Importance-Driven Deep Learning System Testing

Deep Learning (DL) systems are key enablers for engineering intelligent applications due to their ability to solve complex tasks such as image recognition and machine translation. Nevertheless, using DL systems in safety- and security-critical applications requires to provide testing evidence for their dependable operation. Recent research in this direction focuses on adapting testing criteria from traditional software engineering as a means of increasing confidence for their correct behaviour. However, they are inadequate in capturing the intrinsic properties exhibited by these systems. We bridge this gap by introducing DeepImportance, a systematic testing methodology accompanied by an Importance-Driven (IDC) test adequacy criterion for DL systems. Applying IDC enables to establish a layer-wise functional understanding of the importance of DL system components and use this information to guide the generation of semantically-diverse test sets. Our empirical evaluation on several DL systems, across multiple DL datasets and with state-of-the-art adversarial generation techniques demonstrates the usefulness and effectiveness of DeepImportance and its ability to guide the engineering of more robust DL systems

A Methodology for Discovering how to Adaptively Personalize to Users using Experimental Comparisons

We explain and provide examples of a formalism that supports the methodology of discovering how to adapt and personalize technology by combining randomized experiments with variables associated with user models. We characterize a formal relationship between the use of technology to conduct A/B experiments and use of technology for adaptive personalization. The MOOClet Formalism [11] captures the equivalence between experimentation and personalization in its conceptualization of modular components of a technology. This motivates a unified software design pattern that enables technology components that can be compared in an experiment to also be adapted based on contextual data, or personalized based on user characteristics. With the aid of a concrete use case, we illustrate the potential of the MOOClet formalism for a methodology that uses randomized experiments of alternative micro-designs to discover how to adapt technology based on user characteristics, and then dynamically implements these personalized improvements in real time

PuLSE-I: Deriving instances from a product line infrastructure

Reusing assets during application engineering promises to improve the efficiency of systems development. However, in order to benefit from reusable assets, application engineering processes must incorporate when and how to use the reusable assets during single system development. However, when and how to use a reusable asset depends on what types of reusable assets have been created.Product line engineering approaches produce a reusable infrastructure for a set of products. In this paper, we present the application engineering process associated with the PuLSE product line software engineering method - PuLSE-I. PuLSE-I details how single systems can be built efficiently from the reusable product line infrastructure built during the other PuLSE activities

An Approach to Transform Public Administration into SOA-based Organizations

Nowadays, Service-Oriented Architectures (SOA) is widely spread in private organizations. However, when transferring this knowledge to Public Administration, it is realized that it has not been transformed in terms of its legal nature into organizations capable to operate under the SOA paradigm. This fact prevents public administration bodies from offering the efficient services they have been provided by different boards of governments. A high-level framework to perform this transformation is proposed. Taking it as starting point, an instance of a SOA Target Meta-Model can be obtained by means of an iterative and incremental process based on the analysis of imperatives and focused on the particular business context of each local public administration. This paper briefly presents a practical experience consisting in applying this process to a Spanish regional public administration.Junta de Andalucía TIC-578

Complementing Measurements and Real Options Concepts to Support Inter-iteration Decision-Making in Agile Projects

Agile software projects are characterized by iterative and incremental development, accommodation of changes and active customer participation. The process is driven by creating business value for the client, assuming that the client (i) is aware of it, and (ii) is capable to estimate the business value, associated with the separate features of the system to be implemented. This paper is focused on the complementary use of measurement techniques and concepts of real-option-analysis to assist clients in assessing and comparing alternative sets of requirements. Our overall objective is to provide systematic support to clients for the decision-making process on what to implement in each iteration. The design of our approach is justified by using empirical data, published earlier by other authors

Which environmental factors most strongly influence a street's appeal for bicycle transport among adults? : a conjoint study using manipulated photographs

BACKGROUND: Micro-environmental factors (specific features within a streetscape), instead of macro-environmental factors (urban planning features), are more feasible to modify in existing neighborhoods and thus more practical to target for environmental interventions. Because it is often not possible to change the whole micro-environment at once, the current study aims to determine which micro-environmental factors should get the priority to target in physical environmental interventions increasing bicycle transport. Additionally, interaction effects among micro-environmental factors on the street's appeal for bicycle transport will be determined. METHODS: In total, 1950 middle-aged adults completed a web-based questionnaire consisting of a set of 12 randomly assigned choice tasks with manipulated photographs. Seven micro-environmental factors (type of cycle path, speed limit, speed bump, vegetation, evenness of the cycle path surface, general upkeep and traffic density) were manipulated in each photograph. Conjoint analysis was used to analyze the data. RESULTS: Providing streets with a cycle path separated from motorized traffic seems to be the best strategy to increase the street's appeal for adults' bicycle transport. If this adjustment is not practically feasible, micro-environmental factors related to safety (i.e. speed limit, traffic density) may be more effective in promoting bicycle transport than micro-environmental factors related to comfort (i.e. evenness of the cycle path surface) or aesthetic (i.e. vegetation, general upkeep). On the other hand, when a more separated cycle path is already provided, micro-environmental factors related to comfort or aesthetic appeared to become more prominent. CONCLUSIONS: Findings obtained from this research could provide advice to physical environmental interventions about which environmental factors should get priority to modify in different environmental situations