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{{Paper
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https://ceur-ws.org/Vol-1791/preface.pdf
SATToSE 2016: The Post-Proceedings Editorial
Haidar Osman1 , Davide Di Ruscio2 , Vadim Zaytsev3 ,
Mircea Lungu4 , Anya Helene Bagge5
University of Bern, Switzerland osman@inf.unibe.ch
1
2
University of L’Aquila, Italy, davide.diruscio@univaq.it
3
Raincode, Belgium, vadim@grammarware.net
4
University of Groningen, The Netherlands m.f.lungu@rug.nl
5
University of Bergen, Norway anya@ii.uib.no
Venue
SATToSE is the Seminar Series on Advanced Techniques and Tools for Software
Evolution. Its previous editions have happened in Waulsort (Belgium, 2008),
Côte d’Opale (France, 2009), Montpellier (France, 2010), Koblenz (Germany,
2011, 2012), Bern (Switzerland, 2013), L’Aquila (Italy, 2014), and Mons (Bel-
gium 2015). Its ninth edition took place in Bergen, Norway on 11–13 July 2016.
Each edition of SATToSE witnesses presentations on software visualisation tech-
niques, tools for coevolving various software artefacts, their consistency manage-
ment, runtime adaptability and context-awareness, as well as empirical results
about software evolution.
The goal of SATToSE is to gather both undergraduate and graduate students
to showcase their research, exchange ideas, improve their communication skills,
attend and contribute technology showdown and hackathons.
The highlights of the programme included four invited talks (given by Oscar
Nierstrasz, Venera Arnaoudova, Aiko Yamashita, and Romain Robbes), an inter-
active tutorial (by Venera Arnaoudova), and a hands-on hackathon (by Gregorio
Robles). The detailed programme, as well as the pre-proceedings drafts can be
found on our website: http://sattose.org/2016.
Selection process
Each pre-proceedings submission was reviewed by at least three different peers.
All submissions with a conflict of interest with one of the editors (co-authored
by them or their colleagues) were handled by the other editor. We would like to
express our gratitude to the program committee (listed in lexicographic order)
who provided the reviews.
⇧ Bram Adams ⇧ Georgios Gousios
⇧ Alexander Bergel ⇧ Kim Mens
⇧ Serge Demeyer ⇧ Haidar Osman
⇧ Coen De Roover ⇧ Romain Robbes
⇧ Michael W. Godfrey ⇧ Vadim Zaytsev
The call for post-proceedings contributions was communicated to all par-
ticipants after the event. Only some decided to pursue the finalisation of their
contribution for the post-proceedings where they might have solicited more co-
authors, changed the title, and included more results. As a result, we have re-
ceived 6 submissions of the extended versions of pre-proceedings abstracts.
Each submitted report for the post-proceedings has been assigned a shepherd
to ensure that the authors took the reviews from the pre-proceedings phase into
account. The emphasis was put on clear problem definitions and descriptions
of advanced aspects of the techniques contemplated in the solution, as opposed
to the finality of the obtained results. Thus, most submissions are intermediate
reports on ongoing work or summaries of previously developed tools and papers.
Organisation
⇧ General Chair: Anya Helene Bagge (University of Bergen)
⇧ Program Chair: Mircea Lungu (University of Groningen)
⇧ Hackathon Chair: Gregorio Robles (Universidad Rey Juan Carlos)
⇧ Proceedings Chair: Haidar Osman (University of Bern)
⇧ Social Media Chair: Vadim Zaytsev (Raincode)
⇧ Local Organization Chair: Anna Maria Eilertsen (University of Bergen)
⇧ Local Staff:
• Katerina Ivanova (University of Bergen)
• Eivind Jahren (University of Bergen)
• Håkon Lerring (University of Bergen)
• Niklas Trippler (University of Bergen)
• Patrick Monslaup (University of Bergen)
⇧ Steering Committee Chair Kim Mens (Université catholique de Louvain)
⇧ Steering Committee:
• Anya Helene Bagge (University of Bergen, Norway)
• Coen De Roever (Free University Brussels)
• Davide Di Ruscio (University of L’Aquila, Italy)
• Michael W. Godfrey (University of Waterloo)
• Mircea Lungu (University of Groningen)
• Oscar Nierstrasz (University of Bern)
• Vadim Zaytsev (Universiteit van Amsterdam)
⇧ Post-proceedings Editors:
• Haidar Osman (University of Bern)
• Mircea Lungu (University of Groningen)
Contents of the volume
⇧ Beyond Context-Oriented Software
The last two decades have seen a lot of research on context-aware and
context-oriented software development technologies, across subfields of com-
puter science. This research area is slowly starting to mature and researchers
currently explore how to unify different solutions proposed in these subfields.
We envision that within another decade some of these solutions will make it
into mainstream software development approaches, tools and environments.
Most end-user software built by that time will be context-aware and able
to adapt seamlessly to its context of use (devices, surrounding environment,
and users? preferences). This transition from traditional to context-oriented
software also requires a mindset shift in users. If users are to accept adap-
tive systems, they need to be in control. Context-orientation should evolve
to become less technology- and more user-centric, putting the user back in
control. A first step is to provide good feedback to the user about when and
what adaptations take place, and mechanisms to allow users to partly control
certain adaptations, followed by easily usable and understandable personal-
isation mechanisms dedicated to each end user. Eventually, when adaptive
systems become completely natural and adopted by end users, this will cul-
minate in our vision where users are in full control of relevant features or
adaptations of applications of their interest, selected on-demand from online
feature clouds, and integrated automatically into the running system.
⇧ Building Ecosystem-Aware Tools Using the Ecosystem Monitoring Frame-
work
Integrating ecosystem data into developer tools can be very beneficial but
is usually complicated. By automating the routine parts of this task we can
reduce the amount of work needed to develop these tools. We have devel-
oped a framework that allows developers to quickly develop new tools that
use ecosystem data. This framework automates the execution of user-defined
analyses on ecosystem projects, allowing the developer to focus only on what
ecosystem data is needed for her tool and how to present it.
⇧ On the Non-Generalizability in Bug Prediction
Bug prediction is a technique used to estimate the most bug-prone entities in
software systems. Bug prediction approaches vary in many design options,
such as dependent variables, independent variables, and machine learning
models. Choosing the right combination of design options to build an effec-
tive bug predictor is hard. Previous studies do not consider this complexity
and draw conclusions based on fewer-than-necessary experiments. We argue
that each software project is unique from the perspective of its development
process. Consequently, metrics and machine learning models perform dif-
ferently on different projects, in the context of bug prediction. We confirm
our hypothesis empirically by running different bug predictors on different
systems. We show there are no universal bug prediction configurations that
work on all projects.
⇧ Towards Efficient Object-Centric Debugging with Declarative Breakpoints
Debuggers are central tools in IDEs for inspecting and repairing software
systems. However, they are often generic tools that operate at a low level
of abstraction. Developers need to use simple breakpoint capabilities and
interpret the raw data presented by the debugger. They are confronted with
a large abstraction gap between application domain and debugger presen-
tations. We propose an approach for debugging object-oriented programs,
using expressive and flexible breakpoints that operate on sets of objects in-
stead of a particular line of source code. This allows developers to adapt the
debugger to their domain and work at a higher level of abstraction, which
enables them to be more productive. We give an overview of the approach
and demonstrate the idea with a simple use case, and we discuss how our
approach differs from existing work.
⇧ Comparing The Accumulation Of Technical Debt Between Two Applications
Developed With Spring Web MVC And Apache Struts 2
This paper presents the results of an observational study that investigates
the differences between two widely used software development frameworks
for Java EE applications. Also, it presents the accumulation of Technical
Debt and the evolution of code quality metrics of software developed using
these frameworks. Considering that web applications hold the lion?s share
of today?s IT industry, this study focuses on two widely popular Java EE
frameworks, namely Spring Web MVC Framework and Apache Struts 2. In
particular, we have developed one system over four versions in both frame-
works while monitoring Technical Debt and code quality metrics. The find-
ings indicate that software developed based on these frameworks is relatively
free of Technical Debt. Moreover, we have not noticed any significant dif-
ferences between the two frameworks in terms of Technical Debt, from the
perspective of source code metrics. Finally, conducting this study, we real-
ized that if the framework is properly used it can potentiality lead to high
quality and maintainable systems.
⇧ CSS Corpus for Reproducible Analysis
Reproducibility of research heavily depends on the availability of the datasets
from the experiments in the context of metaprogramming, the corpus of the
code that was used to run the analyses and transformations. In the case of
CSS, the problem is even more acute since the web is a constantly chang-
ing environment where the same address can refer to a frequently changing
artefact. In this report, we explain how we created a corpus of CSS files
as a part of our project of building a framework for analysing style sheets.
We also include two case studies of explanatory nature showing how style
sheets from various websites go about coding conventions and about code
duplication. We believe this work will be useful for other CSS researchers to
compare techniques they develop, on a uniform yet realistic dataset.