04:00 - 04:30

• Automatic and Continuous Software Architecture Validation

  Software systems tend to suffer from architectural problems as they are being developed. While modern software development methodologies such as Agile and Dev-Ops suggest different ways of assuring code quality, very little attention is paid to maintaining high quality of the architecture of the evolving systems. By detecting and alerting about violations of the intended software architecture, one can often avoid code-level bad smells such as spaghetti code.  Typically, if one wants to reason about the software architecture, the burden of first defining the intended architecture falls on the developer's shoulders. This includes definition of valid and invalid dependencies between software components. However, the developers are seldom familiar with the entire software system, which makes this task difficult, time consuming and error-prone.  We propose and implement a solution for automatic detection of architectural violations in software artifacts. The solution, which utilizes a number of predefined and user-defined patterns, does not require prior knowledge of the system or its intended architecture. We propose to leverage this solution as part of the nightly build process used by development teams, thus achieving continuous automatic validation of the system's software architecture. As we show in multiple open-source and proprietary cases, a small set of predefined patterns can detect architectural violations as they are introduced over the course of development, and also capture deterioration in existing architectural problems. By evaluating the tool on relatively large open-source projects, we also validate its scalability and practical applicability to large software systems.

Maayan Goldstein; Itai Segall

IBM Haifa Research Lab, Israel

04:30 - 05:00

• Comparing Software Architecture Recovery Techniques Using Accurate Dependencies

  Many techniques have been proposed to automatically recover software architectures from software implementations. A thorough comparison among the recovery techniques is needed to understand their effectiveness and applicability. This study improves on previous studies in two ways. First, we study the impact of leveraging more accurate symbol dependencies on the accuracy of architecture recovery techniques. Previous studies have not seriously considered how the quality of the input might affect the quality of the output for architecture recovery techniques. Second, we study a system (Chromium) that is substantially larger (9.7 million lines of code) than those included in previous studies. Obtaining the ground-truth architecture of Chromium involved two years of collaboration with its developers. As part of this work we developed a new sub module-based technique to recover preliminary versions of ground-truth architectures. The other systems that we study have been examined previously. In some cases, we have updated the ground-truth architectures to newer versions, and in other cases we have corrected newly discovered inconsistencies. Our evaluation of nine variants of six state-of-the-art architecture recovery techniques shows that symbol dependencies generally produce architectures with higher accuracies than include dependencies. Despite this improvement, the overall accuracy is low for all recovery techniques. The results suggest that (1) in addition to architecture recovery techniques, the accuracy of dependencies used as their inputs is another factor to consider for high recovery accuracy, and (2) more accurate recovery techniques are needed. Our results show that some of the studied architecture recovery techniques scale to the 10M lines-of-code range (the size of Chromium), whereas others do not.

   

  Preprint available:

Thibaud Lutellier; Devin Chollack; Joshua Garcia; Lin Tan; Derek Rayside; Nenad Medvidovic; Robert Kroeger

University of Waterloo, Canada; George Mason University, USA; University of Southern California, USA; Google, Canada

05:00 - 05:30

• SPF: A Middleware for Social Interaction in Mobile Proximity Environments

  Smart interconnected devices are changing our lives and are turning conventional spaces into smart ones. Physical proximity, a key enabler of social interactions in the old days is not exploited by smart solutions, where the social dimension is always managed through the Internet. This paper aims to blend the two forces and proposes the idea of social smart space, where modern technologies can help regain and renew social interactions, and where proximity is seen as enabler for dedicated and customized functionality provided by users to users. A Social Proximity Framework (SPF) provides the basis for the creation of this new flavor of smart spaces. Two different versions of the SPF, based on different communication infrastructures, help explain the characteristics of the different components, and show how the SPF can benefit from emerging connection-less communication protocols. A first assessment of the two implementations concludes the paper.

   

  Preprint available:

Luciano Baresi; Laurent-Walter Goix; Sam Guinea; Valerio Panzica La Manna; Jacopo Aliprandi; Dario Archetti

Politecnico di Milano, Italy; Econocom-Osiatis, France