28,849 research outputs found
Simple algebraic data types for C
ADT is a simple tool in the spirit of Lex and Yacc that makes algebraic data types and a restricted form of pattern matching on those data types as found in SML available in C programs. ADT adds runtime checks, which make C programs written with the aid of ADT less likely to dereference a NULL pointer. The runtime tests may consume a significant amount of CPU time; hence they can be switched off once the program is suitably debugged
FixMiner: Mining Relevant Fix Patterns for Automated Program Repair
Patching is a common activity in software development. It is generally
performed on a source code base to address bugs or add new functionalities. In
this context, given the recurrence of bugs across projects, the associated
similar patches can be leveraged to extract generic fix actions. While the
literature includes various approaches leveraging similarity among patches to
guide program repair, these approaches often do not yield fix patterns that are
tractable and reusable as actionable input to APR systems. In this paper, we
propose a systematic and automated approach to mining relevant and actionable
fix patterns based on an iterative clustering strategy applied to atomic
changes within patches. The goal of FixMiner is thus to infer separate and
reusable fix patterns that can be leveraged in other patch generation systems.
Our technique, FixMiner, leverages Rich Edit Script which is a specialized tree
structure of the edit scripts that captures the AST-level context of the code
changes. FixMiner uses different tree representations of Rich Edit Scripts for
each round of clustering to identify similar changes. These are abstract syntax
trees, edit actions trees, and code context trees. We have evaluated FixMiner
on thousands of software patches collected from open source projects.
Preliminary results show that we are able to mine accurate patterns,
efficiently exploiting change information in Rich Edit Scripts. We further
integrated the mined patterns to an automated program repair prototype,
PARFixMiner, with which we are able to correctly fix 26 bugs of the Defects4J
benchmark. Beyond this quantitative performance, we show that the mined fix
patterns are sufficiently relevant to produce patches with a high probability
of correctness: 81% of PARFixMiner's generated plausible patches are correct.Comment: 31 pages, 11 figure
Trustworthy Refactoring via Decomposition and Schemes: A Complex Case Study
Widely used complex code refactoring tools lack a solid reasoning about the
correctness of the transformations they implement, whilst interest in proven
correct refactoring is ever increasing as only formal verification can provide
true confidence in applying tool-automated refactoring to industrial-scale
code. By using our strategic rewriting based refactoring specification
language, we present the decomposition of a complex transformation into smaller
steps that can be expressed as instances of refactoring schemes, then we
demonstrate the semi-automatic formal verification of the components based on a
theoretical understanding of the semantics of the programming language. The
extensible and verifiable refactoring definitions can be executed in our
interpreter built on top of a static analyser framework.Comment: In Proceedings VPT 2017, arXiv:1708.0688
Mining Fix Patterns for FindBugs Violations
In this paper, we first collect and track a large number of fixed and unfixed
violations across revisions of software.
The empirical analyses reveal that there are discrepancies in the
distributions of violations that are detected and those that are fixed, in
terms of occurrences, spread and categories, which can provide insights into
prioritizing violations.
To automatically identify patterns in violations and their fixes, we propose
an approach that utilizes convolutional neural networks to learn features and
clustering to regroup similar instances. We then evaluate the usefulness of the
identified fix patterns by applying them to unfixed violations.
The results show that developers will accept and merge a majority (69/116) of
fixes generated from the inferred fix patterns. It is also noteworthy that the
yielded patterns are applicable to four real bugs in the Defects4J major
benchmark for software testing and automated repair.Comment: Accepted for IEEE Transactions on Software Engineerin
The SP theory of intelligence: benefits and applications
This article describes existing and expected benefits of the "SP theory of
intelligence", and some potential applications. The theory aims to simplify and
integrate ideas across artificial intelligence, mainstream computing, and human
perception and cognition, with information compression as a unifying theme. It
combines conceptual simplicity with descriptive and explanatory power across
several areas of computing and cognition. In the "SP machine" -- an expression
of the SP theory which is currently realized in the form of a computer model --
there is potential for an overall simplification of computing systems,
including software. The SP theory promises deeper insights and better solutions
in several areas of application including, most notably, unsupervised learning,
natural language processing, autonomous robots, computer vision, intelligent
databases, software engineering, information compression, medical diagnosis and
big data. There is also potential in areas such as the semantic web,
bioinformatics, structuring of documents, the detection of computer viruses,
data fusion, new kinds of computer, and the development of scientific theories.
The theory promises seamless integration of structures and functions within and
between different areas of application. The potential value, worldwide, of
these benefits and applications is at least $190 billion each year. Further
development would be facilitated by the creation of a high-parallel,
open-source version of the SP machine, available to researchers everywhere.Comment: arXiv admin note: substantial text overlap with arXiv:1212.022
Model Transformations in MT
Model transformations are recognised as a vital aspect of Model Driven Development,but current approaches cover only a small part of the possible spectrum. In this paper I present the MT model transformation which shows how a QVT-like language can be extended with novel pattern matching constructs, how tracing information can be automatically constructed and visualized, and how the transformed model is pruned of extraneous elements. As MT is implemented as a DSL within the Converge language, this paper also demonstrates how a general purpose language can be embedded in a model transformation language, and how DSL development can aid experimentation and exploration of new parts of the model transformation spectrum
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