4,686 research outputs found
Automated analysis of feature models: Quo vadis?
Feature models have been used since the 90's to describe software product lines as a way of reusing common parts in a family of software systems. In 2010, a systematic literature review was published summarizing the advances and settling the basis of the area of Automated Analysis of Feature Models (AAFM). From then on, different studies have applied the AAFM in different domains. In this paper, we provide an overview of the evolution of this field since 2010 by performing a systematic mapping study considering 423 primary sources. We found six different variability facets where the AAFM is being applied that define the tendencies: product configuration and derivation; testing and evolution; reverse engineering; multi-model variability-analysis; variability modelling and variability-intensive systems. We also confirmed that there is a lack of industrial evidence in most of the cases. Finally, we present where and when the papers have been published and who are the authors and institutions that are contributing to the field. We observed that the maturity is proven by the increment in the number of journals published along the years as well as the diversity of conferences and workshops where papers are published. We also suggest some synergies with other areas such as cloud or mobile computing among others that can motivate further research in the future.Ministerio de Economía y Competitividad TIN2015-70560-RJunta de Andalucía TIC-186
Overcoming Language Dichotomies: Toward Effective Program Comprehension for Mobile App Development
Mobile devices and platforms have become an established target for modern
software developers due to performant hardware and a large and growing user
base numbering in the billions. Despite their popularity, the software
development process for mobile apps comes with a set of unique, domain-specific
challenges rooted in program comprehension. Many of these challenges stem from
developer difficulties in reasoning about different representations of a
program, a phenomenon we define as a "language dichotomy". In this paper, we
reflect upon the various language dichotomies that contribute to open problems
in program comprehension and development for mobile apps. Furthermore, to help
guide the research community towards effective solutions for these problems, we
provide a roadmap of directions for future work.Comment: Invited Keynote Paper for the 26th IEEE/ACM International Conference
on Program Comprehension (ICPC'18
Rationale in Development Chat Messages: An Exploratory Study
Chat messages of development teams play an increasingly significant role in
software development, having replaced emails in some cases. Chat messages
contain information about discussed issues, considered alternatives and
argumentation leading to the decisions made during software development. These
elements, defined as rationale, are invaluable during software evolution for
documenting and reusing development knowledge. Rationale is also essential for
coping with changes and for effective maintenance of the software system.
However, exploiting the rationale hidden in the chat messages is challenging
due to the high volume of unstructured messages covering a wide range of
topics. This work presents the results of an exploratory study examining the
frequency of rationale in chat messages, the completeness of the available
rationale and the potential of automatic techniques for rationale extraction.
For this purpose, we apply content analysis and machine learning techniques on
more than 8,700 chat messages from three software development projects. Our
results show that chat messages are a rich source of rationale and that machine
learning is a promising technique for detecting rationale and identifying
different rationale elements.Comment: 11 pages, 6 figures. The 14th International Conference on Mining
Software Repositories (MSR'17
Issues of Architectural Description Languages for Handling Dynamic Reconfiguration
Dynamic reconfiguration is the action of modifying a software system at
runtime. Several works have been using architectural specification as the basis
for dynamic reconfiguration. Indeed ADLs (architecture description languages)
let architects describe the elements that could be reconfigured as well as the
set of constraints to which the system must conform during reconfiguration. In
this work, we investigate the ADL literature in order to illustrate how
reconfiguration is supported in four well-known ADLs: pi-ADL, ACME, C2SADL and
Dynamic Wright. From this review, we conclude that none of these ADLs: (i)
addresses the issue of consistently reconfiguring both instances and types;
(ii) takes into account the behaviour of architectural elements during
reconfiguration; and (iii) provides support for assessing reconfiguration,
e.g., verifying the transition against properties.Comment: 6\`eme Conf\'erence francophone sur les architectures logicielles
(CAL'2012), Montpellier : France (2012
SourcererCC: Scaling Code Clone Detection to Big Code
Despite a decade of active research, there is a marked lack in clone
detectors that scale to very large repositories of source code, in particular
for detecting near-miss clones where significant editing activities may take
place in the cloned code. We present SourcererCC, a token-based clone detector
that targets three clone types, and exploits an index to achieve scalability to
large inter-project repositories using a standard workstation. SourcererCC uses
an optimized inverted-index to quickly query the potential clones of a given
code block. Filtering heuristics based on token ordering are used to
significantly reduce the size of the index, the number of code-block
comparisons needed to detect the clones, as well as the number of required
token-comparisons needed to judge a potential clone.
We evaluate the scalability, execution time, recall and precision of
SourcererCC, and compare it to four publicly available and state-of-the-art
tools. To measure recall, we use two recent benchmarks, (1) a large benchmark
of real clones, BigCloneBench, and (2) a Mutation/Injection-based framework of
thousands of fine-grained artificial clones. We find SourcererCC has both high
recall and precision, and is able to scale to a large inter-project repository
(250MLOC) using a standard workstation.Comment: Accepted for publication at ICSE'16 (preprint, unrevised
Leveraging Program Analysis to Reduce User-Perceived Latency in Mobile Applications
Reducing network latency in mobile applications is an effective way of
improving the mobile user experience and has tangible economic benefits. This
paper presents PALOMA, a novel client-centric technique for reducing the
network latency by prefetching HTTP requests in Android apps. Our work
leverages string analysis and callback control-flow analysis to automatically
instrument apps using PALOMA's rigorous formulation of scenarios that address
"what" and "when" to prefetch. PALOMA has been shown to incur significant
runtime savings (several hundred milliseconds per prefetchable HTTP request),
both when applied on a reusable evaluation benchmark we have developed and on
real applicationsComment: ICSE 201
- …