12,869 research outputs found
Automated Fixing of Programs with Contracts
This paper describes AutoFix, an automatic debugging technique that can fix
faults in general-purpose software. To provide high-quality fix suggestions and
to enable automation of the whole debugging process, AutoFix relies on the
presence of simple specification elements in the form of contracts (such as
pre- and postconditions). Using contracts enhances the precision of dynamic
analysis techniques for fault detection and localization, and for validating
fixes. The only required user input to the AutoFix supporting tool is then a
faulty program annotated with contracts; the tool produces a collection of
validated fixes for the fault ranked according to an estimate of their
suitability.
In an extensive experimental evaluation, we applied AutoFix to over 200
faults in four code bases of different maturity and quality (of implementation
and of contracts). AutoFix successfully fixed 42% of the faults, producing, in
the majority of cases, corrections of quality comparable to those competent
programmers would write; the used computational resources were modest, with an
average time per fix below 20 minutes on commodity hardware. These figures
compare favorably to the state of the art in automated program fixing, and
demonstrate that the AutoFix approach is successfully applicable to reduce the
debugging burden in real-world scenarios.Comment: Minor changes after proofreadin
Semantics-based Automated Web Testing
We present TAO, a software testing tool performing automated test and oracle
generation based on a semantic approach. TAO entangles grammar-based test
generation with automated semantics evaluation using a denotational semantics
framework. We show how TAO can be incorporated with the Selenium automation
tool for automated web testing, and how TAO can be further extended to support
automated delta debugging, where a failing web test script can be
systematically reduced based on grammar-directed strategies. A real-life
parking website is adopted throughout the paper to demonstrate the effectivity
of our semantics-based web testing approach.Comment: In Proceedings WWV 2015, arXiv:1508.0338
Test Case Purification for Improving Fault Localization
Finding and fixing bugs are time-consuming activities in software
development. Spectrum-based fault localization aims to identify the faulty
position in source code based on the execution trace of test cases. Failing
test cases and their assertions form test oracles for the failing behavior of
the system under analysis. In this paper, we propose a novel concept of
spectrum driven test case purification for improving fault localization. The
goal of test case purification is to separate existing test cases into small
fractions (called purified test cases) and to enhance the test oracles to
further localize faults. Combining with an original fault localization
technique (e.g., Tarantula), test case purification results in better ranking
the program statements. Our experiments on 1800 faults in six open-source Java
programs show that test case purification can effectively improve existing
fault localization techniques
IntRepair: Informed Repairing of Integer Overflows
Integer overflows have threatened software applications for decades. Thus, in
this paper, we propose a novel technique to provide automatic repairs of
integer overflows in C source code. Our technique, based on static symbolic
execution, fuses detection, repair generation and validation. This technique is
implemented in a prototype named IntRepair. We applied IntRepair to 2,052C
programs (approx. 1 million lines of code) contained in SAMATE's Juliet test
suite and 50 synthesized programs that range up to 20KLOC. Our experimental
results show that IntRepair is able to effectively detect integer overflows and
successfully repair them, while only increasing the source code (LOC) and
binary (Kb) size by around 1%, respectively. Further, we present the results of
a user study with 30 participants which shows that IntRepair repairs are more
than 10x efficient as compared to manually generated code repairsComment: Accepted for publication at the IEEE TSE journal. arXiv admin note:
text overlap with arXiv:1710.0372
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