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Software ecosystems are considered the natural evolution of software product lines. A software ecosystem provides a (software) product within a particular business and organizational context that supports the exchange of activities and services within a domain. However, the increasing degree of autonomy demanded by software ecosystems is elevating the system response to end users, while the existing software ecosystem architectures are not well prepared to deal with the dynamicity of context changes and autonomous behavior needs. In order to provide a transition toward an increased level of autonomy, in this article, we introduce the notion of autonomous dynamic ecosystems as representative of those software ecosystems able to support dynamic, smart, and autonomous features demanded by modern software systems. In this work, we further investigate and provide evidence of four industrial examples that have fully embodied the principles of autonomous dynamic ecosystems, and we characterize the main features and technology requirements of this kind of new ecosystems. [ABSTRACT FROM AUTHOR]

Motivated by the rising environmental protection awareness and the importance of green product design, in this article we develop two models to investigate the quality and greenness decisions and product line choices of a green manufacturer as well as the corresponding impact of product line length on environmental performance. In our models, both the manufacturer and consumers show environmental responsibility behaviors. We find that the manufacturer extends the product line when the unit fit cost, the green cost, the quality cost, the market scale of low-segment consumers, and the environmental responsibility level (or unit environmental cost) are low. In the presence of two products with different market positioning, our analysis reveals that: first, owing to the consumer's self-selection behavior, product quality and greenness may be distorted from the efficient quality and greenness; second, product line extension may improve both the environmental performance and the manufacturer's utility, i.e., achieving a win–win outcome; and third, a higher unit environmental cost (environmental responsibility level or a longer product line) will improve the environmental performance if the unit environmental cost is high. In the continuous green valuation setting, interestingly, we find different results that the manufacturer with a high environmental responsibility level may extend its product line, and the environmental performance increases with the unit environmental cost in the single-product case. [ABSTRACT FROM AUTHOR]

Software companies frequently customize and extend product lines in multiple projects concurrently to quickly deliver solutions to customers. Engineers use a distributed and feature-oriented development process, commonly supported by version control systems to track implementation-level changes. For instance, feature branches are widely used to add new or modify existing features. However, when merging back features to the product line, the information about feature-to-code mappings is usually lost. Furthermore, the granularity of merging is limited to branches, making it hard to extract and merge selected individual features from one product to another. This paper thus presents feature-oriented clone and pull operations for distributed development, which are implemented in the FORCE2 platform. Our evaluation uses variants of the ArgoUML product line to investigate the correctness and performance of our approach. The results show that the feature-oriented operations work with high precision and recall for different cases of feature interactions, also when feature implementations are scattered across many locations in the source code. The performance measurements demonstrate that the operations can be integrated in the typical workflows of engineers. [ABSTRACT FROM AUTHOR]

At the beginning of the testing phase and before the deployment phase of a project's development cycle, we need to predict files with a high chance of change. Software products are always prone to change due to several reasons, including fixing errors or improvements. In this work, we used the Eclipse (releases from 2.0 to 3.5) to investigate how prediction models can perform when learning from a release and predicting in the subsequent one, which contains new files that models have not seen. We compared the performance of these models with models that are trained and tested on the same release. We found no differences between predicting the same release or subsequent release on two pre Europa releases. Predicting change in newly created files helps improve maintenance planning for software project managers and reduce cost. It will also help to enhance the quality of software by improving the practices of developers. This study used the Adaptive Boost classifier with the decision tree J48 algorithm and combined it with the re‐sampling method. We find this to be better than using a meta classifier alone or combine the re‐sampling with the standard classification. We compared our results with related works and found that our results are outperforming. [ABSTRACT FROM AUTHOR]

The specifications of a certain domain are addressed by a portfolio of software products, known as Software Product Line (SPL). Feature Model (FM) supports domain engineering by modeling domain knowledge along with variability among SPL. The quality of FM is one of the significant factors for the successful SPL in order to attain high quality software products. However, the benefits of SPL can be reduced due to defects in FM. Dead Feature (DF) is one of such defects. Several approaches exist in the literature to detect defects due to DF in FMs. But only a few can handle their sources and solutions which are cumbersome and difficult to understand by humans. An ontological knowledge-based method for handling defects due to DF in FMs is described in this paper. It specifies FM in the form of ontology-based knowledge representation. The rules based on first-order logic are created and implemented using Prolog to detect defects due to DF with sources as well as suggest solutions to resolve these defects. A case study of the product line available on SPLOT repository is utilized for illustrating the proposed work. The experiments are performed with real-world FMs of varied sizes from SPLOT and FMs created with the FeatureIDE tool. The results prove the efficiency, scalability (up to model with 32,000 features) and accuracy of the presented method. Therefore, reusability of DFs free knowledge enables deriving defect free products from SPL and eventually enhances the quality of SPL. [ABSTRACT FROM AUTHOR]

Copyright of Elektronik Industrie is the property of Hüthig GmbH and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Elektronik Industrie is the property of Hüthig GmbH and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The success of a freemium model depends on the number of customers who purchase the premium version in the presence of the free version. The authors investigate the strategy of extending the premium product line to spur demand for the existing premium version. Extending the results of the standard product line model is insufficient in such cases because of the conceptual nuances in a freemium context. The authors conduct a randomized field experiment with an online content provider that offers book titles in a PDF version for free and sells the paperback version for a premium. The authors show that paperback titles accompanied by an additional premium version, either in e-book or hardcover format, have higher sales than those in the control condition. The positive impact on paperback sales is stronger for titles that are more popular or cheaper, and the effect of introducing the e-book version is higher when the e-book price is closer to the paperback price. By analyzing individual customer choices, the authors identify the existence of the compromise effect and the attraction effect in the extended product line setting, a significant contribution not only in the freemium context but also to the product line literature. [ABSTRACT FROM AUTHOR]

Software product line engineering emerged as an effective approach for the development of families of software‐intensive systems in several industries. Although its use has been widely discussed and researched, there are still several open challenges for its industrial adoption and application. One of these is how to efficiently develop and reuse shared software artifacts, which have dependencies on the underlying electrical and hardware systems of products in a family. In this work, we report on our experience in tackling such a challenge in the railway industry and present a model‐based approach for the automatic generation of test scripts for product variants in software product lines. The proposed approach is the result of an effort leveraging the experiences and results from the technology transfer activities with our industrial partner Alstom SA in Sweden. We applied and evaluated the proposed approach on the Aventra software product line from Alstom SA. The evaluation showed that the proposed approach mitigates the development effort, development time, and consistency drawbacks associated with the traditional, manual creation of test scripts. We performed an online survey involving 37 engineers from Alstom SA for collecting feedback on the approach. The result of the survey further confirms the aforementioned benefits. [ABSTRACT FROM AUTHOR]

This paper develops a flexible recipe for identifying unobserved input allocations, as well as quantity- and revenue-based total factor productivity (TFP) across product lines, for multiproduct producers, using demand- and supply-side information. Applying variants of this recipe to a panel of plants manufacturing machinery in India from 2000–2007 yields sizable within-plant TFP differences. Removing an average plant's lowest-performing product increases the unweighted average of plant-level revenue-based productivity by 10%–65%. A 1 standard deviation decline in product-level revenue-based TFP generates around a 6 percentage point increase in the probability of dropping that product. [ABSTRACT FROM AUTHOR]

This paper studies two fundamental questions regarding probabilistic selling in vertically differentiated markets: When is it profitable and how does one design it optimally? For the first question, we identify an important but overlooked economic mechanism driving probabilistic selling in vertically differentiated markets: the convexity of consumer preferences. In stark contrast to the literature finding that probabilistic selling is never profitable except in the presence of certain capacity constraint or consumer bounded rationality, we find that with many alternative utility functions capable of representing convex preference, probabilistic selling is always profitable. For the second question, we study the optimal strategy of probabilistic selling, including the design and price of the probabilistic good and the prices of the component goods. We show that under some technical conditions, the optimal price of the high‐quality component good increases while the optimal price of the low‐quality component good decreases upon the introduction of probabilistic selling, thereby increasing the market coverage and the economic efficiency without launching an actual new product line. To further illustrate the design of probabilistic selling, we use an example based on the canonical utility function, which is widely used in the economics literature on vertical product differentiation. We derive a closed‐form solution to the problem of optimal probabilistic selling. We also take advantage of the analytical tractability of the canonical utility to further explore the design of multiple probabilistic goods. [ABSTRACT FROM AUTHOR]

Context: Dynamic software product lines (DSPLs) have considerably increased their adoption for variability management for self-adaptive systems. The most widely used models for managing the variability of DSPLs are the MAPE-K control loop and context-aware feature models (CFMs). Aim: In this paper, we review and synthesize evidence of using variability constraint approaches, methodologies, and challenges for DSPL. Method: We conducted a systematic mapping, including three research questions. This study included 84 papers published from 2010 to 2021. Results: The main results show that open-dynamic variability shows a presence in 57.1% of the selected papers, and on the other hand, closed-dynamic variability appears in 38.1%. The most commonly used methodology for managing a DSPL environment is based on proprietary architectures (60.7%), where the use of CFMs predominates. For open-dynamic variability approaches, the MAPE-K control loop is mainly used. The main challenges in DSPL management are based on techniques (28.6%) and open variation (21.4%). Conclusions: Open-dynamic variability has prevailed over the years as the primary approach to managing variability in DSPL, where its primary methodology is the MAPE-K control loop. Response RQ3 requires further review. [ABSTRACT FROM AUTHOR]

In this article, we give a formula for the generalization of the binomial coefficient to the complex numbers as a linear combination of sinc functions. We then give a general formula to compute the integral on the real line of the product of the binomial coefficient and a given function, which, in some cases, turns out to be equal to the series of their values on the integers. Finally, we establish a list of identities obtained by applying these formulas. [ABSTRACT FROM AUTHOR]

Balanced systems have extensive applications in engineering fields such as new energy storage and aeronautics. The reliability analysis of such systems has been reported in literature. However, most existing studies focus on the binary-state situation, and research on multi-state cases and the relevant rebalancing mechanism is still limited. To fill this gap, a multi-state k-out-of-n:F balanced system with a rebalancing mechanism is studied in this paper. Both components and the system have multiple states, and all the components are required to be working in similar states to ensure that the system operates in a balanced condition. It means that the difference between the maximum and minimum component states should not exceed a threshold. Otherwise, the system is out of balance and should be rebalanced by identifying the components whose states are too high and adjusting them into lower states. A continuous-time Markov process is used to describe the component operation process and relevant reliability indices are derived accordingly. An age maintenance strategy is also proposed and an optimization model is constructed to obtain the optimal results. Finally, numerical examples based on a product line balancing problem are presented to demonstrate the application of the proposed model. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Computer Science & Technology (JCS&T) is the property of Journal of Computer Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose: This paper studies how multichannel retailers choose the product quality level and decide which attribute to make prominent in their physical store in a competitive environment. Design/methodology/approach: This paper develops a game theoretic model, in which multichannel retailers' decisions are made in three stages. Using prominent experiential attributes (e.g. functionality) in their offline store and product quality decisions, multichannel retailers are capable of transferring the sales between different channels. Findings: This analysis shows that making different attributes prominent in their physical store may be an equilibrium, and each multichannel retailer chooses the highest quality level for the prominent attribute. However, the prominent attribute of the highest quality level is not always optimal. Under certain conditions, multichannel retailers may make the experiential attribute prominent in their respective physical stores, which can result in equilibrium. Practical implications: The results indicate that multichannel retailers should avoid blindly highlighting high-quality attributes in a competitive environment, or falling into price completion. Originality/value: From the perspective of prominent attributes, this study designs the optimal product line based on channel characteristics. The results of the research can provide practical implications for multichannel retailers to increase sales. [ABSTRACT FROM AUTHOR]

The increasing rate of oral squamous cell carcinoma (OSCC) and the undesirable side effects of anticancer agents have enhanced the demand for the development of efficient, detectable, and targeted anticancer systems. Saponins are a diverse family of natural glycosides that have recently been evaluated as an effective compound for the targeted therapy of squamous cell carcinoma. Due to their porous nature and stable structure, metal–organic frameworks (MOFs) are a well-known substance form for various biological applications, such as drug delivery. In this study, we fabricated a novel hybrid, highly porous and low-toxic saponin-loaded nanostructure by modifying graphene oxide (GO)/reduced GO (rGO) with aluminum fumarate (AlFu) as MOF core–shell nanocomposite. The characterization of the nanostructures was investigated by FTIR, TEM, EDX, FESEM, and BET. MTT assay was used to investigate the anticancer activity of these compounds on OSCC and PDL normal dental cells. The effect of the nanocomposites on OSCC was then investigated by studying apoptosis and necrosis using flow cytometry. The GO/rGO was decorated with a saponin–AlFu mixture to further investigate cytotoxicity. The results of the MTT assay showed that PDL cells treated with AlFu–GO–saponin at a concentration of 250 μg/mL had a viability of 74.46 ± 16.02%, while OSCC cells treated with this sample at a similar concentration had a viability of only 38.35 ± 19.9%. The anticancer effect of this nanostructure on OSCC was clearly demonstrated. Moreover, the number of apoptotic cells in the AlFu–GO–saponin and AlFu–rGO–saponin groups was 10.98 ± 2.36%–26.90 ± 3.24% and 15.9 ± 4.08%–29.88 ± 0.41%, respectively, compared with 2.52 ± 0.78%–1.31 ± 0.62% in the untreated group. This significant increase in apoptotic effect observed with AlFu–rGO–saponin was also reflected in the significant anticancer effect of saponin-loaded nanostructures. Therefore, this study suggests that an effective saponin delivery system protocol for the precise design and fabrication of anticancer nanostructures for OSCC therapy should be performed prior to in vivo evaluations. [ABSTRACT FROM AUTHOR]

Incorporating consumer choice behavior into a product line design optimization model enhances the understanding of consumer choices and improves the opportunities to increase profit. Most product line optimization problems assume that parameters are precisely known in consumer choice model. However, the decision maker does not precisely know the model parameters because of insufficient sample data, measurement problems, and other factors. We investigate the problem of establishing robust product line pricing under a multinomial logit model to account for the uncertainty of the valuation parameter. First, we present a nominal product line model to maximize profit. We then establish a robust product line model to maximize the worst-case expected profit, where the valuation parameter lies in an uncertainty set. We consider both single and multiple products development and derive the optimal prices' closed-form expressions. Through numerical experiments, we illustrate the benefit of robust product line pricing to address parameter uncertainty. We demonstrate that the difference between the expected nominal profit and the worst-case profit increases with the increase of the interval of the uncertainty set, and the robust profit relative to the worst-case nominal profit improves. The robust product line design can ensure steadier, even higher profit. [ABSTRACT FROM AUTHOR]

Product design constitutes a critical process for a firm, which if not implemented effectively it may even question its viability. The optimal product line design is an NP-hard problem, where a company aims at designing a set of products that will optimize a specific objective. Whilst Tabu Search (TS) has effectively solved a large number of combinatorial optimization problems, it has not yet been evaluated in product design. In this paper we design and implement a TS algorithm, which is applied to both artificial and actual consumer-related data preferences for specific products. The algorithm's performance is evaluated against previous approaches like Genetic Algorithm and Simulated Annealing. The results indicate that the proposed approach outperforms nine tested heuristics in terms of accuracy and efficiency. It also constitutes a more robust technique, and can be effectively generalized to larger problem sizes, which include higher number of products, attributes, or levels. Finally, a novel variant of TS capable of reducing execution time called Tabu Search Class Move, is introduced. [ABSTRACT FROM AUTHOR]

The article discusses several topics related to textile technology. It highlights a study that demonstrates the superior thermal comfort and moisture-wicking properties of wool compared to other fabrics. The article also mentions the development of a proposed standard for measuring nanoparticle properties, which has potential applications in various industries. Additionally, it discusses the launch of a new product line of synthetic rubbers that offer enhanced performance in harsh industrial environments. The article concludes by mentioning innovative biobased technologies, including a plant-based deodorizer, a dual-cooling capability technology, and a cosmetic technology for textiles that rejuvenates the skin's natural balance. Lastly, it mentions a groundbreaking study where bacteria were used to convert plastic waste into a biodegradable substance with properties similar to spider silk. [Extracted from the article]

The aim of this article is to establish the behaviour of partial Euler products for Dirichlet L-functions under the generalised Riemann hypothesis (GRH) via Ramanujan's work. To understand the behaviour of Euler products on the critical line, we invoke the deep Riemann hypothesis (DRH). This work clarifies the relation between GRH and DRH. [ABSTRACT FROM AUTHOR]

Green product design is recognized as one of the important approaches to improve environmental and social performance and achieve sustainable development. In the context of constraints of carbon emission, this article proposes a bilevel joint optimization (BJO) approach to optimize the green product line design with the consideration of the interactive relationship between firms in a competitive marketplace. A nonlinear, integer bilevel programming model with the consideration of carbon emission is developed based on the leader-follower decision framework. A bilevel nested genetic algorithm is presented to solve this optimization model. A case study of notebook computer involving one leader and one follower is developed to test the proposed optimization model. It is concluded that the presented BJO method can achieve a relatively better optimal solution to increase the profit of the product line while decreasing the amount of carbon emission for both leader and follower. [ABSTRACT FROM AUTHOR]

When an autonomous industrial vehicle moves to a certain point to take over or leave an order, intermediate commands may appear on its route that can be taken together with the first order. Orders will be allocated through an algorithm that analyzes delivery times and priorities. This paper presents results of researches regarding the development and use of a simulator to determine the efficiency of the algorithm for allocating transport orders in an intelligent manufacturing line for polymeric products. It is presented for comparison the variant in which the vehicle deals only with the first order and after its finish can take a new order. The paper comes from the development of previously made articles in which an algorithm is used to allocate the transport loads of autonomous industrial vehicles and a neural network that analyzes the capacity of batteries, thus estimating the distances that the vehicle can travel with certain percentages of battery. [ABSTRACT FROM AUTHOR]

Firms offer a variety of products to meet different customer needs. In many horizontally differentiated markets, prices are stable, and firms make infrequent adjustments to their product lines. Although prior research focused on product line design, we investigate how firms should allocate their marketing effort when their product lines are fixed. We propose a simple model to analyze product line marketing. Our model exhibits a flagship product effect in which the firm's optimal marketing effort is concentrated, provided that the ratio between consumer tastes dispersion and the convexity of the cost of marketing effort is below a threshold. The flagship product is selected according to a marketing effort allocation index that measures the trade-off between a product's markup and its potential market share. This result is robust with or without competition and whether prices are exogenous or endogenous. Firms often experience shocks to their marketing cost because of technological improvement or externalities. If a monopolist's cost of marketing effort declines, she should place more emphasis on a low-utility, high-markup product. Conversely, if the cost increases, the monopolist may find it beneficial to focus her marketing effort on a high-utility, low-markup product. When multiproduct firms compete against each other, we show that if the opponent's cost of marketing effort decreases, there can be a spillover effect, in which the firm benefits from the opponent's cost reduction, thereby leading to a win-win situation. This paper was accepted by Dmitri Kuksov, marketing. [ABSTRACT FROM AUTHOR]

Copyright of Packaging & Food Machinery is the property of Packaging & Food Machinery Magazine and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We develop an easy‐to‐implement programmed method for generating new product ideas from existing products. In this method, whose core is a compatibility matrix, each pair of components or each pair of attributes used in a new design is already part of one or more existing products produced by the firm or its competitors. The method has theoretical significance because such new designs might exist. The method also has practical significance because in most cases, a firm can use this programmed approach almost routinely. [ABSTRACT FROM AUTHOR]

The aim of this paper is to investigate pricing and production decisions of a monopoly firm that operates a co-product technology with two grades. A novel mathematical model that embeds a utility-maximizing customer choice model is developed to solve this problem. The closed-form expressions for the optimal solutions are derived and the results suggest that the distribution of customer valuations, yield rate and demand uncertainties have a vital influence on the firm's optimal prices and profits. We then extend our study by allowing stockout-based substitution where a customer may be willing to purchase a substitute if his most preferred product is not available but the substitute provides him with non-negative utility. The results indicate that disregarding stockout-based substitution (i) results in severe supply-demand mismatches for the product line in two directions; (ii) leads to higher or lower profit margins for both products; (iii) may not cause profit loss when the prices of both products are exogenous; however, this result does not hold when the prices are endogenous. [ABSTRACT FROM AUTHOR]

Today's manufacturing environment expects more with less expenses and effort. The development process must be effective to be in the global competitive market as a pioneer or world-class. It has been achieved by adopting the tool called Total Productive Maintenance (TPM) and Lean Manufacturing (LM). The application and results of tool implementation have been measured by the integrated performance index that Nakajima says is Overall Equipment Effectiveness (OEE) and Through-put Effectiveness (TE). Based on this, towards assessing the effectiveness of a manufacturing line with or without inventory, the Overall Manufacturing Line Effectiveness (OMLE) has been developed. OMLE provides a way to monitor the whole manufacturing chain by evaluating the outcomes of the entire incident. In this paper, the effectiveness of the product line manufacturing system has been estimated for various types of manufacturing processes through case studies. This analysis aims to increase the visibility and quantification of losses/waste in processes and improve the effectiveness of the product line. The bottleneck parameter and its corresponding processes in the product line have been defined and substantially changed in the product line regardless of the number of processes in the product line. The OMLE before and after implementing the kaizen in the case studies has been presented. The OMLE results of the various product manufacturing process lines have also been compared. OMLE serves as a blueprint to improve production process/line quality or output to produce a targeted resolution. [ABSTRACT FROM AUTHOR]

Problem description. We consider a dual channel in which a focal manufacturer (he) sells his output through his online store and an independent brick-and-mortar retailer (she). In this manufacturer-centric dual channel, we study product line, stocking, and pricing decisions in the presence of stochastic demand and inventory constraints. The pricing decisions include choosing whether to give price match guarantees (PMGs), standard in the U.S. retail practice. Methodology/Results. We analyze a game-theoretic model in which a focal manufacturer designs a product line, sets wholesale prices, and decides what products to sell in the dual channel. An independent brick-and-mortar retailer responds to the product line design and the wholesale prices by making stocking decisions in her store. Then, both stores observe demand and independently set retail prices subject to any PMGs that the stores gave to consumers. The brick-and-mortar store (online store) fulfills demand in a make-to-stock (make-to-order) fashion. We find that whenever one of the stores holds a competitive advantage, the manufacturer sells the same product line in both stores. If the brick-and-mortar store holds an advantage, it matches the online store's retail price to obtain favorable wholesale pricing from the manufacturer. We find no equilibria where the online store price matches the brick-and-mortar store or the stores' prices match each other. Finally, when neither store has a clear advantage, the manufacturer mitigates price competition by designing a different product for each store. Managerial implications. Our model helps identify optimal stocking and pricing strategies that depend on e-fulfillment cost and demand uncertainty and offers a novel reason for offering PMGs in a supply chain. [ABSTRACT FROM AUTHOR]

Software product line configuration (SPLC) is a typical many-objective optimization problem. Its purpose is to optimize multiple objectives simultaneously in a highly constrained space for searching. Recently, the concept of combining evolutionary algorithms with satisfiability (SAT) solvers has drawn increasing attention to this problem. However, most computational approaches often suffer from model instability and poor performance. Therefore, to address these limitations with higher efficiency, we propose a new algorithm, MySPLC, for configuring software product lines, which involves three main strategies. SMS is a new operator with higher performance than other traditional genetic operators. MSPS selects multiple invalid solutions in a population iteration to process. This balances the time required for environment selection and invalid solution processing, making each environment selection more efficient and meaningful. MCVFS makes the population evolve in a more diversified direction. We performed experiments on 10 feature models, and the feature numbers of these feature models ranged from 544 to 31012. The results show that our algorithm can find more diverse solutions than state-of-the-art methods. In addition, we study the related parameters,genetic operators, convergence and scalability of the algorithm. These studies further expand the application scenarios of the algorithm. [ABSTRACT FROM AUTHOR]

Product Line Engineering (PLE) is a fundamental component of systems engineering. As postulated in INCOSE's Vision 2025, Model‐Based Systems Engineering (MBSE) is becoming the norm for systems engineering. Thus, we need to integrate PLE into MBSE. An important aspect of this integration is the definition of model‐based methods. This paper defines two possible approaches for variant modeling with SysML applied at Airbus and provides insights into their application in practice. [ABSTRACT FROM AUTHOR]

Systems and Software Product Line Engineering (PLE) is an engineering discipline to produce and maintain a family of similar products in an efficient manner. It has long been known that managing a product portfolio as a single entity, as opposed to a multitude of separate products, can bring substantial improvements in schedule, cost, and quality. DevOps is an engineering discipline, practiced within an infrastructure of test and deployment automation, that seeks to minimize the time that a change to a product is made, and the product is built, validated, deployed, and made available to the end users. Many organizations find themselves willing to employ both disciplines – that is, to employ DevOps for products in a product line. This paper shows how that can be done, relates a case where it was done, and reports on the substantial benefits that were realized. [ABSTRACT FROM AUTHOR]

Nowadays, cloud‐native software architectures have a significant relevance due to the speed and agility they provide. These properties lead relevant organizations in different industries, like video streaming (Netflix), car‐sharing (Uber, Cabify), banking (BBVA, HSBC), and governmental agencies (NASA, FBI, CERN, ESA) to heavily rely on cloud‐native software to run their business‐critical applications. Additionally, including fault injection actions in the production infrastructure allows companies to have consistent environments, to improve applications dependability against unexpected failures, to provide better user experience, and to improve the overall system quality. Thus, cloud computing technologies allow development teams to rapidly create complex systems and to continuously deploy them, at a global scale. This work describes Pystol, a novel fault injection platform—represented as a Software Product Line—to analyze the effects caused by a wide spectrum of adverse conditions. Pystol is designed to be executed on top of cloud‐native environments, either in private or public clouds. The proposed architecture shows a way for representing feature models based on Unified Model Language (in short, UML) component diagrams. Furthermore, we present a thorough empirical study carried out in real‐world environments, providing promising results. [ABSTRACT FROM AUTHOR]

This paper explores the impact of carbon cap-and-trade policies and consumer low-carbon preferences on the choice of manufacturers' product lines. We further investigate the optimal decisions of manufacturers under different product line strategies. Moreover, we analyze consumer surplus, environmental impact, and social welfare under different product line strategies. The results show that producing low-carbon and ordinary products is the optimal product line strategy for manufacturers. In addition, we demonstrate that when considering carbon cap-and-trade policies and consumers' low-carbon preferences, the consumer surplus, environmental impact, and social welfare when manufacturers produce low-carbon products are always better than in other scenarios. Furthermore, our research results also show that with the increase of carbon trading prices, the consumer surplus and social welfare when manufacturers choose to produce low-carbon products are always better than in other scenarios. However, we find that the environmental impact is not always outperforming when manufacturers choose a product line that produces low-carbon products than other scenarios. [ABSTRACT FROM AUTHOR]

Product derivation is the process of building a specific product from a software product line. Effective product derivation can improve software reuse productivity. Existing methods can only obtain abstract feature models, lacking detailed specifications of individual features. They are more about deriving code assets or class diagram templates without precise model descriptions for specific products. This article proposes a product derivation approach to obtain a formal specification of a specific product based on the feature model and formal specification. We use the integration ordering and behavior preserving integration techniques to integrate the formal specification for each feature pair. The method is divided into two steps. First, it determines the feature formal specification integration ordering based on the feature model. Then, the behavior-preserving integration will be conducted for pairs, including declaration integration, functional scenario path generation, and function integration based on path matching. Behavior preserving integration guarantees consistent behavior to ensure the quality of the formal specification after integration. Finally, we developed a support tool to conduct a case study. The tool first guides the user to perform feature functional scenario path matching, then performs functional integration based on the matching results and repeats the above steps to generate a product model. The result indicates that our method facilitates the derivation process and improves the quality of the generated models. [ABSTRACT FROM AUTHOR]

The study evaluates the success of an industry self‐regulatory initiative, the Children's Food and Beverage Advertising Initiative (CFBAI), designed to limit advertising of less nutritious foods to children that began in 2006 and implemented by pledging firms by 2013. We estimate the nutritional profile (calories, sugar, sodium, and fiber) of cereals that were advertised on national/local television (approximately 170 million ads) and measure children's exposure (over 21,000 children) to these ads for years 2001–2013. We also examine how firms responded to the voluntary agreement in terms of their advertising and product line decisions. Results reveal improvements in the nutritional quality of cereal children are exposed to through advertising, indicating the success of this self‐regulatory initiative in this product category. Results also reveal the ways in which manufacturers adapted their product line offerings and ad airings in response to their CFBAI pledges. [ABSTRACT FROM AUTHOR]