How to Improve the Production Process for interactive TV with semi-formal Methods

The central question for this paper is how to improve the production process by closing the gap between industrial designers and software engineers of television(TV)-based User Interfaces (UI) in an industrial environment. Software engineers are highly interested whether one UI design can be converted into several fully functional UIs for TV products with different screen properties. The aim of the software engineers is to apply automatic layout and scaling in order to speed up and improve the production process. However, the question is whether a UI design lends itself for such automatic layout and scaling. This is investigated by analysing a prototype UI design done by industrial designers. In a first requirements study, industrial designers had created meta-annotations on top of their UI design in order to disclose their design rationale for discussions with software engineers. In a second study, five (out of ten) industrial designers assessed the potential of four different meta-annotation approaches. The question was which annotation method industrial designers would prefer and whether it could satisfy the technical requirements of the software engineering process. One main result is that the industrial designers preferred the method they were already familiar with, which therefore seems to be the most effective one although the main objective of automatic layout and scaling could still not be achieved.

Teachers' professional development in a community

The goal of this article was to study teachers' professional development related to web-based learning in the context of the teacher community. The object was to learn in what kind of networks teachers share the knowledge of web-based learning and what are the factors in the community that support or challenge teachers professional development of web-based learning. The findings of the study revealed that there are teachers who are especially active, called the central actors in this study, in the teacher community who collaborate and share knowledge of web-based learning. These central actors share both technical and pedagogical knowledge of web-based learning in networks that include both internal and external relations in the community and involve people, artefacts and a variety of media. Furthermore, the central actors appear to bridge different fields of teaching expertise in their community. According to the central actors' experiences the important factors that support teachers' professional development of web-based learning in the community are; the possibility to learn from colleagues and from everyday working practices, an emotionally safe atmosphere, the leader's personal support and community-level commitment. Also, the flexibility in work planning, challenging pupils, shared lessons with colleagues, training events in an authentic work environment and colleagues' professionalism are considered meaningful for professional development. As challenges, the knowledge sharing of web-based learning in the community needs mutual interests, transactive memory, time and facilities, peer support, a safe atmosphere and meaningful pedagogical practices. On the basis of the findings of the study it is suggested that by intensive collaboration related to web-based learning it may be possible to break the boundaries of individual teachership and create such sociocultural activities which support collaborative professional development in the teacher community. Teachers' in-service training programs should be more sensitive to the culture of teacher communities and teachers' reciprocal relations. Further, teacher trainers should design teachers' in-service training of web-based learning in co-evolution with supporting networks which include the media and artefacts as well as people.

Fulfilled and missed requirements for online reservation systems: an empirical investigation of Austrian and Swiss hotels

Temporal data are a core element of a reservation. In this paper we formulate 10 requirements and 14 sub-requirements for handling temporal data in online hotel reservation systems (OHRS) from a usability viewpoint. We test the fulfillment of these requirements for city and resort hotels in Austria and Switzerland. Some of the requirements are widely met; however, many requirements are fulfilled only by a surprisingly small number of hotels. In particular, numerous systems offer options for selecting data which lead to error messages in the next step. A few screenshots illustrate flaws of the systems. We also draw conclusions on the state of applying software engineering principles in the development of Web pages.

Geo-Locating the Knowledge Transfer in StackOverflow

By analyzing the transactions in Stack Overflow we can get a glimpse of the way in which the different geographical regions in the world contribute to the knowledge market represented by the website. In this paper we aggregate the knowledge transfer from the level of the users to the level of geographical regions and learn that Europe and North America are the principal and virtually equal contributors; Asia comes as a distant third, mainly represented by India; and Oceania contributes less than Asia but more than South America and Africa together.

Measurement and stability of the pointing of the BepiColombo Laser Altimeter under thermal load

The BepiColombo Laser Altimeter (BELA) has been selected to fly on ESA׳s BepiColombo mission to Mercury. The instrument will be the first European laser altimeter designed for interplanetary flight. This paper describes the setup used to characterize the angular movements of BELA under the simulated environmental conditions that the instrument will encounter when orbiting Mercury. The system comprises a laser transmitter and a receiving telescope, which can move with respect to each other under thermal load. Tests performed using the Engineering Qualification Model show that the setup is accurate enough to characterize angular movements of the instrument components to an accuracy of ≈10 μrad. The qualification instrument is thermally stable to operate during all mission phases around Mercury proving that the transmitter and receiver sections will remain within the alignment requirements during its mission.

Development of a 3D Game Engine

This paper presents the development history and specification of a 3D game engine titled "Spark Engine". The term "engine" is used to describe a complex graphics software suite that streamlines application development and provides efficient rendering functionality. A game engine specifically provides tools to simplify game development. Spark Engine is fully shader driven and is built on top of Microsoft's XNA Framework. It is a reusable and flexible platform that can be used to build any type of graphics application ranging from gaming to simulation. The engine was released as open source software under the New BSD License with an interest in furthering its development.

Identifying Moderator Variables Through Requirements Elicitation Experiments Limitations

Interviews are the most widely used elicitation technique in Requirements Engineering (RE). Despite its importance, research in interviews is quite limited, in particular from an experimental perspective. We have performed a series of experiments exploring the relative effectiveness of structured and unstructured interviews. This line of research has been active in Information Systems in the past years, so that our experiments can be aggregated together with existing ones to obtain guidelines for practice. Experimental aggregation is a demanding task. It requires not only a large number of experiments, but also considering the influence of the existing moderators. However, in the current state of the practice in RE, those moderators are unknown. We believe that analyzing the threats to validity in interviewing experiments may give insight about how to improve further replications and the corresponding aggregations. It is likely that this strategy may be applied in other Software Engineering areas as well.

Comparative analysis of meta-analysis methods: when to use which?

Background: Several meta-analysis methods can be used to quantitatively combine the results of a group of experiments, including the weighted mean difference, statistical vote counting, the parametric response ratio and the non-parametric response ratio. The software engineering community has focused on the weighted mean difference method. However, other meta-analysis methods have distinct strengths, such as being able to be used when variances are not reported. There are as yet no guidelines to indicate which method is best for use in each case. Aim: Compile a set of rules that SE researchers can use to ascertain which aggregation method is best for use in the synthesis phase of a systematic review. Method: Monte Carlo simulation varying the number of experiments in the meta analyses, the number of subjects that they include, their variance and effect size. We empirically calculated the reliability and statistical power in each case Results: WMD is generally reliable if the variance is low, whereas its power depends on the effect size and number of subjects per meta-analysis; the reliability of RR is generally unaffected by changes in variance, but it does require more subjects than WMD to be powerful; NPRR is the most reliable method, but it is not very powerful; SVC behaves well when the effect size is moderate, but is less reliable with other effect sizes. Detailed tables of results are annexed. Conclusions: Before undertaking statistical aggregation in software engineering, it is worthwhile checking whether there is any appreciable difference in the reliability and power of the methods. If there is, software engineers should select the method that optimizes both parameters.

On the Mahalanobis Distance Classification Criterion for Multidimensional Normal Distributions

Many existing engineering works model the statistical characteristics of the entities under study as normal distributions. These models are eventually used for decision making, requiring in practice the definition of the classification region corresponding to the desired confidence level. Surprisingly enough, however, a great amount of computer vision works using multidimensional normal models leave unspecified or fail to establish correct confidence regions due to misconceptions on the features of Gaussian functions or to wrong analogies with the unidimensional case. The resulting regions incur in deviations that can be unacceptable in high-dimensional models. Here we provide a comprehensive derivation of the optimal confidence regions for multivariate normal distributions of arbitrary dimensionality. To this end, firstly we derive the condition for region optimality of general continuous multidimensional distributions, and then we apply it to the widespread case of the normal probability density function. The obtained results are used to analyze the confidence error incurred by previous works related to vision research, showing that deviations caused by wrong regions may turn into unacceptable as dimensionality increases. To support the theoretical analysis, a quantitative example in the context of moving object detection by means of background modeling is given.

Determining practices achievement in the requirement management process using a two-stage questionnaire

This paper aims to obtain a baseline snapshot of the requirement management process using a two-stage questionnaire to identify both performed and non-performed CMMI practices. The questionnaire proposed in this paper may help with the assessment of the requirement management process, provide useful information related to the current state of the process, and indicate those practices that require immediate attention with the aim of begin a Software Process Improvement program.

Harmony: Towards automated self-adaptive consistency in cloud storage

In just a few years cloud computing has become a very popular paradigm and a business success story, with storage being one of the key features. To achieve high data availability, cloud storage services rely on replication. In this context, one major challenge is data consistency. In contrast to traditional approaches that are mostly based on strong consistency, many cloud storage services opt for weaker consistency models in order to achieve better availability and performance. This comes at the cost of a high probability of stale data being read, as the replicas involved in the reads may not always have the most recent write. In this paper, we propose a novel approach, named Harmony, which adaptively tunes the consistency level at run-time according to the application requirements. The key idea behind Harmony is an intelligent estimation model of stale reads, allowing to elastically scale up or down the number of replicas involved in read operations to maintain a low (possibly zero) tolerable fraction of stale reads. As a result, Harmony can meet the desired consistency of the applications while achieving good performance. We have implemented Harmony and performed extensive evaluations with the Cassandra cloud storage on Grid?5000 testbed and on Amazon EC2. The results show that Harmony can achieve good performance without exceeding the tolerated number of stale reads. For instance, in contrast to the static eventual consistency used in Cassandra, Harmony reduces the stale data being read by almost 80% while adding only minimal latency. Meanwhile, it improves the throughput of the system by 45% while maintaining the desired consistency requirements of the applications when compared to the strong consistency model in Cassandra.

Ranking web services using centralities and social indicators

Nowadays, developers of web application mashups face a sheer overwhelming variety and pluralism of web services. Therefore, choosing appropriate web services to achieve specific goals requires a certain amount of knowledge as well as expertise. In order to support users in choosing appropriate web services it is not only important to match their search criteria to a dataset of possible choices but also to rank the results according to their relevance, thus minimizing the time it takes for taking such a choice. Therefore, we investigated six ranking approaches in an empirical manner and compared them to each other. Moreover, we have had a look on how one can combine those ranking algorithms linearly in order to maximize the quality of their outputs.

Agile user stories enriched with usability

Usability is a critical quality factor. Therefore, like traditional software teams, agile teams have to address usability to properly catch their users experience. There exists an interesting debate in the agile and usability communities about how to achieve this integration. Our aim is to contribute to this debate by discussing the incorporation of particular usability recommendations into user stories, one of the most popular artifacts for communicating agile requirements. In this paper, we explore the implications of usability for both the structure of and the process for defining user stories. We discuss what changes the incorporation of particular usability issues may introduce in a user story. Although our findings require more empirical validation, we think that they are a good starting point for further research on this line.

A Recommendation Framework Based on the Analytic Network Process and its Application in the Semantic Technology Domain

When users face a certain problem needing a product, service, or action to solve it, selecting the best alternative among them can be a dicult task due to the uncertainty of their quality. This is especially the case in the domains where users do not have an expertise, like for example in Software Engineering. Multiple criteria decision making (MCDM) methods are methods that help making better decisions when facing the complex problem of selecting the best solution among a group of alternatives that can be compared according to different conflicting criteria. In MCDM problems, alternatives represent concrete products, services or actions that will help in achieving a goal, while criteria represent the characteristics of these alternatives that are important for making a decision.