Hyperparameter optimization (HPO) is known to be costly in deep learning, especially when leveraging automated approaches. Most of the existing automated HPO methods are accuracy-based, i.e., accuracy metrics are used to guide the trials of different hyperparameter configurations amongst a specific search space. However, many trials may encounter severe training problems, such as vanishing gradients and insufficient convergence, which can hardly be reflected by accuracy metrics in the early stages of the training and often result in poor performance. This leads to an inefficient optimization trajectory because the bad trials occupy considerable computation resources and reduce the probability of finding excellent hyperparameter configurations within a time limitation. In this paper, we propose Bad Trial Tackler (BTTackler), a novel HPO framework that introduces training diagnosis to identify training problems automatically and hence tackles bad trials. BTTackler diagnoses each trial by calculating a set of carefully designed quantified indicators and triggers early termination if any training problems are detected. Evaluations are performed on representative HPO tasks consisting of three classical deep neural networks (DNN) and four widely used HPO methods. To better quantify the effectiveness of an automated HPO method, we propose two new measurements based on accuracy and time consumption. Results show the advantage of BTTackler on two-fold: (1) it reduces 40.33% of time consumption to achieve the same accuracy comparable to baseline methods on average and (2) it conducts 44.5% more top-10 trials than baseline methods on average within a given time budget. We also released an open-source Python library that allows users to easily apply BTTackler to automated HPO processes with minimal code changes\footnotehttps://github.com/thuml/BTTackler.

The COVID-19 pandemic has sparked considerable alarm amongst the general community and has significantly affected the societal attitudes and perceptions. In the current era, social engineers are applying various strategies to exploit human weakness. Phishing, a social engineering technique, is one of the most widely used and effective ways to undermine human assets. In this research study, firstly, we aim to educate the participants regarding phishing attacks; secondly, the dangers associated with excessive online sharing; and thirdly, how to utilise game scenarios developed by the participants to elicit security requirements. We have employed various research methods, such as, survey, observation, personas development, and scenario-based technique to achieve these objectives. Our re-evaluation results show that the PhishI game effectively educates participants regarding phishing attacks and dangers associated with disclosing excessive online information.

Abstract In modern times, internationally organized teams face a number of coordination problems owing to their different physical operating locations. These challenges usually come in temporal, cultural, and linguistic forms. To resolve some of these issues, we need more coordination, teamwork, and shared understanding in the requirements engineering phase. Many approaches have been introduced to overcome these challenges associated with global software engineering (GSE). The objective of this research study is to introduce amateurs to GSE and improve their understanding of its associated challenges through an activity‐based learning approach. Our method is primarily targeted toward students who already have theoretical knowledge on the topic but require first‐hand experience with GSE. With the aforementioned motivation in mind, we propose, designe, and empirically evaluate two different activities that can help enhance awareness of GSE challenges. For each activity, we simulate an environment wherein participants are made to go through various constructed coordination challenges related to communication, time management, team mistrust, linguistic barriers, cultural barriers, and distribution of tasks. The effectiveness of our proposed activities, captured by the extent to which participants were able to deal with GSE challenges, was judged through various techniques including (i) observation, (ii) post activities survey questionnaire, and (iii) brainstorming and discussion. We show that the proposed activities were effective in helping students learn and further their understanding of GSE concepts. In particular, discussion sessions and survey questionnaire results reflect their ability to identify critical GSE challenges (specifically related to teams) in a simulated scenario.

The world is evolving in a pace faster than ever, in terms of the ways in which human can interact with the rest of the world virtually or physically. Our exploration together with Carl along the road involves many models and methods that help better understand users' needs, desires and intentions, specify clearer system requirements and know-how, describe simpler service interface to find a match between requests and capabilities. There are implicit relations between these research topics, namely, building smarter software systems that can adapt to the needs and intentions of users, as well as the concrete operational context and environment. This paper may look retro-futurism in a sense, as we are looking forward to fulfillment the early AI and SE visions, by reviewing viable fundamental software requirements engineering principles and service system thinking methods, and at the same time by making sense of the on-going development of smart applications with the latest intelligent computing technologies.

Abstract Quality of research and knowledge sources can be a critical factor to judge the quality of the research citing them. The prevailing online dissemination of research via blogs, websites, experience reports, and white papers can be helpful as it minimizes potential publication biases. In this paper, we have (i) identified the body of software engineering (SE) literature that is non‐indexed by Web‐of‐Science but has been used in published SE systematic literature review (SLR) studies (as primary studies); (ii) proposed a checklist‐based method for quality assessment of non‐indexed and grey literature; (iii) empirically evaluated the effectiveness of the proposed method; (iv) searched primary studies retrieved from the SLRs in DBLP and Google Scholar (GS) to verify whether DBLP or Google Scholar can act as viable options to search for non‐indexed Web‐of‐Science (non‐WOS‐indexed) literature. Besides proposing our synthesized checklist method, we found that (i) SE literature reviews use significantly non‐indexed Web‐of‐Science sources; (ii) DBLP only covers a portion of the non‐WOS‐indexed reference, whereas GS has a more complete coverage of the non‐indexed reference in comparison. Preliminary evaluation of the proposed quality assessment point system‐based and checklist‐based methods shows it to be a viable way to assess quality of the non‐indexed and grey literature.

The rapid development of Internet of Things (IoT) technology makes smart homes a reality, where many user-centered service scenarios are yet to be built. For such applications, it is of utmost importance to let end users express their needs easily on the one hand, and these users’ expectations can be interpreted by the smart home systems accurately on the other hand. Unfortunately, existing requirements languages are not for end users to express their needs in daily terms. An easy but expressive requirements language is required. This paper carries out a survey on suitable and expressive requirements description language for smart homes. Based on the results, a user requirements description language Smart3E is designed for enabling end user expressions. This paper also puts forward the challenges that are needed to be addressed when allowing end users to express their needs freely in smart home domain.

Training a classifier based on imbalanced data set is considered a great challenge in classification tasks, as classifiers are often "biased" due to highly skewed data distribution and overlapping borderline between different classes. When the imbalanced data appears in the multi-class classification scenario, the classification difficulty increases exponentially. In this paper, we propose an integrated approach to handle imbalanced multi-class classification by combining the population-based sampling method and a multi-expert classifier. In the implementation, we choose the Ant Colony Optimization to realize the sampling process. As for the classifier, the voting mechanism is applied to intensify the weak classifiers. To test the algorithm’s performance, we choose 10 representative imbalanced multi-class data sets from the UCI Machine Learning Repository. G – mean and mAUC are chosen as the metrics. According to the experimental results, the proposed algorithm dominates in 8 data sets and gets a second place in 1 data set when evaluated by G – mean, and ranks first in 3 data sets and top-3 among the most for mAUC.

Background: One of the necessary conditions for any substantial research work is to synthesis the depth and the breath of the existing published literature on that topic. It is, thus, of extreme importance for a researcher to understand and look for both credible and exhaustive information sources. This first (important) step can be made significantly easier if the researcher can employ a more systematic way to extract the maximum of the literature on the topic. Objective: Essentially, the objective of this preliminary study is to rank three freely available academic search engines (Google Scholar, DBLP, Microsoft Academic Search) on the basis of the indexed Software Engineering academic literature they contain. Method: We have used a systematic mapping to conduct the study. Results: After extracting and analyzing 1067 secondary studies (from 18 tertiary studies), we have concluded that Google Scholar has indexed 98.96%, DBLP has indexed 93.43%, and Microsoft Academic Search engine has indexed 97.46% of the secondary studies. Thus, this implies that Google Scholar and Microsoft Academic Search might be a better-suited option for searching for secondary studies.

Objective of the study is to calculate: a) grey literature evidence in the selected Systematic literature reviews (SLRs); b) Google Scholar indexing for the extracted primary studies from the selected SLRs. We have randomly selected 20+ SLRs from Science Direct, IEEE Xplore, Springer Link and ACM. Result: a) Random selection of 20+ SLRs and grey literature calculation verifies that the grey literature percentage ranges around 5.7% to 9.1%; b) The second phase showed that Google Scholar was successful in retrieving around ~91% of the primary studies.

Human remains susceptible to manipulations, and social engineers are expert of these techniques. To better understand the attack and defense strategies of social engineering attack, there is a need to map social engineering strategies with the war strategies. We can find plenty of war strategist and books on war strategies. By mapping the knowledge, we may get unique ways of defense and can further identify social engineering attack patterns. In this study, we have mapped the principles suggested by Sun-Tzu with social engineering attacks and further mentioned the initial results (by showing examples for each case). We aim to extend this work and further verify the effectiveness of this strategy in near future.

Attribute recognition is a crucial but challenging task due to viewpoint changes, illumination variations and appearance diversities, etc. Most of previous work only consider the attribute-level feature embedding, which might perform poorly in complicated heterogeneous conditions. To address this problem, we propose a hierarchical feature embedding (HFE) framework, which learns a fine-grained feature embedding by combining attribute and ID information. In HFE, we maintain the inter-class and intra-class feature embedding simultaneously. Not only samples with the same attribute but also samples with the same ID are gathered more closely, which could restrict the feature embedding of visually hard samples with regard to attributes and improve the robustness to variant conditions. We establish this hierarchical structure by utilizing HFE loss consisted of attribute-level and ID-level constraints. We also introduce an absolute boundary regularization and a dynamic loss weight as supplementary components to help build up the feature embedding. Experiments show that our method achieves the state-of-the-art results on two pedestrian attribute datasets and a facial attribute dataset.

With the recent advancement in data science, Predictive Analytics (PA) functions have been built into many commercial products, which affects several “non-functional” goals, including usability, performance, and transparency of the software, as well as privacy and well-being of the user. The direct and indirect consequences are yet to be understood better before the service providers take any further actions in response. In this work, a survey was conducted with a sample set of 153 respondents from U.S., on their acceptance of applications with PA. The result shows that many consumers recognize the benefit of PA features, but they are not without concerns about transparency, privacy, and personal well-being. Once users are highly concerned, they may choose not to use these features or even give up the products altogether. Based on the survey result, we have discussed how requirements engineering can help the stakeholders make better decisions related to PA adoption and design, and how RE tools can help address user concerns related to PA.

Online discussion forums can be used for reflecting on the overall user experience of a system. If a user forum is well‐structured, it can be a valuable source of requirements‐related information, which can potentially be accommodated in the requirements engineering process to enhance the current and future software. However, presently, there are limited approaches for extracting such requirements‐related information from the relevant community forums. To fill this gap, this study proposes an automated approach, which automatically identifies requirements information using natural language processing and machine learning. For this purpose, the authors analysed 3319 user comments collected from the seven discussion topics in the Reddit forum. Then, using a content analysis approach, they studied how frequently end‐users submit such information across each discussion topic. Also, they developed an automated approach that identifies key stakeholders, who frequently contribute his rationales in the forum discussion. Further, they employed different machine learning algorithms to classify user comments into rationale elements of different types. The authors' results show that online forums, such as Reddit, can be a rich source of requirements elicitation. Also, machine learning is a promising tool to detect user's rationale and identify different kinds of requirements modelling elements.

Abstract Due to the pervasive use of online forums and social media, users' feedback are more accessible today and can be used within a requirements engineering context. However, such information is often fragmented, with multiple perspectives from multiple parties involved during on‐going interactions. In this paper, the authors propose a Crowd‐based Requirements Engineering approach by Argumentation (CrowdRE‐Arg). The framework is based on the analysis of the textual conversations found in user forums, identification of features, issues and the arguments that are in favour or opposing a given requirements statement. The analysis is to generate an argumentation model of the involved user statements, retrieve the conflicting‐viewpoints, reason about the winning‐arguments and present that to systems analysts to make informed‐requirements decisions. For this purpose, the authors adopted a bipolar argumentation framework and a coalition‐based meta‐argumentation framework as well as user voting techniques. The CrowdRE‐Arg approach and its algorithms are illustrated through two sample conversations threads taken from the Reddit forum. Additionally, the authors devised algorithms that can identify conflict‐free features or issues based on their supporting and attacking arguments. The authors tested these machine learning algorithms on a set of 3,051 user comments, preprocessed using the content analysis technique. The results show that the proposed algorithms correctly and efficiently identify conflict‐free features and issues along with their winning arguments.

In the past, users were asked to express their needs and intentions by writing a structured requirements document in natural language. Due to the pervasive use of online forums and social media, user feedback is more accessible today. However, the information obtained is often fragmented, involving multipleperspectives from multiple parties on an on-going basis. In this paper, we propose a Crowd-based Requirements Engineering approach by Argumentation (CrowdRE-Arg), which analyses the conversations from user forum, identifies the arguments in favor or opposing of a given requirements related discussion topic. By generating the argumentation model of the involved user statements, we are able to recover the conflicting viewpoints, to reason about the winning arguments for informed requirements decisions. The proposed approach is illustrated with a data set of sample conversations about the design of a new Google-Map feature from Reddit. Also, we apply natural language processing techniques and machine learning algorithms to support the automated execution of the CrowdRE-Arg approach.

Requirements elicitation is one of the essential steps towards software design and construction. Business analysts and stakeholders often face challenges in gathering or conveying key software requirements. There are many methods and tools designed by researchers and practitioners but with the persistent development of new technologies, there is a need to make requirements gathering and design‐rationale process more efficient and adaptable. Storytelling is an emerging concept and researchers are witnessing its effectiveness in education, community building, information system, and requirement elicitation. Objectives of this study are to devise a method for requirements elicitation and improving design‐rationales using story‐based techniques and evaluate the effectiveness of the proposed activity. To answer the research objectives, the authors have conducted open‐ended interviews to get feedback on the proposed method; the authors have case requirement from a running project to map how this method can be useful; and performed empirical evaluation of the proposed card‐based activity. The estimated regression model, in our study, has shown that participants' perception about the simplicity/easiness and the joy of playing the game has an eventual positive effect on requirements elicitation through enhancing user's desire to play the game, which in turn increases the collaborative learning outcomes of the game.

Protecting people from cyber threats imposes great challenges, not only technically, but also socially. To achieve the intended level of awareness, software security principles need to be shown with concrete examples during security education. This study aims to design a serious game integrating software security knowledge and concepts into the processes to make it more engaging to learn while playing. In this paper, we have: (i) designed a serious game to compensate the deficiencies in the literature; (ii) performed empirical evaluations including survey, brainstorming and observation to the proposed game. Results: Our study shows that: (i) Cyber Security‐Requirements Awareness Game (CSRAG) has a positive effect on players security learning outcomes, level of engagement and participation; (ii) Game‐based learning can be an effective way of teaching security related scenarios.

Context: In the current era of digital technology, social engineers are using various tactics to undermine human weaknesses. Social Engineers target human psychology to achieve their target(s) which are in the form of data, account details, or IT devices etc. According to our research, one of the first methods social engineers used to target victims is Phishing/Spear Phishing. Objective: The objective of this study is to utilize serious game to: i) educate players regarding phishing and spear-phishing attacks; ii) make aware and educate players regarding dangers associated with excessive online information disclosure. Method: In order to address the objectives we have: i) performed an in-depth literature review to extract insights related to social engineering, phishing, game design, learning functions, human interaction, and game-based learning etc; ii) proposed and aligned the game design with social engineering ontology concepts; iii) performed an empirical evaluation to evaluate the effectiveness of the designed board game. Conclusion: From this research study, we conclude that: i) PhishI game is useful in educating players regarding excessive online information disclosure and phishing awareness; ii) game-based learning is an effective method for inculcating and general cyber-related awareness in players.

Dental radiography provides important evidence for clinical diagnosis, treatment and quality evaluation. Much effort has been spent on developing digitalized dental X-ray image analysis systems for clinical quality improvement. In this paper, we present the datasets, procedures, and results conducted to evaluate dental treatment qualities using periapical dental X-ray images taken before and after the operations. In order to support dentists to make clinical decisions, we propose a tool pipeline for automated clinical quality evaluation. We build a dataset with 196 patients' periapical dental radiography images before and after the treatments. Radiography images are labelled as cases that are `getting better', `getting worse' and `have no explicit change' by designated dental experts. Our proposal includes an automatic method with the medical knowledge to crop the ROIs for clinical evaluation - the apical adjacent regions, and then pairs of ROIs are fed into a CNN to train the model for automated clinical quality evaluation. Our approach achieves the F1 score of 0.749, which is comparable to the performance of expert dentists and radiologists.

We are witnessing a radical change of attitude towards health information management - the adoption of data analytics to help people monitor and predict health conditions proactively. Most hospitals are aggregating data to provide some sort of analytics as part of their daily practices. Many medical doctors start developing data repositories of their own specialty so that evidence-based clinical decisions can be made, and data of research value can be obtained and exploited efficiently. Health analytics projects need to have software requirements defined for them. These projects must deal with the data itself, the operations performed on the data, and the formatting and distribution of the data for use. The end products of requirements process for a health analytics project will be a set of business and user requirements (both functional, and nonfunctional). It reveals stakeholder needs of analytics results, in terms of how quickly, how often and in what format. This paper shares our observations on the status quo in this area, present the problems and challenges encountered, report the experience and findings in real world projects, and discuss some possible future directions in this area.

While culture being the "software" controlling human mind, computer software development becomes one of the most creative activities that human undertake since the civilisation began. The only limitation in software creation is human imagination, and that limit is often self-imposed. The "Internetware", refers to a software paradigm, aims to satisfy the need of human kind using Internet as an integrated development and execution platform. Such software systems composed of entities distributed through the Internetwork, allowing connections that would be impossible or difficult to make otherwise. This paper gear towards the tasks for the Internetware is to accommodate creativity. In particular, we propose a six-step approach to Internetware development, an approach suggests essential difference to traditional methods. The six steps in this approach are search, ideation, specification, coding, testing, and operation. For each of these steps, we suggest a set of techniques to carry out the step in practice. The proposed developmental model asks researchers and practitioners of the Internetware paradigm to better understand human creativity and to formulate an algorithmic perspective on creative behavior in human, to design programs that can enhance human creativity without necessarily being creative themselves.

Requirements are usually presented as Natural Language based documents. In the conceptual modeling phase, requirements are collected from different stakeholders and analyzed by requirement engineers. However, the size of the requirements documents can become very large, and the modeling process is quite time consuming and resource consuming. In order to solve this problem, much has been written on the processing of requirements documents to yield conceptual models. In this paper, we proposed an approach for identifying and extracting relations in a range of requirements documents with three steps: text analysis, entity extraction and relation mapping. If the entities in the relation are quite close to each other, for example, in the strategic dependency relationship, we will define a set of linguistic patterns used for identifying relations and propose a matching algorithm of semantic automata to extract the relation. Based on this approach, we developed a system to automatically generate the strategic dependency model of i framework and the activity model from Chinese requirements documents. A series of experiments were conducted to evaluate the performance of the automated requirements analysis system. The results show that the system achieves high recall with a consistent improvement in precision, which demonstrates the applicability of our approach.

We propose a modeling language for non-functional requirements (NFRs) that views NFRs as requirements over qualities, mapping a software-related domain to a quality space. The language is compositional in that it allows (recursively) complex NFRs to be constructed in several ways. Importantly, the language allows the definition of requirements about the quality of fulfillment of other requirements, thus capturing, among others, the essence of probabilistic and fuzzy goals as proposed in the literature. We also offer a methodology for systematically refining informal NFRs elicited from stakeholders, resulting in unambiguous, de-idealized, and measurable requirements. The proposal is evaluated with a requirements dataset that includes 370 NFRs crossing 15 projects. The results suggest that our framework can adequately handle and clarify NFRs generated in practice.

The prevailing of social computing and online services has brought both challenges and opportunities. For service providers to better understand the potential needs of service users, their social roles and positions should be modeled and analyzed to reflect the users' needs and preferences as using the provided services. In this paper, we set out from a conceptual modeling framework for social-role based online community behavior, explain how such a model can be used in representing the stakeholders/players' goals, obligations and choices in an Internetware-based service community. Then we can reason about the different environment expectation to different roles, and behavioral pattern bring about by the different expectations, conflicts between roles and gaps between requirements and the current system behavior. In the Internetware setting, software entities should be able to detect the social environmental changes and adapt to collaborate dynamically for specific needs, by playing different roles when they are working. This paper models Internetware using social roles and uses the model to better understand the behavior of Internetware.

There are many business information systems under operation supporting the essential business processes of large scale multi-national enterprises, which forms the essential IT assets of these organizations. However, the isolation of these systems, improper process configurations and unbalanced resource allocations often leads to the deterioration of these enterprises, or even major management crisis. Service-oriented computing is considered a possible remedy for such issues with relatively low migration cost that has attracted much industrial attention. In this paper, through a survey to an industrial consulting case from a Southeastern Asia Garment Manufacture, we discuss how service requirements are elicited, how to evolve conventional management information systems into composite service systems that is reconfigurable at runtime, so as to realize resources optimization and efficiency improvement. The purpose of this paper is to analyze the know how of migrating conventional management information systems into service-oriented architecture, from a requirements engineering perspective.

Many graphs in practical applications are not deterministic, but are probabilistic in nature because the existence of the edges is inferred with the use of a variety of statistical approaches. In this paper, we will examine the problem of clustering uncertain graphs. Uncertain graphs are best clustered with the use of a possible worlds model in which the most reliable clusters are discovered in the presence of uncertainty. Reliable clusters are those which are not likely to be disconnected in the context of different instantiations of the uncertain graph. We present experimental results which illustrate the effectiveness of our model and approach.

Along with the green attentions and efforts on energy efficiency of computer hardware and embedded systems, software relevant sustainability issues are becoming increasingly focused, as a part of Green Information Technology (GIT). Undoubtedly, software evolution capability is a vital part in achieving such sustainability, as software that is not adaptable will become obsolete sooner or later. Internetware is currently one of the prevailing paradigms of software evolution, known as its autonomous, cooperative, situational, evolvable, emergent and trustworthy. In this paper, we propose an approach of evolution focusing on sustainability for Internetware software entities. Targeting certain software systems which cannot actively control their functions, service components or attached actuators energy-efficiently, the proposed transformation mechanism can intelligently implement power management adaptations using Web Ontology Language (OWL) -based user behavioral profiles and reasoning mechanisms. In the effort of increasing the sustainability, the transformation consequently enables a greener, predicted and rapidly adapted evolution.

One of the prominent properties of the Internetware Software Paradigm is its evolutionary characteristic. It is recognised that the evolution of software systems are driven by the needs of final users, and influenced by changes in the operational environments and technology advancement. The evolution of biological and social systems often forms a spiral incremental tendency where the changes are continuous, and stepwise. Inspired by the classical pyramid model of Maslow on Human needs, we propose to understand the evolution of software in the Internetware era with a double pyramid model. In other words, user's needs are gradually changing and their expectations to the system functionalities and qualities are getting higher; at the same time, more and more sophisticated software services become available, they provide richer functionalities, better qualities, more diversified choices, and more appealing user experiences. We first structure the development of user expectation and the capability of services as two separate pyramids, and then we define how the two pyramids interacts and influence each other within a co-evolution model. An example of Internetware system development is presented to illustrate how the co-evolution model helps shorten life cycle of system development and achieve high quality and efficiency at the same time.

SUMMARY: To address the impending need for exploring rapidly increased transcriptomics data generated for non-model organisms, we developed CBrowse, an AJAX-based web browser for visualizing and analyzing transcriptome assemblies and contigs. Designed in a standard three-tier architecture with a data pre-processing pipeline, CBrowse is essentially a Rich Internet Application that offers many seamlessly integrated web interfaces and allows users to navigate, sort, filter, search and visualize data smoothly. The pre-processing pipeline takes the contig sequence file in FASTA format and its relevant SAM/BAM file as the input; detects putative polymorphisms, simple sequence repeats and sequencing errors in contigs and generates image, JSON and database-compatible CSV text files that are directly utilized by different web interfaces. CBowse is a generic visualization and analysis tool that facilitates close examination of assembly quality, genetic polymorphisms, sequence repeats and/or sequencing errors in transcriptome sequencing projects. AVAILABILITY: CBrowse is distributed under the GNU General Public License, available at http://bioinfolab.muohio.edu/CBrowse/ CONTACT: [email protected] or [email protected]; [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Various governmental or academic institutes survey current security trends, and report vulnerabilities, security breaches, and their costs. However, it is unclear whether (and how) practitioners analyze these vulnerabilities and attacks to arrive at security requirements and decide on security solutions. What modeling methods are used for eliciting, analyzing, and documenting security requirements in real-world practice? This paper intends to answer such questions through a survey of security requirements engineering practices. 374 software professionals from 237 International and Chinese firms participated in the survey. The results show businesses often try to consider security from early stages of the development life cycle, however, ultimately, security is left to be built into the system at the implementation phase. We observed that practitioners favour qualitative risk assessment rather than quantitative approaches, and this helps them consider more varieties of factors when comparing alternative security design solutions.

In today's service computing environments, user needs and expectations are constantly changing. New services emerge while old ones become obsolete and need to be replaced. In such settings, composite services need to be adaptive to changes in user requirements and the environment. This paper proposes a conceptual framework for modeling compositional adaptation for services founded on a requirements monitoring facility. This facility helps maintain adherence between user requirements changes and the dynamics of service composition structure and quality attributes. Specifically, user requirements are represented as goals and soft goals, service composition structure is represented with a CSP-like grammar, and the adaptation mechanism is based on AI planning. The proposed approach is evaluated in a service simulation environment of real-world supply-chain adaptation scenarios.

In this paper, we investigate the highly reliable subgraph problem, which arises in the context of uncertain graphs. This problem attempts to identify all induced subgraphs for which the probability of connectivity being maintained under uncertainty is higher than a given threshold. This problem arises in a wide range of network applications, such as protein-complex discovery, network routing, and social network analysis. Since exact discovery may be computationally intractable, we introduce a novel sampling scheme which enables approximate discovery of highly reliable subgraphs with high probability. Furthermore, we transform the core mining task into a new frequent cohesive set problem in deterministic graphs. Such transformation enables the development of an efficient two-stage approach which combines novel peeling techniques for maximal set discovery with depth-first search for further enumeration. We demonstrate the effectiveness and efficiency of the proposed algorithms on real and synthetic data sets.

BACKGROUND: HIV and HCV infections have become the leading global public-health threats. Even more remarkable, HIV-HCV co-infection is rapidly emerging as a major cause of morbidity and mortality throughout the world, due to the common rapid mutation characteristics of the two viruses as well as their similar complex influence to immunology system. Although considerable progresses have been made on the study of the infection of HIV and HCV respectively, few researches have been conducted on the investigation of the molecular mechanism of their co-infection and designing of the multi-target co-inhibitors for the two viruses simultaneously. RESULTS: In our study, a multi-target Quantitative Structure-Activity Relationship (QSAR) study of the inhibitors for HIV-HCV co-infection were addressed with an in-silico machine learning technique, i.e. multi-task learning, to help to guide the co-inhibitor design. Firstly, an integrated dataset with 3 HIV inhibitor subsets targeted on protease, integrase and reverse transcriptase respectively, together with another 6 subsets of 2 HCV inhibitors targeted on NS3 serine protease and NS5B polymerase respectively were compiled. Secondly, an efficient multi-target QSAR modelling of HIV-HCV co-inhibitors was performed by applying an accelerated gradient method based multi-task learning on the whole 9 datasets. Furthermore, by solving the L-1-infinity regularized optimization, the Drug-like index features for compound description were ranked according to their joint importance in multi-target QSAR modelling of HIV and HCV. Finally, a drug structure-activity simulation for investigating the relationships between compound structures and binding affinities was presented based on our multiple target analysis, which is then providing several novel clues for the design of multi-target HIV-HCV co-inhibitors with increasing likelihood of successful therapies on HIV, HCV and HIV-HCV co-infection. CONCLUSIONS: The framework presented in our study provided an efficient way to identify and design inhibitors that simultaneously and selectively bind to multiple targets from multiple viruses with high affinity, and will definitely shed new lights on the future work of inhibitor synthesis for multi-target HIV, HCV, and HIV-HCV co-infection treatments.

Driven by the emerging network applications, querying and mining uncertain graphs has become increasingly important. In this paper, we investigate a fundamental problem concerning uncertain graphs, which we call the distance-constraint reachability (DCR) problem: Given two vertices s and t, what is the probability that the distance from s to t is less than or equal to a user-defined threshold d in the uncertain graph? Since this problem is #P-Complete, we focus on efficiently and accurately approximating DCR online. Our main results include two new estimators for the probabilistic reachability. One is a Horvitz-Thomson type estimator based on the unequal probabilistic sampling scheme, and the other is a novel recursive sampling estimator, which effectively combines a deterministic recursive computational procedure with a sampling process to boost the estimation accuracy. Both estimators can produce much smaller variance than the direct sampling estimator, which considers each trial to be either 1 or 0. We also present methods to make these estimators more computationally efficient. The comprehensive experiment evaluation on both real and synthetic datasets demonstrates the efficiency and accuracy of our new estimators.

Non-functional requirements are considered as vital factors for producing software of better quality. As a widely adopted non-functional requirements analysis framework, the NFR Framework provides a graphical treatment for goal refinement and evaluation. This paper propose a logical representation for the NFR Framework. In addition, an NFR extension operator and an accompanying extension function for composing multiple viewpoints of NFR are proposed. Compared with the graphical NFR Framework, the logical approach further enhances the reasoning capabilities of the NFR framework. A real-world example has been used to illustrate the formal approach.

Software Systems running in the Internet are facing an ever-changing environment, which requires constant monitoring and adaptation facilities to be in place, so that user's needs and system requirements are satisfied on-demand. This paper summarizes our general observation and understanding to how user and system goals can drive the adaptation mechanisms of individual software service modules, implemented as internetware components. In particular, a theoretical typology of different levels of adaptation capability is proposed. Their correspondence with the key characteristics of internetware is analyzed. A common architecture to support the run-time adaptation of internetware is also suggested in company with a development method.

Numerical reservoir simulation is one of the effective tools for complex fluid analysis in the oil industry. This paper analyzed the principle of thermal recovery simulation, and designed and implemented a parallel program of the thermal recovery simulation based on PESTc toolkit. The improved domain decomposition with load-balance control was presented to partition the computation into different processing units efficiently. Compared with the serial program, our implementation can gain 8.16 times speedup using 16 cores over a large-scale reservoir test case.

Requirements engineering has gained growing attention in both academia and industry, as today’s software intensive systems are expected to provide highly user-centric functions and qualities. Thus, it is important to understand under what situations existing requirements engineering practice is not working well. Continuing our probe into the industrial practices status quo, this paper reports the results from a recent survey of requirements practices in China in 2009. The web-based survey of requirements engineering practices focuses on requirements elicitation techniques, requirements representation techniques. Although purporting to report on the state-of-the-art of requirements engineering in China, it is likely to portray the state-of-the-art of RE worldwide as well.

In the services era, evaluation of existing services and planning for new services according to user requirements are key activities that need systematic support. This paper proposes a requirements-driven evaluation framework for Internetware-based services, with respect to both their functionality and risk. In particular, we offer an account of how to model these requirements, how to derive from them a space of service functionality alternatives, and how to select among these alternatives on the basis of desired qualities. In essence, the selection of service functionality is framed as a satisfaction problem for requirements; while service risk is addressed as an analysis of failure rates. We use a typical logistics example scenario to illustrate the proposed framework.

In this paper, we consider a novel scheme referred to as Cartesian contour to concisely represent the collection of frequent itemsets. Different from the existing works, this scheme provides a complete view of these itemsets by covering the entire collection of them. More interestingly, it takes a first step in deriving a generative view of the frequent pattern formulation, i.e., how a small number of patterns interact with each other and produce the complexity of frequent itemsets. We perform a theoretical investigation of the concise representation problem and link it to the biclique set cover problem and prove its NP-hardness. We develop a novel approach utilizing the technique developed in frequent itemset mining, set cover, and max k-cover to approximate the minimal biclique set cover problem. In addition, we consider several heuristic techniques to speedup the construction of Cartesian contour. The detailed experimental study demonstrates the effectiveness and efficiency of our approach.

Rapid changes in the social and technical environment bring about many new challenges to system requirements engineering, amongst which out-sourcing or off-shoring of certain design tasks to countries with more human resources and broader markets becomes promising business leverage. This paper reports the results from a survey of requirements practices in China and points out their implications. The survey aims to understand the current state of RE practice in China, and investigate the impacts that Chinese culture has on requirements engineering activities. We collected data from 149 participants in 97 Chinese companies and 15 research institutes. We also analyzed the impact of Chinese culture on requirements engineering practices. We hope our results are useful for industrial practitioners and academic researchers wishing to improve current practices, and for foreign software companies wishing to better understand their Chinese customers.

Security requirements analysis is gaining growing attention as new vulnerabilities and threats are emerging on daily basis, the systematic evaluation of security requirements is of utmost importance among the various decisions to be made related to security. This short contribution proposes using a 3-dimensional vector for quantitative evaluation of security requirements, which takes into account the importance of assets to be protected, the vulnerability of the system and the trustworthiness of environment.

Since the first IEEE International Requirements Engineering for Services (REFS) workshop took place in the historical capital of China, Beijing, on 23 July 2007, three editions of the workshop have been running as a series at the COMPSAC conference, serving as an interactive forum for in-depth discussion of all issues related to requirements engineering for services. Researchers from the diverse areas of requirements engineering, services engineering, and services management presented and debated major issues, challenges, trends, and technical advances in requirements engineering for services. Based upon the ranking of papers assigned by the program committee in the workshops, a collection of six research papers from the workshop, together with two main conference papers on relevant topics, were invited to submit a revised and extended version to the IEEE Transations on Services Computing (TSC). Of these, two papers are included in this first special section on REFS.

Presents the introductory welcome message from the conference proceedings.

Provides a listing of current committee members and society officers.

At the present time, requirements knowledge is mainly in the possession of requirements experts and senior experienced practitioners, which is often implicit and pragmatic to share with novices. Requirements patterns aim to help derive complete, consistent, and implementable requirements specifications from rough sketches of the problem context. In this paper, we propose to use semi-formal approaches such as Problem Frames (PF) and i* to help represent, organize, and analyze recurring requirements knowledge patterns. The proposed PF and i* integrated approach enables simultaneous consideration of the designerpsilas subjective intentions as well as concrete environmental constraints.

This paper presents a new method to discover transition rules of geographical cellular automata (CA) based on a bottom‐up approach, ant colony optimization (ACO). CA are capable of simulating the evolution of complex geographical phenomena. The core of a CA model is how to define transition rules so that realistic patterns can be simulated using empirical data. Transition rules are often defined by using mathematical equations, which do not provide easily understandable explicit forms. Furthermore, it is very difficult, if not impossible, to specify equation‐based transition rules for reflecting complex geographical processes. This paper presents a method of using ant intelligence to discover explicit transition rules of urban CA to overcome these limitations. This ‘bottom‐up’ ACO approach for achieving complex task through cooperation and interaction of ants is effective for capturing complex relationships between spatial variables and urban dynamics. A discretization technique is proposed to deal with continuous spatial variables for discovering transition rules hidden in large datasets. The ACO–CA model has been used to simulate rural–urban land conversions in Guangzhou, Guangdong, China. Preliminary results suggest that this ACO–CA method can have a better performance than the decision‐tree CA method.

This paper presents a new method to improve the classification performance for remote-sensing applications based on swarm intelligence. Traditional statistical classifiers have limitations in solving complex classification problems because of their strict assumptions. For example, data correlation between bands of remote-sensing imagery has caused problems in generating satisfactory classification using statistical methods. In this paper, ant colony optimization (ACO), based upon swarm intelligence, is used to improve the classification performance. Due to the positive feedback mechanism, ACO takes into account the correlation between attribute variables, thus avoiding issues related to band correlation. A discretization technique is incorporated in this ACO method so that classification rules can be induced from large data sets of remote-sensing images. Experiments of this ACO algorithm in the Guangzhou area reveal that it yields simpler rule sets and better accuracy than the See 5.0 decision tree method.

An automated Web service discovery requires Web service capability specifications of a high precision. Semantic-based approaches are inherently more precise than conventional keyword-based approaches. This paper proposes to build capability specifications of Web services based on an Environment Ontology, main concepts of which are the environment entities in a particular application domain and their interactions. For each environment entity, there is a tree-like hierarchical state machine modeling the effects which are to be achieved by the Web services on this environment entity. The proposed approach is based on the assumption that the Web service capability specifications, built on the effects of the environment entities, are more accessible and observable. Algorithms for constructing the domain environment ontology and the matchmaking between the Web service capability specifications are presented to show how the Web service discovery is supported. An example on Travel Service is given to illustrate this proposed approach.

In this position paper, we set out to explore the possibilities of formulating problems in requirements engineering with concepts and frameworks from cybernetics. The objective is to seek practical synergies and to understand notable differences between the two areas. We try to understand to what extent known research results from cybernetics can be applied to address problems encountered at the requirements stage in software life cycle. In particular, we try to formulate the goal-oriented requirements analysis process as a feedback control system, in which a classical "divide and conquer" design philosophy is turned into a continuous augmentation process to existing design towards an optimal one. Similarly, control frameworks for the requirements elicitation process and requirements inconsistency management process are briefly explored. Potential control variables such as information entropy value for elicitation and quantitative measurements for inconsistencies are discussed.

The service-oriented computing paradigm aims to support automated discovery and selection of web services according to user's requirements. At present, user's requirements are often represented in certain existing standard interoperable service description languages such as WSDL/OWL-S. However, general service requestors may find such languages hard to use directly due to the reason that service requirements are often partially elicited and fragmented. In this paper, we propose an automated service requirements elicitation mechanism (SREM) to help extract and accumulate relevant knowledge on service requirements. First, the SREM elicitation approach proposes to use a list of questions to narrow generic service requirements down to specific expressions of user preferences. Then, a service requirements and capability ontology is adopted to capture services requirements in breadth and precision. By integrating service requirements issued by different requestors, SREM provides non-trivial requirements guidelines and heuristic rules on service publication and discovery, also provided is a service requirements analysis mechanism that improves the accuracy of service discovery and efficiency of service composition continuously.

In this paper, we would like to quantify factors that contribute to the cacheability decision of web objects. Our study is based on a comprehensive study of object attributes that are related to the HTTP protocol transfer, proxy preference, content availability, freshness revalidation as well as the inter-relationship and dependency among them. Furthermore, the relative importance of these factors towards the final cacheability decision of web objects are also investigated. This study is important because it provides hints on how to optimize web caching performance.

This paper proposes an approach for supporting the automatic retrieval of Web services. Different from the available approaches, this approach uses a context ontology as the basis of the capability descriptions of Web services. When the capability descriptions of both Web services and the Web requests are grounded onto the same ontology, a matchmaking method has been given for judging the equivalency between them. A case study has been used for illustrating the main ideas

Design for security is extremely complicated due to the unique nature of the issue. It requires a thorough understanding about the social setting of the security system. To obtain such understanding, sensible steps to take include identifying the players involved in the system, recognizing their personal preferences, agenda and power in relation to other players, identifying the assets being protected, the vulnerable points at which the systems may fail when attacked. Equally important is to taking rationale steps to predict most likely attackers, knowing their possible motivations, and capabilities enabled by latest the technologies and resource occupations. Only based on integrated analysis on both sides, rationale, informative and efficient tradeoffs on security can be made. Unfortunately, current system development practices treat design decisions on security in an ad-hoc way, often as an afterthought. This paper proposes to use social modeling concepts to analyze the business and organizational context of systems with regard to security. The main concepts used are actor, role, agent and goal, task, and resource dependencies between actors. The approach encompasses several analysis steps on the functional and non-functional requirements in relevance to security, thus integrating security into the system design process from the outset

As the Web client devices become more and more heterogeneous, the Web content providers should cater for multi-presentation services. Transcoding is seen as an alternative to deliver such services. When deployed offline, transcoding is space-consuming, inflexible, and difficult to maintain. On-demand transcoding, on the other hand, is CPU-consuming and time-delaying. Inspired by new multimedia standards - like JPEG 2000 and MPEG-4 -, a new adaptation called modulation is devised. Unlike transcoding, modulation does not involve complex computations and can offer high data reuse, which is beneficial to Internet data access. The specifications of modulation are presented, and so is its comparison with transcoding

In this paper, we formalize the concept of a delegation network for Web intermediaries and present formal semantics for the responsibility of these actors. Key properties of the network are proven and method to judge an actor's responsibility is given. This work is important because it determines the accuracy of task execution and the feasibility of content reuse in the network

Capability specification is key problem for Web service discovery. Conventional one-step process based capability specification has its limitations. This paper proposes an approach for semantic behavior-based capability specification of Web service to stride over the limitations. Meta-level environment ontology is proposed to provide formal and sharable specifications of environment resources in a particular domain. For each environment resource, there is a corresponding hierarchical state machine specifying its dynamic characteristics. Then, effects on the environment resources are modelled with the hierarchical state machines. On the basis of the environment ontology, forest-structured communicating hierarchical state machines (FCHM) are defined and expected to be semantics of capability specification of Web services, which can be derived from the effects that Web services impose on their environments

As technology design becomes increasingly motivated by business strategy, technology users become wary of vendor intentions. Conversely, technology producers must determine what strategies they can employ to gain the trust of consumers in order to acquire and retain their business. As a result, both parties have a need to understand how business strategies shape technology design, and how such designs alter relationships among stakeholders. In this work, we use the Trusted Computing domain as an example. Can the technology consumer trust the advertised intentions of Trusted Computing Technology? Can the providers of Trusted Computing gain the trust of consumers? We use the i* Modeling Framework to analyze the links between strategies and technologies in terms of a network of social intentional relationships. By applying the qualitative i* evaluation procedure, we probe the intentions behind the strategies of technology providers, facilitating an analysis of trust.

We propose to integrate goal-oriented requirements language i* with concepts from problem frames (PF). The integration of goal and problem makes it possible to address designer's subjective intentions and the physical constraints from the environment at the same time. We illustrate the proposed approach with the meeting scheduler example

Formal Tropos is a specification language for early requirements. It is based on concepts from an agent-oriented early requirement model framework (i/sup */) and extends them with a rich temporal specification language. We demonstrated through a small case study how model checking could be used to verify early requirements written in Formal Tropos. We address issues of methodology and scalability for our earlier proposal. In particular, we propose guidelines for producing a Formal Tropos specification from an i/sup */ diagram and for deciding what model checking technique to use when a particular formal property is to be validated. We also evaluate the scope and scalability of our proposal using a tool, the T-Tool, that maps Formal Tropos specifications to a language that can be handled by NUSMV, a state-of-the-art model checker. Our experiments are based on a course management case study.

Security issues for software systems ultimately concern relationships among social actors stakeholders, system users, potential attackers - and the software acting on their behalf. We propose a methodological framework for dealing with security and privacy requirements based on i*, an agent-oriented requirements modeling language. The framework supports a set of analysis techniques. In particular, attacker analysis helps identify potential system abusers and their malicious intents. Dependency vulnerability analysis helps detect vulnerabilities in terms of organizational relationships among stakeholders. Countermeasure analysis supports the dynamic decision-making process of defensive system players in addressing vulnerabilities and threats. Finally, access control analysis bridges the gap between security requirement models and security implementation models. The framework is illustrated with an example involving security and privacy concerns in the design of agent-based health information systems. In addition, we discuss model evaluation techniques, including qualitative goal model analysis and property verification techniques based on model checking.