Adaptable Visualisation Based On User Needs

Software developers often ask questions about software systems and software ecosystems that entail exploration and navigation, such as who uses this component?, and where is this feature implemented?. Software visualisation can be a great aid to understanding and exploring the answers to such questions, but visualisations require expertise to implement effectively, and they do not always scale well to large systems. We propose to automatically generate software visualisations based on software models derived from open source software corpora and from an analysis of the properties of typical developers queries and commonly used visualisations. The key challenges we see are (1) understanding how to match queries to suitable visualisations, and (2) scaling visualisations effectively to very large software systems and corpora. In the paper we motivate the idea of automatic software visualisation, we enumerate the challenges and our proposals to address them, and we describe some very initial results in our attempts to develop scalable visualisations of open source software corpora.

Practical domain-specific debuggers using the Moldable Debugger framework

Understanding the run-time behavior of software systems can be a challenging activity. Debuggers are an essential category of tools used for this purpose as they give developers direct access to the running systems. Nevertheless, traditional debuggers rely on generic mechanisms to introspect and interact with the running systems, while developers reason about and formulate domain-specific questions using concepts and abstractions from their application domains. This mismatch creates an abstraction gap between the debugging needs and the debugging support leading to an inefficient and error-prone debugging effort, as developers need to recover concrete domain concepts using generic mechanisms. To reduce this gap, and increase the efficiency of the debugging process, we propose a framework for developing domain-specific debuggers, called the Moldable Debugger, that enables debugging at the level of the application domain. The Moldable Debugger is adapted to a domain by creating and combining domain-specific debugging operations with domain-specific debugging views, and adapts itself to a domain by selecting, at run time, appropriate debugging operations and views. To ensure the proposed model has practical applicability (i.e., can be used in practice to build real debuggers), we discuss, from both a performance and usability point of view, three implementation strategies. We further motivate the need for domain-specific debugging, identify a set of key requirements and show how our approach improves debugging by adapting the debugger to several domains.

Towards moldable development tools

Developers commonly ask detailed and domain-specific questions about the software systems they are developing and maintaining. Integrated development environments (IDEs) form an essential category of tools for developing software that should support software engineering decision making. Unfortunately, rigid and generic IDEs that focus on low-level programming tasks, that promote code rather than data, and that suppress customization, offer limited support for informed decision making during software development. We propose to improve decision making within IDEs by moving from generic to context-aware IDEs through moldable tools. In this paper, we promote the idea of moldable tools, illustrate it with concrete examples, and discuss future research directions.

Polymorphism in the Spotlight: Studying its Prevalence in Java and Smalltalk

Subtype polymorphism is a cornerstone of object-oriented programming. By hiding variability in behavior behind a uniform interface, polymorphism decouples clients from providers and thus enables genericity, modularity and extensi- bility. At the same time, however, it scatters the implementation of the behavior over multiple classes thus potentially hampering program comprehension. The extent to which polymorphism is used in real programs and the impact of polymorphism on program comprehension are not very well understood. We report on a preliminary study of the prevalence of polymorphism in several hundred open source software systems written in Smalltalk, one of the oldest object-oriented programming languages, and in Java, one of the most widespread ones. Although a large portion of the call sites in these systems are polymorphic, a majority have a small number of potential candidates. Smalltalk uses polymorphism to a much greater extent than Java. We discuss how these findings can be used as input for more detailed studies in program comprehension and for better developer support in the IDE.

Towards Self-Learning Radio-Based Localization Systems

Location-awareness indoors will be an inseparable feature of mobile services/applications in future wireless networks. Its current ubiquitous availability is still obstructed by technological challenges and privacy issues. We propose an innovative approach towards the concept of indoor positioning with main goal to develop a system that is self-learning and able to adapt to various radio propagation environments. The approach combines estimation of propagation conditions, subsequent appropriate channel modelling and optimisation feedback to the used positioning algorithm. Main advantages of the proposal are decreased system set-up effort, automatic re-calibration and increased precision.

Learning software-maintenance tasks in offshoring projects: a cognitive-load perspective

Individual learning is central to the success of the transition phase in software mainte-nance offshoring projects. However, little is known on how learning activities, such as on-the-job training and formal presentations, are effectively combined during the tran-sition phase. In this study, we present and test propositions derived from cognitive load theory. The results of a multiple-case study suggest that learning effectiveness was highest when learning tasks such as authentic maintenance requests were used. Con-sistent with cognitive load theory, learning tasks were most effective when they imposed moderate cognitive load. Our data indicate that cognitive load was influenced by the expertise of the onsite coordinator, by intrinsic task complexity, by the degree of specifi-cation of tasks, and by supportive information. Cultural and semantic distances may in-fluence learning by inhibiting supportive information, specification, and the assignment of learning tasks.

UAVNet: A Mobile Wireless Mesh Network Using Unmanned Aerial Vehicles

We developed UAVNet, a framework for the autonomous deployment of a flying Wireless Mesh Network using small quadrocopter-based Unmanned Aerial Vehicles (UAVs). The flying wireless mesh nodes are automatically interconnected to each other and building an IEEE 802.11s wireless mesh network. The implemented UAVNet prototype is able to autonomously interconnect two end systems by setting up an airborne relay, consisting of one or several flying wireless mesh nodes. The developed software includes basic functionality to control the UAVs and to setup, deploy, manage, and monitor a wireless mesh network. Our evaluations have shown that UAVNet can significantly improve network performance.

Governing individual learning in the transition phase of software maintenance offshoring: a dynamic perspective

Prior studies suggest that clients need to actively govern knowledge transfer to vendor staff in offshore outsourcing. In this paper, we analyze longitudinal data from four software maintenance offshore out-sourcing projects to explore why governance may be needed for knowledge transfer and how governance and the individual learning of vendor engineers inter-act over time. Our results suggest that self-control is central to learning, but may be hampered by low levels of trust and expertise at the outset of projects. For these foundations to develop, clients initially need to exert high amounts of formal and clan controls to enforce learning activities against barriers to knowledge sharing. Once learning activities occur, trust and expertise increase and control portfolios may show greater emphases on self-control.

Learning Software-Maintenance Tasks in the Transition Phase of Offshore Outsourcing Projects: Two Learning-Theoretical Perspectives

The increasing practice of offshore outsourcing software maintenance has posed the challenge of effectively transferring knowledge to individual software engineers of the vendor. In this theoretical paper, we discuss the implications of two learning theories, the model of work-based learning (MWBL) and cognitive load theory (CLT), for knowledge transfer during the transition phase. Taken together, the theories suggest that learning mechanisms need to be aligned with the type of knowledge (tacit versus explicit), task characteristics (complexity and recurrence), and the recipients’ expertise. The MWBL proposes that learning mechanisms need to include conceptual and practical activities based on the relative importance of explicit and tacit knowledge. CLT explains how effective portfolios of learning mechanisms change over time. While jobshadowing, completion tasks, and supportive information may prevail at the outset of transition, they may be replaced by the work on conventional tasks towards the end of transition.

Managing Knowledge Transfer in Software-Maintenance Outsourcing Transitions: A System-Dynamics Perspective

The existing literature suggests that transitions in software-maintenance offshore outsourcing projects are prone to knowledge transfer blockades, i.e. situations in which the activities that would yield effective knowledge transfer do not occur, and that client management involvement is central to overcome them. However, the theoretical understanding of the knowledge transfer blockade is limited, and the reactive management behavior reported in case studies suggests that practitioners may frequently be astonished by the dynamics that may give rise to the blockade. Drawing on recent research from offshore sourcing and reference theories, this study proposes a system dynamics framework that may explain why knowledge transfer blockades emerge and how and why client management can overcome the blockade. The results suggest that blockades may emerge from a vicious circle of weak learning due to cognitive overload of vendor staff and resulting negative ability attributions that result in reduced helping behavior and thus aggravate cognitive load. Client management may avoid these vicious circles by selecting vendor staff with strong prior related experience. Longer phases of coexistence of vendor staff and subject matter experts and high formal and clan controls may also mitigate vicious circles.

A Case for CDN-as-a-Service in the Cloud: A Mobile Cloud Networking Argument

Content Distribution Networks are mandatory components of modern web architectures, with plenty of vendors offering their services. Despite its maturity, new paradigms and architecture models are still being developed in this area. Cloud Computing, on the other hand, is a more recent concept which has expanded extremely quickly, with new services being regularly added to cloud management software suites such as OpenStack. The main contribution of this paper is the architecture and the development of an open source CDN that can be provisioned in an on-demand, pay-as-you-go model thereby enabling the CDN as a Service paradigm. We describe our experience with integration of CDNaaS framework in a cloud environment, as a service for enterprise users. We emphasize the flexibility and elasticity of such a model, with each CDN instance being delivered on-demand and associated to personalized caching policies as well as an optimized choice of Points of Presence based on exact requirements of an enterprise customer. Our development is based on the framework developed in the Mobile Cloud Networking EU FP7 project, which offers its enterprise users a common framework to instantiate and control services. CDNaaS is one of the core support components in this project as is tasked to deliver different type of multimedia content to several thousands of users geographically distributed. It integrates seamlessly in the MCN service life-cycle and as such enjoys all benefits of a common design environment, allowing for an improved interoperability with the rest of the services within the MCN ecosystem.

Explaining Endogenous Control Change in Outsourced Software Projects

Given the centrality of control for achieving success in outsourced software projects, past research has identified key exogenous factors that determine the choice of controls. This view of exogenously driven control choice is based on a number of assumptions; particularly, clients and vendors are seen as separate cognitive entities that combat opportunistic threats under environmental uncertainty by one-off choices or infrequent revisions of controls. In this paper we complement this perspective by acknowledging that an outsourced software project may be characterized as a collective, evolving process faced with the challenge of coping with cognitive limitations of both client and vendor through a continuous process of learning. We argue that if viewed in this way, controls are less subject of a deliberate choice but rather are subject of endogenously driven change, i.e. controls evolve in close interaction with the evolving software project. Accordingly, we suggest a complementary model of endogenous control, where controls mediate individual and collective learning processes. Our research contributes to a better understanding of the dynamics in outsourced software projects. It also spells out methodological implications that may help improve cross-section control research.

Personal Digital Assistant 2.0 - A Software Prototype for Cognitive Cities

This paper presents a software prototype of a personal digital assistant 2.0. Based on soft computing methods and cognitive computing this mobile application prototype improves calendar and mobility management in cognitive cities. Applying fuzzy cognitive maps and evolutionary algorithms, the prototype represents a next step towards the realization of cognitive cities (i.e., smart cities enhanced with cognition). A user scenario and a test version of the prototype are included for didactical reasons.