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Agile methods have been widely adopted by the industry and its teaching has seen a surge, particularly in the software development field. However, these methods have a number of limitations which affect product outcomes, such as the fact that many software development companies now use Scrum to get developers to work without interruption between iterations, rather than to maintain a sustainable rhythm. Agile experts have stated the importance of incorporating creativity into Scrum, and although there are several agile resources that help with the learning process, it seems essential to approach such learning from a practical point of view. Furthermore, none of these resources introduce creativity. In this paper, we present an educational resource in the form of a serious game that allows you to acquire all the key concepts of agile and creative methods. The game is based on the use of LEGO pieces to simulate a real project, applying the key concepts of the Scrum and Design Thinking frameworks in a gamified way. It was assessed in a professional training centre of computer science by using surveys through which participants evaluated their previous knowledge of agile and creativity methods. We analysed the improvement of these competences, as well as the general level of satisfaction with the game. After the game, the results showed that the participants' knowledge of the Scrum and Design Thinking frameworks had improved and that they were very satisfied with the whole experience. [ABSTRACT FROM AUTHOR]

Different software development approaches (SDAs) are developed with broad portfolios of development processes. Each of the approaches has certain exclusive principles, practices, thinking, and values, which are informally represented, implemented, and improperly institutionalized. Ontologies are developed for the representation, assessment, and adaptation of SDAs separately without having a shared terminology which may lead to terminological conflict and confusion affecting the simultaneous representation and implementation in software development industry and academia. The software engineering approaches does not consider and support sustainability as priority concern. However, the approaches have capabilities of supporting sustainable software development in different sustainability aspects. This research article aims for the designing and development of an integrated ontology of software engineering approaches (i.e., agile, lean, and green) named OntoSuSD (ontology for sustainable software development) to support sustainable software development knowledge, awareness, and implementation. The goal of OntoSuSD is to propose, design and develop a formal, generic, consistent, and shared knowledge base containing semantic terminology and description of concepts and relationships generated around the representation and implementation of lean, agile, and green approaches in software development processes, which will facilitate their simultaneous implementation and assessment for sustainable software development. The OntoSuSD is developed using practical ontology engineering methodology by reusing relevant ontologies and explicit concepts and properties are defined to fulfill knowledge requirements and representations of the domain. The OntoSuSD is evaluated, and results infer OntoSuSD has high ontological design, good domain coverage, potential applications and achieves purpose of the ontology development. [ABSTRACT FROM AUTHOR]

Application security is an important concern, and security activities to support software development lifecycle processes, such as specification, design, implementation, and testing are increasingly in need. Despite the plethora of knowledge available for secure software development in online and books, software systems are seldom secure as developers lack security knowledge. The primary reason for this paradox is the diversity and overwhelming nature of the available security knowledge. In this article, we propose to synthesize the well‐known secure software development practices for both linear and agile lifecycle models. Using the MediaWiki platform, we make this knowledge available to software developers and designers from a single source. [ABSTRACT FROM AUTHOR]

We live at an exciting time where software has become a dominant aspect of our everyday life. Although software provides opportunities for improving various aspects of our society, it also presents many challenges. One of them is development, deployment, and sustaining of high quality software on a broad scale. While agile methods (Scrum being one of the most prominent examples) ease the process, their popularity deteriorates the clarity and simplicity they were once meant to bring into software development. This article explores the synergy of Scrum and Essence, a domain model of software engineering processes, intending to become a common ground for software development methods, bringing clarity into the composition of methods from individual practices. This short communication motivates the interplay of Scrum and Essence, being accompanied with a set of videotutorials and 21 Scrum Essential cards to further guide more effective team's way of working. [ABSTRACT FROM AUTHOR]

Summary Though some software development teams are highly effective at delivering security, others either do not care or do not have access to security experts to teach them how. Unfortunately, these latter teams are still responsible for the security of the systems they build: systems that are ever more important to ever more people. We propose that a series of lightweight interventions, six hours of facilitated workshops delivered over three months, can improve a team's motivation to consider security and awareness of assurance techniques, changing its security culture even when no security experts are involved. The interventions were developed after an Appreciative Inquiry and Grounded Theory survey of security professionals to find out what approaches work best. We tested the interventions in a participatory action research field study where we delivered the workshops to three software development organizations and evaluated their effectiveness through interviews beforehand, immediately afterwards, and after twelve months. We found that the interventions can be effective with teams with limited or no security experience and that improvement is long‐lasting. This approach and the learning points arising from the work here have the potential to be applied in many development teams, improving the security of software worldwide. [ABSTRACT FROM AUTHOR]

The article discusses various topics related to agile software development including "Agile Methods for Safety-Critical Open Source Software," "User Experience Design and Agile Development: Managing Cooperation Through Articulation Work" and "Measuring the Flow in Lean Software Development."

This paper discusses the applicability of agile methods to aircraft embedded software development. It presents the main results of an experiment that combines agile practices from Scrum with model-based development and distributed development. The experiment consists of the development of an aircraft cockpit display system divided in five distributed teams. Three features are analysed and quantified, using the output artefacts of each team: the artefacts' quality, the adherence to agile methods, and the adherence to standard DO-178C. The main conclusion of the experiment is that there is a high correlation between the adherence to agile methods and the artefacts' quality, motivating the use of agile methods in aircraft industry. Also, the experiment evinced that agile methods does not specifically address the integration of distributed teams and the hardware/software integration. This lacuna affects the artefacts' quality. The results of the experiment emphasize the importance of concentrating future work in the proposal of specific agile practices for these activities. [ABSTRACT FROM AUTHOR]

The article discusses a study which investigated a mature Scrum team in a large organization and their interactions with the User Experience (UX) designers working on the same project. Particular focus is given to the difference between agile development and UX design methods for software development. Results of the study showed that ongoing articulation work by developers have led to cooperation between Agile developers and UX designers. Findings also revealed the themes which centre around the types of activities allowing the transformation of paper-based UX designs into working software.

The article discusses a study which examined whether agile methods are inappropriate for safety-critical software development. It cites the need for a process that ensures a high level of software reliability when introducing software technology in a life-dependent environment. It notes that agile methods are flexible and focus on continuous process management and code-level quality. Particular focus is given to experiences on the image-guided surgical toolkit (IGSTK), which is an open source software project that employs agile practices. It mentions the adoption of IGSTK by teaching hospitals and research labs.

This paper reports on a study of a software product line organization that has adopted agile software development to address process rigidity and slowing performance. Experience has showed that despite some impediments, this has become a valuable change to both the organization and its development process. The aim of this study is to identify and understand enabling factors of a combined process, and to understand their subsequent effects. Qualitative data are summarized and analyzed, giving insight into the actions taken, their effects that have emerged over time, and the enabling and contextual factors. The study concludes that a combined process is feasible, that the simplified approach makes the organization more flexible and thus capable of serving a volatile market with fast-changing technologies. This has also enabled the organization to collaborate better with external actors. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The ability to rapidly respond to customer interest and to effectively prioritize development effort has been a long-standing challenge for mass-market software intensive products. This problem is exacerbated in the context of software product lines as functionality may easily fall over software asset and organizational boundaries with consequent losses in efficiency and nimbleness. Some companies facing these problems in their product line respond with a new development process. In this paper we discuss the developments within a single case study, Intuit's Quickbooks product line that combined agile software development, design thinking and self-organizing teams in a successful approach, which provided a significant improvement in terms of responsiveness and accuracy of building customer value. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Software Product Line Engineering (SPLE) demands upfront long-term investment in (i) designing a common set of core-assets and (ii) managing variability across the products from the same family. When anticipated changes in these core-assets have been predicted with certain accuracy, SPLE has proved significant improvements. However, when large/complex software product line projects have to deal with changing market conditions, alternatives to supplement SPLE are required. Agile Software Development (ASD) may be an alternative, as agile processes harness change for the customer's competitive advantage. However, when the aim is to scale Agile projects up to effectively manage reusability and variability across the products from the same family, alternatives to supplement agility are also required. As a result, a new approach called Agile Product Line Engineering (APLE) advocates integrating SPLE and ASD with the aim of addressing these gaps. APLE is an emerging approach, which implies that organizations have to face several barriers to achieve its adoption. This paper presents a systematic literature review of experiences and practices on APLE, in which the key findings uncover important challenges about how to integrate the SPLE model with an agile iterative approach to fully put APLE into practice. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Despite a wide range of scaling frameworks available, large‐scale agile transformations are not straightforward undertakings. Few organizations have structures in place that fit the predefined workflows – while once one applies an off‐the‐shelf framework outside of its prescribed process, guidance quickly runs out. In this paper, we demonstrate how to instantiate a method configuration process using a lightweight experimental approach embedded in Action Research cycles. The proposed approach was developed to assist practitioners working on a multiple‐team project at Intel Technology Poland to find the right practices to continue their Nexus‐based transformation and integrate their in‐house method into the already established company structures, processes, and routines. In particular, it enabled identifying a series of challenges with scaled practices and coping with those. The challenges ranged from logistical problems, through poor availability of the Product Owner, to lackluster knowledge transfer and a wide array of communication/coordination issues at meetings. The study broadens the current body of knowledge within technology management and the scaled agile method‐tailoring domain. It indicates potential corrective actions that may be taken advantage of by entities that are not inclined, due to organizational constraints, to directly implement an off‐the‐shelf framework. Furthermore, our study demonstrates that a gradual transition to large‐scale agile at the project level (1) is possible with the preservation of traditional command‐and‐control management practices; (2) requires neither middle management involvement nor upfront investment; and (3) does not need to disrupt the continuous delivery of the product. [ABSTRACT FROM AUTHOR]

One central aspect of software engineering research is the transfer of the proposed approaches into industrial practice. In the past, a number of technology transfer approaches and experiences from technology transfer projects in software engineering have already been reported. However, many researchers still struggle to get their research results noticed by practitioners. To investigate what is important to practitioners, we conducted a mixed‐methods study that provides us with reliable quantitative data as well as deeper insights from qualitative data. Our results show that there is a mismatch between industry professionals' needs and commonly proposed technology transfer approaches in the software engineering field. For instance, collaboration between industry and academia as well as participation in empirical evaluations is not deemed important from an industry point of view. In contrast, industry professionals emphasize the use of company‐specific pilot projects conducted by industry and the need for experts to be available in every phase of technology transfer. [ABSTRACT FROM AUTHOR]

Design patterns are well‐known solutions to recurring design problems that are widely adopted in the software industry, either as formal means of communication or as a way to improve structural quality, enabling proper software extension. However, the adoption and correct instantiation of patterns is not a trivial task and requires substantial design experience. Some patterns are conceptually close or present similar design alternatives, leading novice developers to improper pattern selection, thereby reducing maintainability. Additionally, the mis‐instantiation of a GoF (Gang‐of‐Four) design pattern, leads to phenomena such as pattern grime or architecture decay. To alleviate this problem, in this work we propose an approach that can help software engineers to more easily and safely select the proper design pattern, for a given design problem. The approach relies on decision trees, which are constructed using domain knowledge, while options are conveyed to software engineers through an Eclipse Theia plugin. To assess the usefulness and the perceived benefits of the approach, as well as the usability of the tool support, we have conducted an industrial validation study, using various data collection methods, such as questionnaires, focus groups, and task analysis. The results of the study suggest that the proposed approach is promising, since it increases the probability of the proper pattern being selected, and various useful future work suggestions have been obtained by the practitioners. [ABSTRACT FROM AUTHOR]

Measuring and estimating the reusability of software components are important steps toward finding reusable candidates. Reuse of software components can aid in the reduction of the development cost of new software or maintenance of existing ones. However, assessing the reusability of software is a challenging task. Even if reusable candidates can be identified, developers will need to decide on the reuse strategies, that is, reuse as it is without any modification, or introduce new changes to the reusable candidate to fulfill requirements in the new environment or releases. Thus, the stability of the reusable candidates plays a pivotal role because it will influence the ease of reuse. Assessing and predicting the stability of potential reusable candidates becomes a significant and important step in software reuse. In this research, we propose to leverage on risk of change as a proxy to measure software stability, where the latter is also a proxy measure for software reuse. Based on experiments conducted on 29 open‐source software with different sizes and application types hosted on GitHub, we found that classes with high impact and high risk of change should be avoided from being reused due to their instability, while those classes with low impact and risk of change should be given priority. The proposed work can aid in providing a better understanding of the ease of reuse for software systems and can be used as a tool to assess its overall quality. [ABSTRACT FROM AUTHOR]

Previous studies have demonstrated the usefulness of employing automated static analysis tools (ASAT) and techniques to detect security bugs in software systems. However, these studies are usually focused on analyzing the effectiveness of the tools using open‐source tools based on C/C++ source code. The choice for making an appropriate decision on the most suitable tool for bug detection in Java code software remains a relatively unexplored domain. To address this deficiency, this study empirically evaluates eight widely used ASATs, namely, Findbug, PMD, YASCA, LAPSE+, JLint, Bandera, ESC/Java, and Java Pathfinder using the Juliet Test Suite (Test Suite v1.2). Additionally, we assessed the performance of the detection capabilities for the aforementioned bug detection tools using robust performance measures such as precision, recall, Youden index, and the OWASP web benchmark evaluation (WBE). The experimental results show that the tools obtain precision values ranging from 83% to 90.7% based on the studied datasets. Specifically, the Java Pathfinder achieves the best precision score of 90.7%, followed by YASCA and Bandera with a precision score of 88.7% and 83%, respectively. Similarly, Bandera, ESC/Java, and Java Pathfinder obtain a Youden index of 0.8, which indicates the effectiveness of the tools in detecting security bugs in Java source code. [ABSTRACT FROM AUTHOR]

The domain of cyber‐physical systems (CPS) has recently seen strong growth, for example, due to the rise of the Internet of Things (IoT) in industrial domains, commonly referred to as "Industry 4.0." However, CPS challenges like the strong hardware focus can impact modern software development practices, especially in the context of modernizing legacy systems. While microservices and DevOps have been widely studied for enterprise applications, there is insufficient coverage for the CPS domain. Our goal is therefore to analyze the peculiarities of such systems regarding challenges and practices for using and migrating towards microservices and DevOps. We conducted a rapid review based on 146 scientific papers, and subsequently validated our findings in an interview‐based case study with nine CPS professionals in different business units at Siemens AG. The combined results picture the specifics of microservices and DevOps in the CPS domain. While several differences were revealed that may require adapted methods, many challenges and practices are shared with typical enterprise applications. Our study supports CPS researchers and practitioners with a summary of challenges, practices to address them, and research opportunities. [ABSTRACT FROM AUTHOR]

Getting scientific software installed correctly and ensuring it performs well has been a ubiquitous problem for several decades now, which is compounded currently by the changing landscape of computational science with the (re‐)emergence of different microprocessor families, and the expansion to additional scientific domains like artificial intelligence and next‐generation sequencing. The European Environment for Scientific Software Installations (EESSI) project aims to provide a ready‐to‐use stack of scientific software installations that can be leveraged easily on a variety of platforms, ranging from personal workstations to cloud environments and supercomputer infrastructure, without making compromises with respect to performance. In this article, we provide a detailed overview of the project, highlight potential use cases, and demonstrate that the performance of the provided scientific software installations can be competitive with system‐specific installations. [ABSTRACT FROM AUTHOR]

User forums enable a large population of crowd‐users to publicly share their experience, useful thoughts, and concerns about the software applications in the form of user reviews. Recent research studies have revealed that end‐user reviews contain rich and pivotal sources of information for the software vendors and developers that can help undertake software evolution and maintenance tasks. However, such user‐generated information is often fragmented, with multiple viewpoints from various stakeholders involved in the ongoing discussions in the Reddit forum. In this article, we proposed a crowd‐based requirements engineering by valuation argumentation (CrowdRE‐VArg) approach that analyzes the end‐users discussion in the Reddit forum and identifies conflict‐free new features, design alternatives, or issues, and reach a rationale‐based requirements decision by gradually valuating the relative strength of their supporting and attacking arguments. The proposed approach helps to negotiate the conflict over the new features or issues between the different crowd‐users on the run by finding a settlement that satisfies the involved crowd‐users in the ongoing discussion in the Reddit forum using argumentation theory. For this purpose, we adopted the bipolar gradual valuation argumentation framework, extended from the abstract argumentation framework and abstract valuation framework. The automated CrowdRE‐VArg approach is illustrated through a sample crowd‐users conversation topic adopted from the Reddit forum about Google Map mobile application. Finally, we applied natural language processing and different machine learning algorithms to support the automated execution of the CrowdRE‐VArg approach. The results demonstrate that the proposed CrowdRE‐VArg approach works as a proof‐of‐concept and automatically identifies prioritized requirements‐related information for software engineers. [ABSTRACT FROM AUTHOR]

Increasingly, the model driven engineering (MDE) community is paying more attention to the techniques offered by the machine learning (ML) community. This has led to the application of ML techniques to MDE related tasks in hope of increasing the current benefits of MDE. Nevertheless, there is a lack of empirical experiments that evaluate the benefits that ML brings to MDE. In this work, we evaluate the benefits of empowering model engineers of model‐driven development (MDD) with an ML classifier. To do this, we tackled how to embed the ML classifier as part of the MDD. Then, this was evaluated using two different real industrial cases. Our results show that despite the ML part takes an extra effort, the use of the ML classifier pays off in terms of the quality results, the perceived usefulness, and intention to use. [ABSTRACT FROM AUTHOR]

Developing sustainable software for the scientific community requires expertise in software engineering and domain science. This can be challenging due to the unique needs of scientific software, the insufficient resources for software engineering practices in the scientific community, and the complexity of developing for evolving scientific contexts. While open‐source software can partially address these concerns, it can introduce complicating dependencies and delay development. These issues can be reduced if scientists and software developers collaborate. We present a case study wherein scientists from the SuperNova Early Warning System collaborated with software developers from the Scalable Cyberinfrastructure for Multi‐Messenger Astrophysics project. The collaboration addressed the difficulties of open‐source software development, but presented additional risks to each team. For the scientists, there was a concern of relying on external systems and lacking control in the development process. For the developers, there was a risk in supporting a user‐group while maintaining core development. These issues were mitigated by creating a second Agile Scrum framework in parallel with the developers' ongoing Agile Scrum process. This Agile collaboration promoted communication, ensured that the scientists had an active role in development, and allowed the developers to evaluate and implement the scientists' software requirements. The collaboration provided benefits for each group: the scientists actuated their development by using an existing platform, and the developers utilized the scientists' use‐case to improve their systems. This case study suggests that scientists and software developers can avoid scientific computing issues by collaborating and that Agile Scrum methods can address emergent concerns. [ABSTRACT FROM AUTHOR]

Among current IT work cultures, DevOps stands out as one of the most adopted worldwide. The focus of this culture is on bridging the gap between development and operations teams, enabling collaborative effort toward quickly producing software, without sacrificing its quality and support. DevOps is used to tackle a variety of issues; as such, there are differing benefits reported by authors when performing their analysis. For this research, we aim to reach consensus on the DevOps benefits reported in existing literature. To accomplish this objective, two systematic literature reviews. The first intends to find all benefits reported in the literature, while the second review will be used to map the benefits found in the first one with DevOps implementation case studies, providing empirical evidences of each benefit. To strengthen the results, the concept‐centric approach is used. During this research it was possible to observe that the most reported benefits are aligned with the DevOps premises of better collaboration between developers and operators, delivering software and products quicker. Based on DevOps implementation case studies, most reported benefits include a faster time to market as well as improvements in synergy and automation. Less reported benefits include a reduction in failed changes and security issues. [ABSTRACT FROM AUTHOR]

Software effort estimation accuracy is a key factor in effective planning, controlling, and delivering a successful software project within budget and schedule. The overestimation and underestimation both are the key challenges for future software development, henceforth there is a continuous need for accuracy in software effort estimation. The researchers and practitioners are striving to identify which machine learning estimation technique gives more accurate results based on evaluation measures, datasets and other relevant attributes. The authors of related research are generally not aware of previously published results of machine learning effort estimation techniques. The main aim of this study is to assist the researchers to know which machine learning technique yields the promising effort estimation accuracy prediction in software development. In this article, the performance of the machine learning ensemble and solo techniques are investigated on publicly and non‐publicly domain datasets based on the two most commonly used accuracy evaluation metrics. We used the systematic literature review methodology proposed by Kitchenham and Charters. This includes searching for the most relevant papers, applying quality assessment (QA) criteria, extracting data, and drawing results. We have evaluated a state‐of‐the‐art accuracy performance of 35 selected studies (17 ensemble, 18 solo) using mean magnitude of relative error and PRED (25) as a set of reliable accuracy metrics for performance evaluation of accuracy among two techniques to report the research questions stated in this study. We found that machine learning techniques are the most frequently implemented in the construction of ensemble effort estimation (EEE) techniques. The results of this study revealed that the EEE techniques usually yield a promising estimation accuracy than the solo techniques. [ABSTRACT FROM AUTHOR]

SUMMARY Smalltalk is an exciting object-oriented language in which even primitive values are uniformly handled as normal objects described by classes that one can browse and extend. Smalltalk was born during the seventies, but the ideas behind currently available implementations are still modern and innovative. Smalltalk benefits from being a highly expressive language in which complex and powerful systems can emerge from the composition of simple building blocks. Thanks to its dynamic nature, fast prototyping and agile software development are made possible. Smalltalk also benefits from having powerful meta-programming facilities. A program is able to query and to change its own structure and behavior. Smalltalk is not only a language but also an interactive system that is implemented in Smalltalk and that can be customized according to users needs. This special issue presents four extended versions of research papers from the third International Workshop on Smalltalk Technologies (IWST) that was organized at Edinburgh on September 2011. Johan Fabry et al. presented Phantom, an aspect language that includes recent research results in aspect interactions and reentrancy control. Phantom is designed to be optimized and compiled where possible., Increasing use of reflection and meta-programming techniques in real world applications underlines the need for more dynamic approaches. New approaches have shifted to object-specific reuse. Jorge Ressia et al. proposed a new abstraction called a talent, which models features that are shared between objects of different class hierarchies., Martin Dias et al. presented Fuel, a general-purpose object serializer that focuses on speed, through a compact binary format and an efficient pickling algorithm. Fuel serializes any object, thus having a full-featured language-specific format., Redesign of nontrivial software is often a challenge. Ciprian Teodorov et al. addressed physical-design automation and presented a methodological approach relying on model-driven engineering. Also, they summarized some lessons learned from the incremental redesign of Madeo, a toolkit that targets field-programmable gate array design automation., The goal of the IWST workshop series is to create and foster a forum around advances or experiences in Smalltalk. Each IWST workshop is organized as a collocated event of the European Smalltalk User Group annual conference. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Measuring and estimating the reusability of software components is important towards finding reusable candidates. Researchers have shown that software metrics can be effectively used to assess software reusability. This work provides a systematic literature review to investigate the main factors that influence software reusability and how these identified factors can be quantified using software metrics. This paper also investigates tool availability of the identified software metrics. Based on the extensive study, we narrowed down 44 factors that could positively or negatively affect the reusability of software systems. In term of software metrics, we report our findings through five main families of metrics, namely coupling, cohesion, complexity, inheritance, and size. We found that most of the metrics examine reusability at the class‐level, and the availability of software tools is limited. Furthermore, not all reusability affecting factors are equally impactful to assess the reusability of software components. While existing studies often discussed the impact of complexity towards software reusability, we found that only a handful of complexity metrics were meant for assessing reusability. We have identified several open challenges and gaps in the area, in particular lack of quantifiable measurement for reusability, limited software tools, and limited metrics that directly measure reusability. [ABSTRACT FROM AUTHOR]

Summary: We discuss the potential benefits, requirements, and implementation challenges of a security‐by‐design approach in which an integrated development environment plugin assists software developers to write code that complies with secure coding guidelines. We discuss how such a plugin can enable a company's policy‐setting security experts and developers to pass their knowledge on to each other more efficiently, and to let developers more effectively put that knowledge into practice. This is achieved by letting the team members develop customized rule sets that formalize coding guidelines and by letting the plugin check the compliance of code being written to those rule sets in real time, similar to an as‐you‐type spell checker. Upon detected violations, the plugin suggests options to quickly fix them and offers additional information for the developer. We share our experience with proof‐of‐concept designs and implementations rolled out in multiple companies, and present some future research and development directions. [ABSTRACT FROM AUTHOR]

Summary: The proliferation of DevOps enables significant acceleration and automation of the delivery and deployment of massive software products. Unfortunately, the development of supporting documents that is vital for large‐scale software systems in many cases does not keep pace with the rhythm of feature delivery using DevOps in practice, which becomes the bottleneck for many software organizations to deliver full value to the customers as claimed by the DevOps. This paper proposes, implements, and evaluates an integrated approach, DevDocOps, for continuous automated documentation, in particular for DevOps. With DevDocOps, supporting documents are created along with the development process simultaneously by various roles within a DevOps project, which largely guarantees the accuracy and integrity of documents as well as significantly increases their delivery speed. Within an established delivery chain, a set of templates are created to collect and transform the required information from its origin to the target documents for delivery. A real system, iDoc, is implemented to map, collect, and synthesize the information from document templates and automate the documentation process. DevDocOps has been successfully adopted in a top‐tier global telecommunication enterprise to support more than 5000 users with different roles related to documentation. The lag time between the releases of the product version and its supporting document has been shortened from 1 to 2 months on average to less than 2 days. DevDocOps extends the scope of DevOps and enhances the value delivery by supporting continuous documentation and bridges the gap between feature delivery and document delivery with automation. [ABSTRACT FROM AUTHOR]

Summary: Integration frameworks are specialized software tools built and adapted to facilitate the design and implementation of integration solutions. An integration solution allows for the reuse of applications from the software ecosystem of companies to support their business processes. There are several open‐source integration frameworks available on the market designed to operate in a business context to manipulate structured data; however, increasingly, they are required to deal with unstructured and large volumes of data, thus requiring effort to adapt these frameworks to work with unstructured and large volume of data. Choosing the framework, which is the easiest to be adapted, is not a trivial task. In this article, we review the newest stable versions of four open‐source integration frameworks by analyzing how they have evolved regarding their adaptive maintainability over five years. We rank them according to their maintainability degree and compare past and current versions of each framework. To encourage and enable researchers and developers to replicate our experiments, with the aim of verifying our findings, and to experiment with new versions of the integration frameworks analyzed, we detail the experimental protocol used while also having made all the required software involved available on the Web. [ABSTRACT FROM AUTHOR]

Summary: This paper presents the framework of cloud‐based software test data generation service (CSTS) that caters to cost‐effective test data generation service in a cloud environment. In contrast to existing conventional or cloud‐based testing frameworks, CSTS has a number of unique benefits. First, CSTS is designed to facilitate test data generation in minimum time and cost. Second, unlike existing frameworks which mandates clients to opt for resources to test their jobs, CSTS guides customer for selecting best cluster configuration in order to minimize the cost. While the existing models do not provide any solution for trust establishment in cloud computing services, CSTS delivers it by implementing security mechanism with the provision of role based access control. The security mechanism proposed in this paper ensures the protection of data and code of different users. Third, CSTS provides a mathematical pricing model to fulfill the expectations of customers and also to maximize the net profit of service providers. Cloud service request model has also been designed that postulates service level agreements between customers and service providers. We have evaluated, compared, and analyzed our framework and have found that it outperforms other existing cloud‐based frameworks. [ABSTRACT FROM AUTHOR]

Summary: This systematic literature review paper investigates the key techniques employed to identify smells in different paradigms of software engineering from object‐oriented (OO) to service‐oriented (SO). In this review, we want to identify commonalities and differences in the identification of smells in OO and SO systems. Our research method relies on an automatic search from the relevant digital libraries to find the studies published since January 2000 on smells until December 2017. We have conducted a pilot and author‐based search that allows us to select the 78 most relevant studies after applying inclusion and exclusion criteria. We evaluated the studies based on the smell detection techniques and the evolution of different methodologies in OO and SO. Among the 78 relevant studies selected, we have identified six different studies in which linguistic source code analysis received less attention from the researchers as compared to the static source code analysis. Smells like the yo‐yo problem, unnamed coupling, intensive coupling, and interface bloat received considerably less attention in the literature. We also identified a catalog of 30 smells infrequently reported for SO systems and that require further attention. Moreover, a suite of 20 smells reported for SO systems can also be detected using static source code metrics in OO. Finally, our review highlighted three major research trends that are further subdivided into 20 research patterns initiating the detection of smells toward their correction. [ABSTRACT FROM AUTHOR]

Summary: Continuous integration (CI) is a software development practice that has been gaining increasing popularity in the last few years. However, we still miss a collection of experiences regarding how software developers perceive the idea of CI, in terms of its fundamental concepts, the reasons that motivate the adoption of this practice, the reasons for build breakage, and the benefits and problems related to CI. To shed light on this direction, we conducted a user survey with 158 CI users. Through a mostly qualitative investigation, we produce a list of findings that are not always obvious. For instance, we observed that (1) developers are not sure whether a job failure represents a failure or not; (2) inadequate testing is the most common technical reason related to build breakage, whereas lack of time plays a role on the social reasons; and (3) although some respondents reported that CI systems increase the confidence that the code is in a known state, some respondents also reported that there is a false sense of confidence when blindly trusting tests. This empirical study is particularly relevant to those interested in better understanding and fostering CI practices either in an open‐source or industrial setting. [ABSTRACT FROM AUTHOR]

Summary: Placement of methods is one of the most important design activities for any object‐oriented application in terms of coupling and cohesion. Due to method misplacement, the application becomes tightly coupled and loosely cohesive, reflecting inefficient design. Therefore, a feature envy code smell emerges from the application, as many methods use more features of other classes than its current class. Hence, development and maintenance time, cost, and effort are increased. To refactor the code smell and enhance the design quality, move method refactoring plays a significant role through grouping similar behaviors of methods. This is because the manual refactoring process is infeasible due to the necessity of huge time and most of the existing techniques consider only coupling‐based and/or cohesion‐based information of nonstatic entities (methods and attributes) for the recommendation. However, this article proposes an approach that uses contextual information, based on information retrieval techniques, along with dependency (coupling and cohesion)‐based information of the application for the recommendation. In addition, the approach incorporates both static and nonstatic entities in the recommendation process. For validation, the approach is applied on seven well‐known open source projects. The results of the experimental evaluation indicate that the proposed approach provides better results with an average precision of 18.91%, a recall of 69.91%, and an F‐measure of 29.77% than the JDeodorant tool (a widely used eclipse plugin for refactorings). Moreover, this article establishes several relationships between the accuracy of the approach and project standards and sizes. [ABSTRACT FROM AUTHOR]

Summary: Mockups are widely used to elicit and validate user requirements in web applications, and several intuitive tools have been developed in recent years, actively involving the end user in the requirements solicitation process. However, most current web development approaches and tools discard mockups after the information‐gathering process, abandoning the opportunity to exploit underlying information in them for autogenerating functional web applications. To overcome this limitation, we have devised a method for deriving the database schema and the logic of the web application from the information contained within mockups. In particular, the method gathers clues on how to organize the data and the control flow of the web application by analyzing the structure and relationships of the widgets in the mockup. Based on the proposed method, we have implemented a tool supporting the generation of web applications abiding by the model‐view‐controller architectural pattern. The tool has been evaluated by involving several end users in the development of web applications for different domains. [ABSTRACT FROM AUTHOR]

The identification of performance issues and the diagnosis of their root causes are time-consuming and complex tasks, especially in clustered environments. To simplify these tasks, researchers have been developing tools with built-in expertise for practitioners. However, various limitations exist in these tools that prevent their efficient usage in the performance testing of clusters (e.g. the need of manually analysing huge volumes of distributed results). In a previous work, we introduced a policy-based adaptive framework (PHOEBE) that automates the usage of diagnosis tools in the performance testing of clustered systems, in order to improve a tester's productivity, by decreasing the effort and expertise needed to effectively use such tools. This paper extends that work by broadening the set of policies available in PHOEBE, as well as by performing a comprehensive assessment of PHOEBE in terms of its benefits, costs and generality (with respect to the used diagnosis tool). The performed evaluation involved a set of experiments in assessing the different trade-offs commonly experienced by a tester when using a performance diagnosis tool, as well as the time savings that PHOEBE can bring to the performance testing and analysis processes. Our results have shown that PHOEBE can drastically reduce the effort required by a tester to do performance testing and analysis in a cluster. PHOEBE also exhibited consistent behaviour (i.e. similar time-savings and resource utilisations), when applied to a set of commonly used diagnosis tools, demonstrating its generality. Finally, PHOEBE proved to be capable of simplifying the configuration of a diagnosis tool. This was achieved by addressing the identified trade-offs without the need for manual intervention from the tester. [ABSTRACT FROM AUTHOR]

The literature on the challenges of and potential solutions to architecting cloud-based systems is rapidly growing but is scattered. It is important to systematically analyze and synthesize the existing research on architecting cloud-based software systems in order to build a cohesive body of knowledge of the reported challenges and solutions. We have systematically identified and reviewed 133 papers that report architecture-related challenges and solutions for cloud-based software systems. This paper reports the methodological details, findings, and implications of a systematic review that has enabled us to identify 44 unique categories of challenges and associated solutions for architecting cloud-based software systems. We assert that the identified challenges and solutions classified into the categories form a body of knowledge that can be leveraged for designing or evaluating software architectures for cloud-based systems. Our key conclusions are that a large number of primary studies focus on middleware services aimed at achieving scalability, performance, response time, and efficient resource optimization. Architecting cloud-based systems presents unique challenges as the systems to be designed range from pervasive embedded systems and enterprise applications to smart devices with Internet of Things. We also conclude that there is a huge potential of research on architecting cloud-based systems in areas related to green computing, energy efficient systems, mobile cloud computing, and Internet of Things. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY Dependency structural matrix (DSM) is an approach originally developed for process optimization. It has been successfully applied to identify software dependencies among packages and subsystems. A number of algorithms have been proposed to compute the matrix so that it highlights patterns and problematic dependencies between subsystems. However, existing DSM implementations often miss important information to fully support reengineering effort. For example, they do not clearly qualify and quantify problematic relationships, information that is crucial to support remediation tasks. We propose enriched DSM (eDSM), which provides small-multiple views and micro-macro-readings by adding fine-grained information in each cell of the matrix. Each cell is enriched with contextual information about (i) the type of dependencies (inheritance, class reference, etc.), (ii) the proportion of referencing entities, and (iii) the proportion of referenced entities. We distinguish independent cycles and stress potentially simple fixes for cycles by using coloring information. This work is language independent and has been implemented on top of the Moose software analysis platform. In this paper, we expand our previous work. We improved the cell content information view on the basis of user feedback and performed multiple validations: two different case studies on Moose and Seaside software; one user study for validating eDSM as a usable approach for developers. Solutions to problems identified with eDSM have been performed and retrofitted in analyzed software. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The article discusses a study which investigated the flow of lean software development. It notes that agile and lean software development is designed as a response to customer needs. It cites increase throughout and reduce lead-time as of the goals of novel measures connected to the flow diagrams. Particular focus is given to the case of Ericsson AB in Sweden, which illustrates the influence of measures on decision making. Results showed that the measures have been useful for practitioners in seeing the progress of complex products where tasks are executed in parallel.

Background: Software product lines and Agile methods have been an effective solution for dealing with the growing complexity of software and handling competitive needs of software organizations. They also share common goals, such as improving productivity, reducing time-to-market, decreasing development costs and increasing customer satisfaction. There has been growing interest in whether the integration of Agile and SPL could provide further benefits and solve many of the outstanding issues surrounding software development. Objective: This study investigates the state-of-the-art in Agile SPL approaches, while identifying gaps in current research and synthesizing available evidence. It also provides a basis for a deeper understanding of the issues involved in the integration of Agile and SPL. Method: A mapping study was undertaken to analyze the relation between Agile and SPL methods. A set of four research questions were defined in which the 32 primary studies were evaluated. Results: This study provides insights into the integration of Agile and SPL approaches, it identifies the current gaps in the research, synthesize the available evidence and propose specific Agile methods and practices for integration in SPL. Conclusions: In general, few studies describe the underlying Agile principles being adopted by proposed Agile SPL solutions. The most common Agile practices proposed by the studies came from the XP and Scrum methods, particularly in the pro-active SPL strategy. We identify certain Agile methods that are being overlooked by the Agile SPL community, and propose specific SPL practices areas suitable for adoption of Agile practices. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Refactoring is a widely accepted technique to improve the software quality by restructuring its design without changing its behavior. In general, a sequence of refactorings needs to be applied until the quality of the code is improved satisfactorily. In this case, the final design after refactoring can vary with the application order of refactorings, thereby producing different quality improvements. Therefore, it is necessary to determine a proper refactoring schedule to obtain as many benefits as possible. However, there is little research on the problem of generating appropriate schedules to maximize quality improvement. In this paper, we propose an approach to automatically determine an appropriate schedule to maximize quality improvement through refactoring. We first detect code clones that are suitable for refactoring and generate the most beneficial refactoring schedule to remove them. It is straightforward to select the best from the exhaustively enumerated schedules. However, such a technique becomes NP-hard, as the number of available refactorings increases. We apply a genetic algorithm (GA) to generate the best refactoring schedule within a reasonable time to cope with this problem. We compare the GA-based approach with manual scheduling, greedy heuristic-based, and exhaustive approaches for four open systems. The results show that the proposed GA-based approach generates more beneficial schedules than the others. Copyright © 2010 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]