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Building and testing software for embedded systems can be challenging with an impact on delivery time, design reproducibility, and collaboration among project contributors. To accelerate project development, presented here is an automated build flow that utilizes Xilinx PetaLinux, and field programmable gate array (FPGA) hardware description and integrates with the GitLab continuous integration and continuous deployment (CI/CD) framework for embedded targets. This build flow automates the complete process of FPGA implementation, PetaLinux configuration, and cross-compilation of software essentials for the target system-on-chip (SoC). The system has been successfully deployed in cross-compiling the control and command toolset for the Positron Emission Tomography scanner (PhenoPET) and the implementation of the message queuing telemetry transport (MQTT) service on a Xilinx Zynq Ultrascale MPSoC. This approach can be easily adapted to other projects with specific requirements. [ABSTRACT FROM AUTHOR]

Cloud computing is a trending topic that has raised attention to attack complicated problems. Likewise, the multi-criteria decision-making methods present extensive interest in decision-analysis situations. As a result, scientific research has shown a notable development in multi-criteria decision-making techniques. Nevertheless, sufficient software is still needed to drive the data produced by multi-criteria analysis. At the same time, in order to present a solution from a homogeneous point of view, the MCDM problems require the use of multiple data sets. In this way, the study for creating software that incorporates dimensional analysis using the intuitionistic fuzzy method is presented in this article. Lastly, the construction of a software package that incorporates the IFDA technique into an interface is the focus of this study. Furthermore, the software’s primary feature makes it easier to manipulate data utilizing a fuzzy set approach for the assessment of multi-criteria decision-making problems. The outcomes showed that our suggestion, which makes use of intuitionistic fuzzy sets, is a powerful tool for solving MCMD problems.

Domain-specific standards and documents heavily regulate safety-critical systems. One example is the DO-178C standard for aerospace, which guides organizations to achieve system safety and evidence for their certification. Under such regulated contexts, most organizations use traditional development processes, in contrast to the massive adoption of Agile in the software industry. Among other benefits, Agile methods promise faster delivery and better flexibility to address customer needs. Adopting Agile methods and practices are possible in aerospace because the DO-178C standard does not prescribe concrete software development methods. In spite of that, Agile development is not used in DO-178C contexts. To help change that, our research aims to understand whether and how organizations engineering safety-critical software systems for aerospace may benefit from Agile methods and practices. We analyzed the DO-178C standard and confirm that it is compatible with Agile methods. Then, we present a systematic literature mapping of adopting Agile in software development for aerospace, where we identified significant concerns, recurrent issues, and several challenges. Some real industry aerospace projects provided us with important data and the perspective of domain experts about the pros and cons of Agile methods in this context. We conclude by proposing an agenda of research opportunities to improve safety-critical software development towards agility that we consider worthy of further research, application and confirmation in wider contexts.

Code generation stands as a powerful technique in modern software development, improving development efficiency, reducing errors, and fostering standardization and consistency. Recently, ChatGPT has exhibited immense potential in automatic code generation. However, existing researches on code generation lack guidance for practical software development process. In this study, we utilized ChatGPT to develop a web-based code generation platform consisting of key components: User Interface, Prompt Builder, and Backend Service. Specifically, Prompt Builder dynamically generated comprehensive prompts to enhance model generation performance. We conducted experiments on 2 datasets to evaluate the performance of code generation in our approach. through 8 widely used metrics. The results demonstrate that (1) our Prompt Builder is effective, resulting in a 65.06% improvement in the exact match (EM), a 38.45% improvement in Bilingual Evaluation Understudy (BLEU), a 15.70% improvement in CodeBLEU, and a 50.64% improvement in Pass@1. (2) In real development scenarios, 98.5% of test cases can be validated through manual validation, highlighting the genuine assistance provided by the ChatGPT-based code generation approach.

Heterogeneous cross-project defect prediction (HCPDP) aims to learn a prediction model from a heterogeneous source project and then apply the model to a target project. Existing HCPDP works mapped the data of the source and target projects in a common space. However, the pre-defined forms of mapping methods often limit prediction performance and it is difficult to measure the distance between two data instances from different feature spaces. This paper introduced optimal transport (OT) theory for the first time to build the relationship between source and target data distributions, and two prediction algorithms were proposed based on OT theory. In particular, an algorithm based on the entropic Gromov-Wasserstein (EGW) discrepancy was developed to perform the HCPDP model. The proposed EGW model measures the distance between two metric spaces by learning an optimal transfer matrix with the minimum data transfer cost and avoids measuring the distance of two instances of different feature spaces. Then, to improve EGW performance, an EGW+ transport algorithm based on EGW was developed by integrating target labels. Experimental results showed the effectiveness of EGW and EGW+ methods, and proved that our methods can support developers to find the defects in the early phase of software development.

This paper presents action research to analyze an approach for assessment of the alleged agile transformation. This approach was implemented at AK Bars Digital Technologies, an IT spin-off of one of the largest banks in Russia using the Scaled Agile Framework. The approach is based on the Goal-Question-Metric approach, non-invasive measurement collection, and systemic analysis. It uses data from several different sources, including interviews, code repositories, user ratings in the play stores, and templates for agile assessment. The effectiveness of the approach is subjectively validated by the adoption of the proposed recommendations by the banks’ senior management. Details are provided on the approach, the required effort from the side of both those assessing and of the people being assessed and the results. The final part of the paper is devoted to the discussion of its generalizability and the plan for future experimentation and refinement.

Organizations are under increasing pressure to develop applications within budget and time at high quality. Therefore, multiple organizations adopt a Low Code Development Platform (LCDP) to develop applications faster and cheaper compared to traditional application development. However, current research on LCDP adoption lacks empirical grounding as well as a deeper understanding of the importance of adoption drivers and inhibitors. We conducted semi-structured interviews and a Delphi study with 17 experts to address these gaps. As a result, we identified 12 drivers and 19 inhibitors for adopting LCDPs. We show that the experts have a consensus on the most and the least important drivers and inhibitors for LCDP adoption. Yet, the ranking of the drivers and inhibitors between the most and least important is context-dependent. For some drivers and inhibitors, the experts’ ranking is similar to academic literature, whereas, for others, it differs. In conclusion, the study at hand empirically validates drivers and inhibitors for LCDP adoption, adds six new drivers and six new inhibitors to the body of knowledge, and analyzes the importance of these factors.

The objective of this work is to provide a comprehensive understanding of the development of autonomous vehicle perception systems. So far, most autonomy perception research has been concentrated on improving perception systems’ algorithmic quality or combining different sensor setups. In our work, we draw conclusions from participating in the Indy Autonomous Challenge 2021 and its follow-up event in Las Vegas 2022. These were the first head-to-head autonomous racing competitions that required an entire perception pipeline to perceive the environment and the opposing surrounding vehicles. Our research includes quantitative results from collected vehicle data and qualitative results from simulation, video, and multiple race analysis. The Indy Autonomous Challenge was one of the few research projects that considered the entire autonomous vehicle. Therefore, our findings indicate insights on the system level, including hardware setup and full-stack software. We can demonstrate that different sensor modalities in the vehicle have strengths and weaknesses when they are deployed. Our results further show the difficulties and challenges that emerge when multi-modal perception systems must run in real-time on real-world autonomous vehicles. The most concise finding from our investigation is the summary of critical learnings when developing and deploying perception systems for autonomous systems. Given the background of the study, it was inevitable that our conclusions were influenced by driving on the racetrack and only one hardware setup available. Therefore, in the discussion, we draw further parallels to driving on public roads in dense traffic. More studies are needed to investigate the development and deployment of multi-modal perception systems for autonomous road vehicles with different hardware setups and various object detection, localization, and prediction algorithms. The novel contributions of this work are given by 12 lessons learned, summarized in 5 categories. These were derived and validated through a realized real-world application project. The videos of the final events in Indianapolis and Las Vegas can be watched here:IAC: https://www.youtube.com/watch?v=ERTffn3IpIs&ab_channel=CNETHighlightsAC@CES: https://www.youtube.com/watch?v=df9f4Qfa0uU&ab_channel=CNETHighlightsMultiple modules of the software stack are open source: https://github.com/TUMFTM.

The restrictions imposed by the COVID-19 pandemic required software development teams to adapt, being forced to work remotely and adjust the software engineering activities accordingly. In the studies evaluating these effects, a few have assessed the impact on software engineering activities from a broader perspective and after a period of time when teams had time to adjust to the changes. No studies have been found comparing software startups and established companies either. This paper aims to investigate the impacts of COVID-19 on software development activities after one year of the pandemic restrictions, comparing the results between startups and established companies. Our approach was to design a cross-sectional survey and distribute it online among software development companies worldwide. The participants were asked about their perception of COVID-19’s pandemic impact on different software engineering activities: requirements engineering, software architecture, user experience design, software implementation, and software quality assurance. The survey received 170 valid answers from 29 countries, and for all the software engineering activities, we found that most respondents did not observe a significant impact. The results also showed that software startups and established companies were affected differently since, in some activities, we found a negative impact in the former and a positive impact in the latter. Regarding the time spent on each software engineering activity, most of the answers reported no change, but on those that did, the result points to an increase in time. Thus, we cannot find any relation between the change in time of effort and the reported positive or negative impact.

Software programming is an acquired evolutionary skill originating from consolidated cognitive functions (i.e., attentive, logical, coordination, mathematic calculation, and language comprehension), but the underlying neurophysiological processes are still not completely known. In the present study, we investigated and compared the brain activities supporting realistic programming, text and code reading tasks, analyzing Electroencephalographic (EEG) signals acquired from 11 experienced programmers. Multichannel spectral analysis and a phase-based effective connectivity study were carried out. Our results highlighted that both realistic programming and reading tasks are supported by modulations of the Theta fronto-parietal network, in which parietal areas behave as sources of information, while frontal areas behave as receivers. Nevertheless, during realistic programming, both an increase in Theta power and changes in network topology emerged, suggesting a task-related adaptation of the supporting network system. This reorganization mainly regarded the parietal area, which assumes a prominent role, increasing its hub functioning and its connectivity in the network in terms of centrality and degree.

Attention and concentration has been claimed as reasons for higher quality code and more productive development, also with some empirical evidence. In this paper we investigate the matter further. We present a systematic literature review focused on investigating the existing methods for measuring attention in the software development processes especially team meetings. Based on the research gap revealed by literature review, we conducted experiments measuring attention levels using portable electroencephalography (EEG) device. Attention was measured while the software developers took part in stand-up and sit-down meetings. The experimental results revealed that stand-up meetings foster higher level of attention compared to sit-down meetings.

As a result of the COVID-19 pandemic, remote work became commonplace out of necessity, and has since remained widespread. Currently, many organizations offer the possibility of remote work while encouraging occasional on-site presence, leading to the emergence of “hybrid work” or “work-from-anywhere” – a blend of remote and on-site work. Hybrid work is a novel phenomenon that currently concerns the industry, as organizations are still looking for good and best practices related to work modes in the post-pandemic situation. As few studies on hybrid work in the context of Software Engineering (SE) currently exist, we take on an explorative approach to the topic in this paper. Using a qualitative case study approach, we interview 10 software developers to study (a) the factors influencing the work mode choices of software developers, and (b) how remote and on-site work could compliment each other in SE. Our findings highlight factors that influence the work mode choices of developers when they are free to choose their own work modes, in addition to providing some insights into challenges in hybrid work in SE and how to tackle them. Hybrid work can, for example, help tackle some of the issues often associated with fully remote work such as social isolation, but it also results in new challenges such as on-site days feeling unrewarding for developers if the office is largely empty. Our findings build on existing research by providing further insights into the challenges and benefits of the two work modes in hybrid contexts.

DevOps is the bundle of applications and culture activity that focuses to separate the challenges between evaluation and performance associates to boost participation and communication. Several companies clutch DevOps fundamentals due to tremendous perspectives, like small tempo for production, rise accuracy, and durability. In contempt of the global assumption of DevOps and its framework, there is an absence of interpretation studies and essential ideas, implementation, and issues related to executing DevOps procedures. The major objective of this research study is to investigate and study issues affiliated with the DevOps culture (DVC) and applications. The challenges that are challenging in adopting DevOps culture in software development (SD) are inspected by conducting the systematic literature review (SLR). Furthermore, it explains the working of DevOps in industries, gives full clarification of DevOps, and probes the cultural issues faced by the industries while executing DevOps. This study discloses ten barriers that should be declamation in accepting DevOps culture. In accordance with the discoveries, these ten barriers contemplate during the execution of DevOps culture i.e. lack of collaboration and coordination, Lack of skill and knowledge, complicated infrastructure, Lack of management, Lack of DevOps approach, and trust confidence problems.

Software programming is an acquired evolutionary skill originating from consolidated cognitive functions (i.e., attentive, logical, coordination, mathematic calculation, and language comprehension), but the underlying neurophysiological processes are still not completely known. In the present study, we investigated and compared the brain activities supporting realistic programming, text and code reading tasks, analyzing Electroencephalographic (EEG) signals acquired from 11 experienced programmers. Multichannel spectral analysis and a phase-based effective connectivity study were carried out. Our results highlighted that both realistic programming and reading tasks are supported by modulations of the Theta fronto-parietal network, in which parietal areas behave as sources of information, while frontal areas behave as receivers. Nevertheless, during realistic programming, both an increase in Theta power and changes in network topology emerged, suggesting a task-related adaptation of the supporting network system. This reorganization mainly regarded the parietal area, which assumes a prominent role, increasing its hub functioning and its connectivity in the network in terms of centrality and degree. [ABSTRACT FROM AUTHOR]

As software products increasingly become part of larger ecosystems, research and development (R&D) units of software producers organize themselves around projects to become more responsive to the environment. Organizations participating in software ecosystems must continuously adapt and adjust their software development and maintenance processes to drive both medium-term and long-term innovation. Agile methods and practices are widely adopted to guide the collaboration within and between project teams in software development. Moreover, when successfully attained, agility can drive innovation by enabling software development organizations to cope with technological changes and exploit emerging opportunities in software ecosystems. In this article, we focus on how organizations attain agility in the maintenance and development of software products. To answer this question, we conduct a longitudinal case study of Agile Scrum implementation in the R&D unit of a major supplier of telecommunication equipment. We investigate the emerging tensions and highlight practices used to balance these tensions in the Agile Scrum implementation. We identify four capabilities and ten practices that support effective collaboration and coordination in the development and maintenance of software products. The study offers practical guidance for R&D managers to attain agility in software ecosystems. [ABSTRACT FROM AUTHOR]

With the utilization of crowdsourcing as a problem-solving approach, software industry has progressed tremendously in recent few years. Different models of crowdsourcing have been used depending on the nature of required outcome of the task, and have had varying levels of success to date. Microtasking is one of the lucrative models of crowdsourcing which penetrated the problem-solving strategy by facilitating the decomposition of complex tasks into short and self-contained microtasks which can be performed in few minutes. Regardless of considerable number of studies explored the kinds of microtasks, existing researches fall short when it comes to technical as well as non-technical tasks and the categorization of relevant microtasks. Thus, the aim of this research is to understand the context of microtasked related crowdsourcing and to explore the microtasks related to crowdsourced software development which exist in literature. Systematic literature review is conducted to identify the microtasking activities and expert review is conducted to validate the identified microtasking activities and their categories. The final publication sample to review the literature is composed of 42 research articles and the reviews of 4 experts are taken for validation. A total of 72 microtasking activities are found along with 11 categories. After validation applied, researchers came up with a list of 61 unique microtasking activities. This paper contributes to software industry by providing list of microtasks along with their categories which will be fruitful for researchers, microtasking platforms and their clients. It contributes to software industry by providing list of microtasks which will be fruitful for researchers and microtasking platforms.

Security is the protection from various kinds of threats and most organizations engage in the challenge of security especially cyber-attacks. The attacks are increasing rapidly, due to which cyber security does not now change on supervised and pattern-based detection algorithms which assure continuous security observing. There are many kinds of problems in vendor organizations like cyber theft, which is the most common attack in cyberspace. This research study is developing a Cyber Security Challenges Model (CSCM) that will facilitate vendors’ organizations to identify challenges of cyber security during the development of software in a vendor organization. To find cyber security issues/challenges, a Systematic Literature Review (SLR) is conducted on 44 relevant research publications by developing a search string based on research questions. As the final selected research publications were less in number and did not complete our aim, therefore, snow bowling technique is applied to 67 relevant research publications. This relevant data was comprised of different databases/sources e.g., Google Scholar, IEEE Explore, SpringerLink, ACM Digital Library, anFffid ScienceDirect. Furthermore, for the distinctive literature review, we’ve carried out all of the steps in SLR, for example, improvement of SLR protocol, initials, and a very last collection of the applicable information, data extraction, data quality assessment, and data synthesis. Thirteen (13) critical cyber security challenges are identified which are; “Security issues/Access of Cyberattacks”, “Lack of Right Knowledge”, “Framework”, “Lack of Technical Support”, “Disaster Issues”, “Cost Security issues”, “Lack of Confidentiality and Trust”, “Lack of Management”, “Unauthorized Access issues”, “Lack of Resources”, “Lack of Metrics”, “Administrative Mistakes during Development” and “Lack of Quality, Liability, and Reliability”. The findings of our analysis study signify the similarities and dissimilarities in the recognized cybersecurity challenges in different decades, companies/firms, continents, databases, and methodologies.

It is vital for firms to measure, and, report on, the impact of eco-innovation towards their environmental performance. Additive Manufacturing is an eco-innovation that contributes towards reducing the environmental impact of manufacturing. However, there is a lack of practical tools for management to monitor and report on firms’ eco-innovation implementation and performance. This paper presents a prototype Eco-innovation Management Information System (EiMIS), developed to enable a firm’s management to systematically manage and report on eco-innovation performance. Using a top-down approach, the EiMIS is developed through utilizing the C# and SQL programming languages for the Graphical User Interface (GUI), Database Management System (DBMS) and other technologies to collect, store (into a relational database) and manage eco-innovation performance data. A 4-tier architecture enables the EiMIS to: store, view and retrieve or generate eco-innovation performance reports; and generally, manage firms’ eco-innovation performance data. This developed prototype could, help introduce information system platforms that: assist firms to collect data that can model their additive manufacturing; ease firms’ eco-innovation performance reporting; improve environmental data management capabilities; and complement firms’ digital transformation strategy.

Software Architecture describes system components and their connections. Requirement elicitation catering the perspective of software architecture is quite challenging and relatively less explored research area for the rapid software development. It has gain growing interest due to reusability of existing modules with less cost and quick developmental time. Software architecture in the context of requirement engineering is an abstraction of software system performing a particular task with the help of group of executable architectural components. In this paper, systematic literature review is adapted as a methodology to explore software architectural elements that provides better performance and simplicity in requirement engineering. We analyzed, reviewed and listed the strategies, tools & techniques along with state-of-the-art mechanisms, pros and cons and application areas. Architectural components that are already implemented in the requirement elicitation process for effective software architectural design are briefly analyzed. Purpose of the paper is to explore and discuss the elements that make software architecture more integral and flexible for traceability of requirements. Another purpose is to identify relation between the software requirements and architecture along with exploring the components to bridge gap between requirements and architecture by critically evaluating industrially and academically proposed methods, tools and frameworks. We also highlighted the open research challenges of Software architecture in requirement elicitation for better software development. In the later section, a resource bank is created acting as a valuable model that encompasses targeted relevant groups, sub-groups with latest software architecture tools & techniques, methods and framework sources to facilitate effective requirement engineering.

Software engineering is a discipline of Computer Science in which the new sub-areas are constantly added, especially in the area of quality, data management, and architectural design. Nowadays software development languages and processes are rapidly changing to deliver high-quality software products, i.e., usable systems, hybrid, and fulfill users’ needs. This paper aims to identify and classify different process models proposed by the researchers based on characteristics of software quality, data management, and software integration and redesign. From a study of several models through a systematic mapping study, we identify different parameters and presented them in a traceability matrix. The parameters are classified into six areas. This paper provides an in- depth theoretical insight into the models and characteristics. A systematic mapping study was conducted through a literature review. The methodology used in this paper is both qualitative and quantitative. Initially, through a systematic mapping study, we study different models working on different parameters. And then proposed a model that can cover all the aspects of software implementation and management. We select ERP systems for it. Later we perform the GAP analysis and statistical evaluation of the model. It has been observed that all of the models are area specific either focused on quality parameters or management issues or architectural-based. The proposed model covers all aspects. The primary research shows that industrialists also need a better model for quality implementation. Our statistical analysis can serve as a decision-making tool for them to add to their decision-making processes. The other could use it to further enhance the framework for quality management. This model will enhance further in the future for better implementation.

The project management process has been used in the area of Software Engineering to support project managers to keep projects under control. One of the essential processes in Software Engineering is to conduct an accurate and reliable estimation of the required effort to complete the project. This article’s objectives are: i) to identify the variables that influence the estimation based on the correlation, and ii) to apply the Extreme Learning Machine - ELM model for effort estimation and compare it with the literature models. Thus, it was investigated which technique has better effort prediction accuracy. The models were compared with each other based on predictive precision in the criterion of absolute mean residue (MAR) and statistical tests. The main findings in this study were: i) important variables for effort estimation and; ii) the results indicated that the ELM model presents the best results compared to the models in the literature for estimating software design effort. In this way, the use of Machine Learning techniques in the effort estimation process can increase the chances of success in the accuracy of the time estimates and the project’s costs.

In the software development process, traceability links between unit tests and code are not explicitly maintained, and dependencies in most cases are manually identified. As a result, a large amount of effort and time is required during the comprehension process to establish the links between these artifacts. Although there are several methods that can infer such links based on different phenomenons, these methods usually produce different set of traceability links. This work expands upon previous traceability link recovery and visualization studies by implementing a combination of traceability recovery methods that automatically retrieve the links, and visualizing them to help developers to overview the links inferred by various recovery techniques, and also to select the right relations for analyses. The results of the usability study show that the visualization model presented herein can effectively support browsing, comprehension, and maintenance of Test-to Code Traceability (TCT) links in a system with enhanced efficiency, as well as visualization of TCT links from multiple sources is better than a visualization of single source of traceability links.

Ample evidence in the literature emphasizes using socio-technical congruence (STC) to address coordination issues in distributed software development. The recent decades have shown a progressive growth in STC, resulting in an increasing number of research studies in the scientific corpora. However, no existing study has systematically analyzed and illustrated the research patterns, latest trends, and evolution in STC. This study aims to explore the knowledge structure and create evolutionary trajectories from STC publications. To achieve this aim, a scientometric analysis is performed that combined a critical literature review (CLR) of STC-related published research in the Web of Science and Scopus databases from 2000 to 2020. The scientometric analysis is conducted through four scientometric techniques: 1) co-word network analysis; 2) co-author network analysis; 3) co-citation analysis; 4) document clustering with timeline analysis. The study outcomes will help understand and visualize STC’s research status quo. CLR is objectively conducted to recognize the latest research topics, themes, and salient features of STC research in software development. A total of 306 bibliographic data are analyzed to generate study-related networks and density visualizations. The results reveal an evolution in the STC field from its conception to the recent developments of STC models and other related factors. This study primarily contributes to the literature by providing a systematic view related to STC research to assist software practitioners in identifying applications and key research areas. Moreover, the combination of scientometric analysis and CLR reveals key researchers, journals and conferences, institutions, prominent contributing countries, and six major research themes, including “community structure” and “socio-technical congruence” as the most prominent ones.

Communication among humans consists of both verbal and non verbal components. The latter may sometimes express concepts or ideas not conveyable by the former. This is also true in Software Engineering. This paper first analyses theoretically the role of non verbal communication in software development teams, using the framework provided by distributed cognition as a conceptual palette and as a point of reference. Then, it presents an empirical investigation involving 38 IT professionals from Russia, sharing their experiences in communicating and interacting when developing software artifacts. The results of this empirical investigation are consistent with many of the ideas underlying a distributed approach to cognition. In addition, our findings provide valuable insights to make communication more effective in software development teams, while defining a new framework for follow-up studies.

The accelerated growth in exploiting vulnerabilities due to errors or failures in the software development process is a latent concern in the Software Industry. In this sense, this study aims to provide an overview of the Secure Software Development trends to help identify topics that have been extensively studied and those that still need to be. Therefore, in this paper, a systematic mapping review with PICo search strategies was conducted. A total of 867 papers were identified, of which only 528 papers were selected for this review. The main findings correspond to the Software Requirements Security, where the Elicitation and Misuse Cases reported more frequently. In Software Design Security, recurring themes are security in component-based software development, threat model, and security patterns. In the Software Construction Security, the most frequent topics are static code analysis and vulnerability detection. Finally, in Software Testing Security, the most frequent topics are vulnerability scanning and penetration testing. In conclusion, there is a diversity of methodologies, models, and tools with specific objectives in each secure software development stage.

System operation, with the advancement of Internet and big data processing, has posed great requirements on software reliability beyond its functionality. However, the front and back ends in the supply chain of software usually make their own decisions regarding whether to reinforce reliability. Very few research works have investigated the limited rational game between the two parties, especially from a dynamic game perspective. To investigate the decision-making path and the influencing factors of the reliability investment, this article proposed a dynamic evolutionary game in a complex situation. Several scenarios were analyzed to identify the determining factors among diverse relevant elements when the evolutionary stable strategy was achieved. Through theoretical derivation and simulation analysis, the results revealed that the reliability development strategy was closely determined by the software complexity, basic costs, free-riding behavior, risk mitigation, social effects, and, most importantly, profitability. Evidence also showed that the decision-making process was impacted by the interactions and the initial choices between the two parties. [ABSTRACT FROM AUTHOR]

We have known for decades that IT projects often fail. The usual explanation is that the cause is poor project management, poor cost estimation, poor requirements, etc. But how can we prevent these causes? To answer this question, it is not sufficient to know that there was poor project management, etc. Would it suffice to educate better project managers? And what would we have to teach them that they don't learn today? We have to know what actually took place in the projects, identify the root causes, and find ways to prevent them (cures). This is similar to accident investigations in aviation. This paper reports the results of five accident investigations of large government IT projects in Denmark. We identified 37 root causes and 22 potential cures. Surprisingly, only one of the causes is programming-related. Each project suffered from around 15 of the causes. Twenty-seven of the causes are not reported in the research literature on IT project failures (e.g. surprises with system integration and wrong estimate of human performance). Half of the cures are familiar to developers, but were ignored in the specific project (example: usability test). The rest are unfamiliar (e.g. problem-oriented requirements and monitoring remaining work).

Despite the extensive adoption of crowdsourcing for the timely, cost-effective, and high-quality completion of software development tasks, a large number of crowdsourced challenges are not able to acquire a winning solution, on time, and within the desired cost and quality thresholds. A possible reason for this is that we currently lack a systematic approach that would aid software managers during the process of designing software development tasks that will be crowdsourced. This paper attempts to extend the current knowledge on designing crowdsourced software development tasks, by empirically answering the following management questions: (a) what type of projects should be crowdsourced; (b) why should one crowdsource-in terms of acquired benefits; (c) where should one crowdsource-in terms of application domain; (d) when to crowdsource-referring to the time period of the year; (e) who will win or participate in the contest; and (f) how to crowdsource (define contest duration, prize, type of contest etc.) to acquire the maximum benefits-depending on the goal of crowdsourcing. To answer the aforementioned questions, we have performed a case study on 2,209 software development tasks crowdsourced through TopCoder platform. The results suggest that there are significant differences in the level to which crowdsourcing goals are reached, across different software development activities. Based on this observation we suggest that software managers should prioritize the goals of crowdsourcing, decide carefully upon the activity to be crowdsourced and then define the settings of the task.

Analogy-Based Estimation (ABE) is one of the promising estimation models used for predicting the software development effort. Researchers proposed different variants of the ABE model, but still, the most suitable procedure could not be produced for accurate estimation. In this study, an artificial Bee colony guided Analogy-Based Estimation (BABE) model is proposed which ensembles Artificial Bee Colony (ABC) with ABE for accurate estimation. ABC produces different weights, out of which the most appropriate is infused in the similarity function of ABE during the stage of model training, which are later used in the testing stage for evaluation. There are six real datasets utilized for simulating the model procedure. Five of these datasets are taken from the PROMISE repository. The predictive performance is improved for BABE over the existing ones. The most significant of its performance is found on the International Software Benchmarking Standards Group (ISBSG) dataset.

Context: Software team formation is an important project management activity. However, forming appropriate teams is a challenge for most of the companies. Objective: To analyze and synthesize the state of the art on the software team formation research. Additionally, we aim to organize the identified body of knowledge in software team formation as a taxonomy. Method: Using a Snowballing-based systematic mapping study, 51 primary studies, out of 2516, were identified and analyzed. We classified the studies considering the research methods used, their overall quality, and the characteristics of the formed teams and the proposed solutions. Results: The majority of the studies use search and optimization techniques in their approaches. Also, technical attributes are the most frequent type considered to build individuals' profiles during the team formation process. Furthermore, we proposed a taxonomy on software team formation. Conclusion: There is a predominant use of search-based approaches that combine search and optimization techniques with technical attributes. However, the adoption of non-technical attributes as complementary information is a tendency. Regarding the research gaps, we highlight the level of subjectivity in software team formation and the lack of scalability of the proposed solutions.

Clinical software is a fundamental tool for supporting healthcare systems because it improves the quality of patient care and automatizes the most frequently performed clinical tasks. Nevertheless, since health systems include various components, such as supplies, transportation, laboratories, and interoperability, eliciting the most critical requirements for understanding the problem that the clinical software must solve is quite a complex task. Indeed, the requirement elicitation process may directly determine the success or failure of the clinical software. In this article, we present the D&I framework, a methodology that uses dissemination and implementation strategies to recommend guidelines for the elicitation of clinical software requirements. The objective of this framework is to support software developers in the identification of key requirements with the goal of more holistically understanding the problem to be solved by the clinical software. We evaluated the D&I framework with a real case study related to a bed management system. We employed a usability instrument with 50 clinicians to evaluate tasks in software modules that represent clinical priorities defined by stakeholders. The results indicate that the perception of usability by end users is acceptable, suggesting that the evaluated tasks satisfy the established clinical priorities. The D&I framework provides a starting point for research and discussion about the contribution of dissemination and implementation strategies to the body of knowledge about requirement engineering.

Software developers' knowledge of integrated development environment (IDE) directly impacts on their productivity. IDE command recommender systems aim at identifying and convincingly presenting to software developers functionality that can help them to accomplish their daily tasks, without overloading them with well known or useless information. Command recommendation requires the estimation of both the utility of commands and the acceptance of the user for new command recommendations. In this paper, we focus on how and when such recommendations should be presented. We performed a long-term user study and our results show that IDE command recommendation must be presented with adequate descriptions of the commands and good usage examples. It seems that a higher frequency of recommendation notifications could be useful, but it should not be too intrusive, especially while developers are focusing on more demanding tasks. To improve recommendation acceptance rate, researchers should also focus on context-aware algorithms and tailor command recommendation timing.

Software crowdsourcing is an emerging and promising software development model. It is based on the characteristics of Internet community intelligence, which makes it have certain advantages in development cost and product quality. Companies are increasingly using crowdsourcing to accomplish specific software development tasks. However, this development model still faces many challenges. One of the key issues is the collaboration between crowdsourced workers. Developer collaboration is important to software development, but workers in crowdsourcing come from an undefined network community, so it's hard to guarantee that they can work together. This paper focuses on task assignment and uses the active time of workers as the basis of grouping to provide a solution for multi-task to multi-worker allocation. Based on the on-demand distribution model, this paper considers three factors: worker's ability, task module complexity, and worker's active time. First, the workers are divided into multiple collaborative candidate groups based on active time. Then, the Hungarian algorithm is used to select the optimal workers for each module from the collaborative candidate groups of each task, and the coordination candidate group replacement strategy is used to solve the assignment failure problem. Finally completing the assignment of all tasks within an assignment cycle. The experiments have shown that the proposed method increases the total utility by 25% and the success rate of distribution by 30% than the sequential assignment method. The proposed method can give a reasonable solution for software crowdsourcing task allocation based on collaborative development.

Software development process tailoring is a standard and regular practice of software development companies. Without realizing it as a regular and well-defined standard approach, companies perform it on an ad-hoc basis. Due to which, process tailoring could not be developed into a formal process and approach to managing software development, processes and projects. Software development process paradigm shift from conventional software development approaches to the agile methodologies left many companies struggling with the reusability of the existing processes and defining new processes from scratch. Limited work on process tailoring and lack of a formal approach, particularly for overwhelmingly used agile methodologies, affected the acknowledgment of this process. Addressing this limitation, present research work formulates a process tailoring framework to tailor agile-based software development processes. The proposed framework recommends tailoring three key processes of agile methodologies based on the project state considering the client’s perspective and requirements. The existing literature have been reviewed to develop a theoretical framework which is verified and validated through structured interviews and case study of real projects. The framework provides a formal and a structured approach to tailor agile-based processes and methodologies.

Inevitably, the time has come that necessitates software systems to have long lasting social impact and environmental friendliness. Although sustainability related to environmental and social aspects have been well versed in the literature, software sustainability, for the way of development and as final product for use, is still not mature enough. With the increasing role of software crowdsourcing, a new working architecture for software development, in global software development (GSD) settings, has emerged challenges regarding sustainable software development and software sustainability, which are still to be elucidated. Software standards and models exist to assist co-located and global software development; however, seismic changes in the working architecture of software development as software crowdsourcing are highlighting a risk of software failure. Recently, statistics showed that only 30% of projects are successful, whereas 50% encounter challenges and the remaining 20% are absolute failures that implicate a challenge toward software success and its sustainability. This posits questions of how many IEEE and international standard organization standards exist that cover the sustainability aspects in particular to software development and how in-depth the development practices are addressing sustainable aspects in software crowdsourcing? Thus, the aim of this paper is to examine the IEEE software standards with a lens of sustainability to software crowdsourcing. After reviewing the existing IEEE standards related to sustainability, it has been observed that few standards exist which have discussed the importance of sustainability on an abstract level (energy and examining environmental influence by the computers) in software development. Moreover, standards are focusing less attention toward the sustainability of software development in the presence of new envision toward software crowdsourcing. Thus, a lack of any guideline toward sustainable software crowdsourcing is highlighted as one of the limitations in the software standards. This paper contributes to the GSD industry in two folds, first by laying down the importance and theoretical association on and around sustainable crowdsourcing, and second by highlighting that the IEEE standards, inadequacy toward the suppressing phenomena of sustainability in software crowdsourcing, if addressed adequately, can minimize the ripple effect toward software failure.

Software refactoring is popular and thus most mainstream IDEs, e.g., Eclipse, provide a top level menu, especially for refactoring activities. The refactoring menu is designed to facilitate refactorings, and it has become one of the most commonly used menus. However, to support a large number of refactoring types, the refactoring menu contains a long list of menu items. As a result, it is tedious to select the intended menu item from the lengthy menu. To facilitate the menu selection, in this paper, we propose an approach to dynamic ranking of refactoring menu items for IDE. We put the most likely refactoring menu item on the top of the refactoring menu according to developers' source code selection and code smells associated with the selected source code. The ranking is dynamic because it changes frequently according to the context. First, we collect the refactoring history of the open source applications and detect the code smells. Based on the refactoring history, we design questionnaires and analyze the responses from developers to discover the source code selection patterns for different refactoring types. Subsequently, we analyze the relationship between code smells associated with the refactoring software entities and the corresponding refactoring types. Finally, based on the preceding analysis, we calculate the likelihood of different refactoring types to be applied when a specific part of source code is selected, and rank the menu items according to the resulting likelihood. We conduct a case study to evaluate the proposed approach. Evaluation results suggest that the proposed approach is accurate, and in most cases (95.69%), it can put the intended refactoring menu item on the top of the menu.

Background: Previous research on user-generated content in technical communication focused primarily on non-traditional forms of technical communication outside of traditional institutions and organizations. User-generated content from the forum StackOverflow provides rich knowledge and stories behind problems faced by web and software developers. This study explores how technical communicators engage in this knowledge-rich content specific to web and software developers. Our findings provide insights into how researchers, instructors, and practicing technical communicators might leverage user-generated forum content in their work. Literature review: Previous research examined how user-generated content is a form of technical writing and technical editing. Furthermore, some research in technical communication has examined how technical user forums present a type of user-generated content to which technical communicators might add value. However, no research on user forums has explicitly examined how technical communicators engage in user forums to gain subject-matter familiarity or expertise. This study seeks to explore how technical communication students engage in user forums to troubleshoot coding problems. Research questions: 1. Are technical communication students able to successfully solve unfamiliar coding problems using user-generated content posted on the StackOverflow website? Are they able to identify the conceptual knowledge needed to solve the coding problem? 2. When learning about new, unfamiliar technical content, how do technical communication students search for information and decide which forum content to engage with? 3. Do technical communication students make meaning and actively fill knowledge gaps when they engage in new, unfamiliar technical content on StackOverflow? 4. After searching and reading through user-generated forum content to troubleshoot a coding task, do technical communication students feel confident enough in what they learned to teach someone else? Results: Most participants were unable to solve any of the coding problems using StackOverflow. Those who did successfully troubleshoot the coding problems exhibited more active scanning when selecting a search thread and made meaning of thread content more closely. Conclusions: Actively engaging and making meaning of thread content reveals insights into the stories behind the thread. These stories provide important details and clues for gaining subject-matter familiarity, but users must actively engage in meaning-making to access the stories and fill knowledge gaps. Practitioners and instructors can leverage content on StackOverflow to better understand coding problems. StackOverflow threads, along with other user-generated forum content, also give instructors insight into technical audiences and can be leveraged to teach students how to use primary research to better understand audiences. Researchers can continue to study how novice users interact with user-generated content by investigating how confidence levels affect meaning-making. [ABSTRACT FROM AUTHOR]

A multithreaded software application is presented that was designed by the Ground Special Power (GSP) team at NASA Kennedy Space Center (KSC) to fully emulate all units that supply VDC power and battery-based power backup to multiple KSC launch ground support systems for the NASA Space Launch Systems (SLS) rocket. The software application was built using Java programming language in Microsoft Windows 8 Operating System (OS) to emulate the operation, communication, and functionality of each VDC-power supply and battery backup units concurrently in communication via Ethernet open-socket protocol with Allen–Bradley (AB) RSlogix-5000 Programming Logic Controllers (PLC) currently operated as redundant data acquisition and control system at SLS launch pads and processing facility sites. The software application also simulates all the input/output (IO) signals acquired and generated in the SLS field via Mimic, a software platform commercially available to build simulation on IO signals for RSlogix-5000 PLC. All individual Java-based VDC-power unit simulators are concurrently integrated with the Mimic-based field IO simulation via Modbus communication protocol allowing a comprehensive simulation on GSP for SLS launch pads and processing facilities at NASA KSC. [ABSTRACT FROM AUTHOR]

The role of project managers has become crucial to thesuccessofsoftwaredevelopmentcompanies,itisimperativeto understand customer requirements while address business needs. In this context, the present work aims to present simulation as a strategy to mitigate fails in software development effort estimation. In doing so, it will activate an outstanding project manager's asset for risk management. This study used historical data of 181 project from a software company and the simulation package ARENA, to model and evaluation. Results point that the current method of project effort estimation - based on empirical feeling-based estimates of its employees - should be improved with the approach of continuous simulation. The modeling of this simulation provided a better understanding of efforts ranges applied in software developments on this company, and,mostimportant,theamountofrisktakenoneachtotaleffort estimative. This simulator attends the prerogatives of the project risk management area, being able to support decisions regarding schedule, resources bottlenecks and risk taken. [ABSTRACT FROM AUTHOR]

Open source has given us many innovations. This article provides an overview of the most important innovations and illustrates the impact that open source is having on the software industry and beyond. The main innovations of open source can be grouped into four categories: legal, process, tool, and business models. Probably the best known innovations are open source licenses, which also define the concept. Software becomes open source if users receive it under an open source license. Discusses each of these categories in detail and explains their significance for open source development. [ABSTRACT FROM AUTHOR]

The Polish economic transformation of the 1990s created an appetite for software that was only partially satisfied by piracy. This market was yet to be taken seriously by Western companies, so local developers stepped up to fill the void. They translated obscure foreign applications, created weird character encoding standards, and built complex business software from scratch, shaping the local IT market for years to come. [ABSTRACT FROM AUTHOR]

Growing demand for software has attracted the attention of the software development industry. Crowdsourced software development has provided a new method for the software industry to produce quality software based on an open-call format. Selecting an appropriate task to develop (developer-end) or evaluate (platform-end) is one of the primary problems in this type of open-call format. Receiving or assigning an improper task to an improper crowdsource (CS) developer does not only decrease the quality of the software deliverables, but also causes overburden on both the platform and the developers. To solve this problem, sorting the tasks based on the developers' human characteristics may increase task relevancy for developers, which can accelerate efficiency and lessen complexity. Thus, this paper has conducted an empirical experiment to measure the influence of personality on task selection based on the important characteristics of a task: money, time, and type. A total of 83 students from the University of Sindh voluntarily participated in four different short-duration rounds of task development using the developed CS platform. The personality types of the participants were measured based on the Myers-Briggs type indicator. In addition, a complex network technique called weighted degree centrality was applied to identify the most suitable personality for task sorting based on money or complexity attractions (i.e., time or type). Based on the results, it can be observed that personality has a significant relationship with task selection. For instance, developers with intuitive (N) and feeling (F) personality traits are primarily focused on the time duration of a project.

How realistic is the connectivity in a testbed? We answer this question by gathering connectivity measurements from 11 datasets, on both testbeds and real-world deployments. We propose a 5-point checklist to assess the realism of a testbed deployment and introduce a visual tool to evaluate the connectivity characteristics of a deployment. [ABSTRACT FROM AUTHOR]

Cloud services are very popular among enterprises; most businesses use multiple cloud services. At the same time, some enterprises acquire, merge, and partner with other companies. It is at that point where one party will need to access the other party?s resources in the cloud as well as its private cloud services. Due to these complex connections, cloud services must deal with different authentication protocols, multiple heterogeneous user stores, and legacy identity systems. As a result, implementing authentication in the cloud has become riskier and more complex. [ABSTRACT FROM AUTHOR]

Several word processing and desktop publishing innovations grew out of 1970s research by Larry Tesler and his collaborators at Stanford and Xerox PARC. One prototype was PUB, a markup language for print publishing. Another was Gypsy, a text editor with a cut/copy/paste command suite that became the de facto standard in desktop publishing and most other applications. [ABSTRACT FROM AUTHOR]