On Evaluating Commercial Cloud Services: A Systematic Review

Background: Cloud Computing is increasingly booming in industry with many competing providers and services. Accordingly, evaluation of commercial Cloud services is necessary. However, the existing evaluation studies are relatively chaotic. There exists tremendous confusion and gap between practices and theory about Cloud services evaluation. Aim: To facilitate relieving the aforementioned chaos, this work aims to synthesize the existing evaluation implementations to outline the state-of-the-practice and also identify research opportunities in Cloud services evaluation. Method: Based on a conceptual evaluation model comprising six steps, the Systematic Literature Review (SLR) method was employed to collect relevant evidence to investigate the Cloud services evaluation step by step. Results: This SLR identified 82 relevant evaluation studies. The overall data collected from these studies essentially represent the current practical landscape of implementing Cloud services evaluation, and in turn can be reused to facilitate future evaluation work. Conclusions: Evaluation of commercial Cloud services has become a world-wide research topic. Some of the findings of this SLR identify several research gaps in the area of Cloud services evaluation (e.g., the Elasticity and Security evaluation of commercial Cloud services could be a long-term challenge), while some other findings suggest the trend of applying commercial Cloud services (e.g., compared with PaaS, IaaS seems more suitable for customers and is particularly important in industry). This SLR study itself also confirms some previous experiences and reveals new Evidence-Based Software Engineering (EBSE) lessons

Formally Verifying Sequence Diagrams for Safety Critical Systems

International audienceUML interactions, aka sequence diagrams, are frequently used by engineers to describe expected scenarios of good or bad behaviors of systems under design, as they provide allegedly a simple enough syntax to express a quite large variety of behaviors. This paper uses them to express formal safety requirements for safety critical systems in an incremental way, where the scenarios are progressively refined after checking the consistency of the requirements. As before, the semantics of these scenarios are expressed by transforming them into an intermediate semantic model amenable to formal verification. We rely on the Clock Constraint Specification Language (CCSL) as the intermediate semantic language. An SMT-based analysis tool called MyCCSL is used to check consistency of the sequence diagrams. We compare these requirements against actual execution traces to prove the validity of our transformation. In some sense, sequence diagrams and CCSL constraints both express a family of acceptable infinite traces that must include the behaviors given by the finite set of finite execution traces against which we validate. Finally, the whole process is illustrated on partial requirements for a railway transit system

Architecture design studio pedagogy for translating environmental sustainable elements

Sustainable design helps reduce negative impacts on the environment and improve building performance. The architectural educators strive to impart the sustainable requisite to students. Based on the literature review and the results of an exploratory study conducted, it is evident that the pedagogy employed by Universiti Teknologi Malaysia (UTM) architectural educators follows reflective-in-action and Kolb‘s theory. However, the environmental sustainable design elements are not reflected in most architectural design studio curriculum. In fact, only a few courses have elements of environmental sustainable design embedded in them. This research aims to determine the manner in which architectural educators in UTM translate environmental sustainable design elements to students. A mixed method was employed in this study: observation on the second year environmental design studio was done for four (4) months (n=7); a questionnaire was distributed to all architectural students (n=150), and interviews of educators (n=17) involved in workbase studios in the department of Architecture were conducted. The data from the observation was analyzed with categorical data analysis with a percent agreement set at 70% inter-coder reliability coefficient. The questionnaire was analyzed using SPSS version 20, with a one way ANOVA set at p<0.05 significance level to obtain results for inferences, while the interviews were analyzed by content analysis. Results on the analysis show that the architectural educators imparted aspect of environmental sustainable design elements directly to the students through various pedagogies, and the students used those environmental sustainable design elements in their design studio work. The results also reveal that the architectural curriculum is a hidden curriculum which embeds sustainable design elements; however, understanding of building ecosystem and ability to design sustainable buildings are not enforced on the students across all the design studios. It is only mandatory in the second semester of the second year studio since the theme is on the environmental paradigm. This implies that in order to empower students with the ability to design environmental sustainable buildings, more sustainable core subjects could be included in the studio curriculum. Findings could be employed by architectural educators and policy makers as a guide for future curriculum upgrading and development

Open source software GitHub ecosystem: a SEM approach

Open source software (OSS) is a collaborative effort. Getting affordable high-quality software with less probability of errors or fails is not far away. Thousands of open-source projects (termed repos) are alternatives to proprietary software development. More than two-thirds of companies are contributing to open source. Open source technologies like OpenStack, Docker and KVM are being used to build the next generation of digital infrastructure. An iconic example of OSS is 'GitHub' - a successful social site. GitHub is a hosting platform that host repositories (repos) based on the Git version control system. GitHub is a knowledge-based workspace. It has several features that facilitate user communication and work integration. Through this thesis I employ data extracted from GitHub, and seek to better understand the OSS ecosystem, and to what extent each of its deployed elements affects the successful development of the OSS ecosystem. In addition, I investigate a repo's growth over different time periods to test the changing behavior of the repo. From our observations developers do not follow one development methodology when developing, and growing their project, and such developers tend to cherry-pick from differing available software methodologies. GitHub API remains the main OSS location engaged to extract the metadata for this thesis's research. This extraction process is time-consuming - due to restrictive access limitations (even with authentication). I apply Structure Equation Modelling (termed SEM) to investigate the relative path relationships between the GitHub- deployed OSS elements, and I determine the path strength contributions of each element to determine the OSS repo's activity level. SEM is a multivariate statistical analysis technique used to analyze structural relationships. This technique is the combination of factor analysis and multiple regression analysis. It is used to analyze the structural relationship between measured variables and/or latent constructs. This thesis bridges the research gap around longitude OSS studies. It engages large sample-size OSS repo metadata sets, data-quality control, and multiple programming language comparisons. Querying GitHub is not direct (nor simple) yet querying for all valid repos remains important - as sometimes illegal, or unrepresentative outlier repos (which may even be quite popular) do arise, and these then need to be removed from each initial OSS's language-specific metadata set. Eight top GitHub programming languages, (selected as the most forked repos) are separately engaged in this thesis's research. This thesis observes these eight metadata sets of GitHub repos. Over time, it measures the different repo contributions of the deployed elements of each metadata set. The number of stars-provided to the repo delivers a weaker contribution to its software development processes. Sometimes forks work against the repo's progress by generating very minor negative total effects into its commit (activity) level, and by sometimes diluting the focus of the repo's software development strategies. Here, a fork may generate new ideas, create a new repo, and then draw some original repo developers off into this new software development direction, thus retarding the original repo's commit (activity) level progression. Multiple intermittent and minor version releases exert lesser GitHub JavaScript repo commit (or activity) changes because they often involve only slight OSS improvements, and because they only require minimal commit/commits contributions. More commit(s) also bring more changes to documentation, and again the GitHub OSS repo's commit (activity) level rises. There are both direct and indirect drivers of the repo's OSS activity. Pulls and commits are the strongest drivers. This suggests creating higher levels of pull requests is likely a preferred prime target consideration for the repo creator's core team of developers. This study offers a big data direction for future work. It allows for the deployment of more sophisticated statistical comparison techniques. It offers further indications around the internal and broad relationships that likely exist between GitHub's OSS big data. Its data extraction ideas suggest a link through to business/consumer consumption, and possibly how these may be connected using improved repo search algorithms that release individual business value components

Enabling Efficient Assertion Inference

peer reviewe