22,404 research outputs found
Automated Test Input Generation for Android: Are We There Yet?
Mobile applications, often simply called "apps", are increasingly widespread,
and we use them daily to perform a number of activities. Like all software,
apps must be adequately tested to gain confidence that they behave correctly.
Therefore, in recent years, researchers and practitioners alike have begun to
investigate ways to automate apps testing. In particular, because of Android's
open source nature and its large share of the market, a great deal of research
has been performed on input generation techniques for apps that run on the
Android operating systems. At this point in time, there are in fact a number of
such techniques in the literature, which differ in the way they generate
inputs, the strategy they use to explore the behavior of the app under test,
and the specific heuristics they use. To better understand the strengths and
weaknesses of these existing approaches, and get general insight on ways they
could be made more effective, in this paper we perform a thorough comparison of
the main existing test input generation tools for Android. In our comparison,
we evaluate the effectiveness of these tools, and their corresponding
techniques, according to four metrics: code coverage, ability to detect faults,
ability to work on multiple platforms, and ease of use. Our results provide a
clear picture of the state of the art in input generation for Android apps and
identify future research directions that, if suitably investigated, could lead
to more effective and efficient testing tools for Android
LittleDarwin: a Feature-Rich and Extensible Mutation Testing Framework for Large and Complex Java Systems
Mutation testing is a well-studied method for increasing the quality of a
test suite. We designed LittleDarwin as a mutation testing framework able to
cope with large and complex Java software systems, while still being easily
extensible with new experimental components. LittleDarwin addresses two
existing problems in the domain of mutation testing: having a tool able to work
within an industrial setting, and yet, be open to extension for cutting edge
techniques provided by academia. LittleDarwin already offers higher-order
mutation, null type mutants, mutant sampling, manual mutation, and mutant
subsumption analysis. There is no tool today available with all these features
that is able to work with typical industrial software systems.Comment: Pre-proceedings of the 7th IPM International Conference on
Fundamentals of Software Engineerin
Semantic Component Composition
Building complex software systems necessitates the use of component-based
architectures. In theory, of the set of components needed for a design, only
some small portion of them are "custom"; the rest are reused or refactored
existing pieces of software. Unfortunately, this is an idealized situation.
Just because two components should work together does not mean that they will
work together.
The "glue" that holds components together is not just technology. The
contracts that bind complex systems together implicitly define more than their
explicit type. These "conceptual contracts" describe essential aspects of
extra-system semantics: e.g., object models, type systems, data representation,
interface action semantics, legal and contractual obligations, and more.
Designers and developers spend inordinate amounts of time technologically
duct-taping systems to fulfill these conceptual contracts because system-wide
semantics have not been rigorously characterized or codified. This paper
describes a formal characterization of the problem and discusses an initial
implementation of the resulting theoretical system.Comment: 9 pages, submitted to GCSE/SAIG '0
Mutation Testing as a Safety Net for Test Code Refactoring
Refactoring is an activity that improves the internal structure of the code
without altering its external behavior. When performed on the production code,
the tests can be used to verify that the external behavior of the production
code is preserved. However, when the refactoring is performed on test code,
there is no safety net that assures that the external behavior of the test code
is preserved. In this paper, we propose to adopt mutation testing as a means to
verify if the behavior of the test code is preserved after refactoring.
Moreover, we also show how this approach can be used to identify the part of
the test code which is improperly refactored
Understanding Android Obfuscation Techniques: A Large-Scale Investigation in the Wild
In this paper, we seek to better understand Android obfuscation and depict a
holistic view of the usage of obfuscation through a large-scale investigation
in the wild. In particular, we focus on four popular obfuscation approaches:
identifier renaming, string encryption, Java reflection, and packing. To obtain
the meaningful statistical results, we designed efficient and lightweight
detection models for each obfuscation technique and applied them to our massive
APK datasets (collected from Google Play, multiple third-party markets, and
malware databases). We have learned several interesting facts from the result.
For example, malware authors use string encryption more frequently, and more
apps on third-party markets than Google Play are packed. We are also interested
in the explanation of each finding. Therefore we carry out in-depth code
analysis on some Android apps after sampling. We believe our study will help
developers select the most suitable obfuscation approach, and in the meantime
help researchers improve code analysis systems in the right direction
Proactive Empirical Assessment of New Language Feature Adoption via Automated Refactoring: The Case of Java 8 Default Methods
Programming languages and platforms improve over time, sometimes resulting in
new language features that offer many benefits. However, despite these
benefits, developers may not always be willing to adopt them in their projects
for various reasons. In this paper, we describe an empirical study where we
assess the adoption of a particular new language feature. Studying how
developers use (or do not use) new language features is important in
programming language research and engineering because it gives designers
insight into the usability of the language to create meaning programs in that
language. This knowledge, in turn, can drive future innovations in the area.
Here, we explore Java 8 default methods, which allow interfaces to contain
(instance) method implementations.
Default methods can ease interface evolution, make certain ubiquitous design
patterns redundant, and improve both modularity and maintainability. A focus of
this work is to discover, through a scientific approach and a novel technique,
situations where developers found these constructs useful and where they did
not, and the reasons for each. Although several studies center around assessing
new language features, to the best of our knowledge, this kind of construct has
not been previously considered.
Despite their benefits, we found that developers did not adopt default
methods in all situations. Our study consisted of submitting pull requests
introducing the language feature to 19 real-world, open source Java projects
without altering original program semantics. This novel assessment technique is
proactive in that the adoption was driven by an automatic refactoring approach
rather than waiting for developers to discover and integrate the feature
themselves. In this way, we set forth best practices and patterns of using the
language feature effectively earlier rather than later and are able to possibly
guide (near) future language evolution. We foresee this technique to be useful
in assessing other new language features, design patterns, and other
programming idioms
- …