcategories. We generate the primary study mapping and report five research findings. Conclusions: Unlike established research fields, it is unclear what types of software performance research categories are available to the community. This work takes the systematic mapping study approach to survey and map the latest software performance research literature. The study results provide an overview of the paper distribution and a reference for researchers to navigate research literature on software performance.

In recent years, the capacity of big data analytics (BDA) has attracted the significant attention of researchers linked to academia and industry professionals. This capacity is related to the possibility of managing informations advanced to reach its supply chain. In other words, information technology uses integrated systems, which facilitates innovation and the diffusion of knowledge throughout this supply chain. However, researchers and professionals still need to explore the capacity potential of BDA, in order to improve supply chain operational decision-making skills. This work classifies the state-of-the-art literature that applied BDA to the supply chain management (SCM). A Systematic Mapping Study was elaborated based on literature guidelines. A total of 50 primary studies were selected through a filtering process from initially 5,437 studies. These primary studies were used to answer the six research questions. The result of the classification showed that 64% of the studies are related to supply-chain management; most of the studies carried out empirical research; and approximately 50% of the primary studies investigated models for optimization process. This research provides to academics and industry professionals the gaps and future challenges related to BDA for SCM.

Collaborative Model-Driven Software Engineering — A systematic survey of practices and needs in industry

Domain-Specific Languages: A Systematic Mapping Study

Collaborative configuration approaches in software product lines engineering: A systematic mapping study

Mobile apps with tested Graphical User Interface (GUI) tend to have higher downloads in the apps store. In recent years, few efforts were made to analyse the research community and research status of the literature for GUI testing on mobile apps, which brings an obstacle to characterise and understand this field. In this study, the authors propose a systematic mapping study to gain insights into the field. First, the authors conduct an extensive search of relevant literature over seven popular digital libraries. From 4427 candidate studies, 114 primary studies published between January 2011 and September 2022 were selected. Next, the authors analyse these primary studies from the perspectives of bibliometric and qualitative analysis. For the bibliometric analysis, first, the authors analyse the popular research topics and their relationships. Second, the authors study the authors' community. For the qualitative analysis, the authors analyse the objectives, approaches and evaluation metrics employed in these primary studies. Their investigation reports several major findings: (1) there are relatively more studies on two topics, that is, test case generation and the automated test; (2) the most productive authors tend to collaborate and often have relatively broad research interests; (3) the functionality is the main objective of GUI testing; the model‐based approach is the most widely used.

To evaluate the methodological quality of recent systematic reviews of interventions for children with cerebral palsy in order to determine the level of confidence in the reviews' conclusions. A comprehensive search of 22 databases identified eligible systematic reviews with and without meta-analysis published worldwide from 2015 to 2019. We independently extracted data and used A Measurement Tool to Assess Systematic Reviews-2 (AMSTAR-2) to appraise methodological quality. Eighty-three systematic reviews met strict eligibility criteria. Most were from Europe and Latin America and reported on rehabilitative interventions. AMSTAR-2 appraisal found critically low confidence in 88% (n=73) because of multiple and varied deficiencies. Only 7% (n=6) had no AMSTAR-2 critical domain deficiency. The number of systematic reviews increased fivefold from 2015 to 2019; however, quality did not improve over time. Most of these systematic reviews are considered unreliable according to AMSTAR-2. Current recommendations for treating children with CP based on these flawed systematic reviews need re-evaluation. Findings are comparable to reports from other areas of medicine, despite the general perception that systematic reviews are high-level evidence. The required use of current widely accepted guidance for conducting and reporting systematic reviews by authors, peer reviewers, and editors is critical to ensure reliable, unbiased, and transparent systematic reviews. What this paper adds Confidence was critically low in the conclusions of 88% of systematic reviews about interventions for children with cerebral palsy (CP). Quality issues in the sample were not limited to systematic reviews of non-randomized trials, or to those about certain populations of CP or interventions. The inclusion of meta-analysis did not improve the level of confidence in these systematic reviews. Numbers of systematic reviews on this topic increased over the 5 search years but their methodological quality did not improve.

Background: Interest in the integration of the agile software development process (ASDP) and user-centred design (UCD) has grown over the last decade. However, there are not many papers that study this issue holistically and uncover the current state of this integration. Aim: This study sets out to answer the following research question: What is the current state of integration between agile processes and usability? Method: We conduct a systematic mapping study (SMS). A SMS is a form of systematic literature review that aims to identify and classify the research papers published about a specified issue. Results: We retrieved a total of 161 primary studies, which we categorized according to four criteria: process, practice, team and technology integration. The largest group refers to process integration with a total of 76 primary studies. Judging by the increase in the number of publications over the last decade, the integration of human-computer interaction (HCI) activities and techniques into the ASDP is an issue of notable interest. Conclusions: There are very few papers that study the literature holistically and report the current state of usability in the ASDP. Additionally, there are no formalized proposals for adopting usability techniques in ASDP.

A good search strategy is essential for a successful systematic literature study. Historically, database searches have been the norm, which was later complemented with snowball searches. Our conjecture is that we can perform even better searches if combining these two search approaches, referred to as a hybrid search strategy. Our main objective was to compare and evaluate a hybrid search strategy. Furthermore, we compared four alternative hybrid search strategies to assess whether we could identify more cost-efficient ways of searching for relevant primary studies. To compare and evaluate the hybrid search strategy, we replicated the search procedure in a systematic literature review (SLR) on industry–academia collaboration in software engineering. The SLR used a more “traditional” approach to searching for relevant articles for an SLR, while our replication was executed using a hybrid search strategy. In our evaluation, the hybrid search strategy was superior in identifying relevant primary studies. It identified 30% more primary studies and even more studies when focusing only on peer-reviewed articles. To embrace individual viewpoints when assessing research articles and minimise the risk of missing primary studies, we introduced two new concepts, wild cards and borderline articles , when performing systematic literature studies. The hybrid search strategy is a strong contender for being used when performing systematic literature studies. Furthermore, alternative hybrid search strategies may be viable if selected wisely in relation to the start set for snowballing. Finally, the two new concepts were judged as essential to cater for different individual judgements and to minimise the risk of excluding primary studies that ought to be included.

EPA-0776 – The comfort care in nursing practice: a systematic review study

In the last decade, as an emerging technique for business processes management, process mining (PM) has been applied in many domains, including manufacturing, supply-chain, government, healthcare, and software engineering. Particularly in healthcare, where most processes are complex, variable, dynamic, and multi-disciplinary in nature, the application of this technique is growing yet challenging. Several literature reviews, as secondary studies, reveal the state of PM applications in healthcare from different perspectives, such as clinical pathways, oncology processes, and hospital management. In this article, we present the results of a systematic mapping (SM) study which we conducted to structure the information available in the primary studies. SM is a well-accepted method to identify and categorize research literature, in which the number of primary studies is rapidly growing. We searched for studies between 2005 and 2017 in the electronic digital libraries of scientific literature, and identified 172 studies out of the 2428 initially found on the topic of PM in healthcare. We created a concept map based on the information provided by the primary studies and classified these studies according to a number of attributes including the types of research and contribution, application context, healthcare specialty, mining activity, process modeling type and notation/language, and mining algorithm. We also reported the demographics and bibliometrics trends in this domain; namely, publication volume, top-cited papers, most contributing researchers and countries, and top venues. The results of mapping showed that, despite the healthcare data and technique related challenges, the field is rapidly growing and open for further research and practice. The researchers who are interested in the field could use the results to elicit opportunities for further research. The practitioners who are considering applications of PM, on the other hand, could observe the most common aims and specialties that PM techniques are applied.

The automation of robotic processes has been experiencing an increasing trend of interest in recent times. However, most of literature describes only theoretical foundations on RPA or industrial results after implementing RPA in specific scenarios, especially in finance and outsourcing. This paper presents a systematic mapping study with the aim of analyzing the current state-of-the-art of RPA and identifying existing gaps in both, scientific and industrial literature. Firstly, this study presents an in-depth analysis of the 54 primary studies which formally describe the current state of the art of RPA. These primary studies were selected as a result of the conducting phase of the systematic review. Secondly, considering the RPA study performed by Forrester, this paper reviews 14 of the main commercial tools of RPA, based on a classification framework defined by 48 functionalities and evaluating the coverage of each of them. The result of the study concludes that there are certain phases of the RPA lifecycle that are already solved in the market. However, the Analysis phase is not covered in most tools. The lack of automation in such a phase is mainly reflected by the absence of technological solutions to look for the best candidate processes of an organization to be automated. Finally, some future directions and challenges are presented.