8,042 research outputs found
Automatic Detection of System-Specific Conventions Unknown to Developers
International audienceIn Apache Ant, a convention to improve maintenance was introduced in 2004 stating a new way to close files instead of the Java generic InputStream.close(). Yet, six years after its introduction, this convention was still not generally known to the developers. Two existing solutions could help in these cases. First, one can deprecate entities, but, in our example, one can hardly deprecate Java's method. Second, one can create a system-specific rule to be automatically enforced. In a preceding publication , we showed that system-specific rules are more likely to be noticed by developers than generic ones. However, in practice, developers rarely create specific rules. We therefore propose to free the developers from the need to create rules by automatically detecting such conventions from source code repositories. This is done by mining the change history of the system to discover similar changes being applied over several revisions. The proposed approach is applied to real-world systems, and the extracted rules are validated with the help of experts. The results show that many rules are in fact relevant for the experts
C to O-O Translation: Beyond the Easy Stuff
Can we reuse some of the huge code-base developed in C to take advantage of
modern programming language features such as type safety, object-orientation,
and contracts? This paper presents a source-to-source translation of C code
into Eiffel, a modern object-oriented programming language, and the supporting
tool C2Eif. The translation is completely automatic and supports the entire C
language (ANSI, as well as many GNU C Compiler extensions, through CIL) as used
in practice, including its usage of native system libraries and inlined
assembly code. Our experiments show that C2Eif can handle C applications and
libraries of significant size (such as vim and libgsl), as well as challenging
benchmarks such as the GCC torture tests. The produced Eiffel code is
functionally equivalent to the original C code, and takes advantage of some of
Eiffel's object-oriented features to produce safe and easy-to-debug
translations
Assessing Comment Quality in Object-Oriented Languages
Previous studies have shown that high-quality code comments support developers in software maintenance and program comprehension tasks. However, the semi-structured nature of comments, several conventions to write comments, and the lack of quality assessment tools for all aspects of comments make comment evaluation and maintenance a non-trivial problem. To understand the specification of high-quality comments to build effective assessment tools, our thesis emphasizes acquiring a multi-perspective view of the comments, which can be approached by analyzing (1) the academic support for comment quality assessment, (2) developer commenting practices across languages, and (3) developer concerns about comments.
Our findings regarding the academic support for assessing comment quality showed that researchers primarily focus on Java in the last decade even though the trend of using polyglot environments in software projects is increasing. Similarly, the trend of analyzing specific types of code comments (method comments, or inline comments) is increasing, but the studies rarely analyze class comments. We found 21 quality attributes that researchers consider to assess comment quality, and manual assessment is still the most commonly used technique to assess various quality attributes. Our analysis of developer commenting practices showed that developers embed a mixed level of details in class comments, ranging from high-level class overviews to low-level implementation details across programming languages. They follow style guidelines regarding what information to write in class comments but violate the structure and syntax guidelines. They primarily face problems locating relevant guidelines to write consistent and informative comments, verifying the adherence of their comments to the guidelines, and evaluating the overall state of comment quality.
To help researchers and developers in building comment quality assessment tools, we contribute: (i) a systematic literature review (SLR) of ten years (2010–2020) of research on assessing comment quality, (ii) a taxonomy of quality attributes used to assess comment quality, (iii) an empirically validated taxonomy of class comment information types from three programming languages, (iv) a multi-programming-language approach to automatically identify the comment information types, (v) an empirically validated taxonomy of comment convention-related questions and recommendation from various Q&A forums, and (vi) a tool to gather discussions from multiple developer sources, such as Stack Overflow, and mailing lists.
Our contributions provide various kinds of empirical evidence of the developer’s interest in reducing efforts in the software documentation process, of the limited support developers get in automatically assessing comment quality, and of the challenges they face in writing high-quality comments. This work lays the foundation for future effective comment quality assessment tools and techniques
What to Fix? Distinguishing between design and non-design rules in automated tools
Technical debt---design shortcuts taken to optimize for delivery speed---is a
critical part of long-term software costs. Consequently, automatically
detecting technical debt is a high priority for software practitioners.
Software quality tool vendors have responded to this need by positioning their
tools to detect and manage technical debt. While these tools bundle a number of
rules, it is hard for users to understand which rules identify design issues,
as opposed to syntactic quality. This is important, since previous studies have
revealed the most significant technical debt is related to design issues. Other
research has focused on comparing these tools on open source projects, but
these comparisons have not looked at whether the rules were relevant to design.
We conducted an empirical study using a structured categorization approach, and
manually classify 466 software quality rules from three industry tools---CAST,
SonarQube, and NDepend. We found that most of these rules were easily labeled
as either not design (55%) or design (19%). The remainder (26%) resulted in
disagreements among the labelers. Our results are a first step in formalizing a
definition of a design rule, in order to support automatic detection.Comment: Long version of accepted short paper at International Conference on
Software Architecture 2017 (Gothenburg, SE
Software that Learns from its Own Failures
All non-trivial software systems suffer from unanticipated production
failures. However, those systems are passive with respect to failures and do
not take advantage of them in order to improve their future behavior: they
simply wait for them to happen and trigger hard-coded failure recovery
strategies. Instead, I propose a new paradigm in which software systems learn
from their own failures. By using an advanced monitoring system they have a
constant awareness of their own state and health. They are designed in order to
automatically explore alternative recovery strategies inferred from past
successful and failed executions. Their recovery capabilities are assessed by
self-injection of controlled failures; this process produces knowledge in
prevision of future unanticipated failures
Improving Prolog programs: Refactoring for Prolog
Refactoring is an established technique from the object-oriented (OO)
programming community to restructure code: it aims at improving software
readability, maintainability and extensibility. Although refactoring is not
tied to the OO-paradigm in particular, its ideas have not been applied to Logic
Programming until now.
This paper applies the ideas of refactoring to Prolog programs. A catalogue
is presented listing refactorings classified according to scope. Some of the
refactorings have been adapted from the OO-paradigm, while others have been
specifically designed for Prolog. The discrepancy between intended and
operational semantics in Prolog is also addressed by some of the refactorings.
In addition, ViPReSS, a semi-automatic refactoring browser, is discussed and
the experience with applying ViPReSS to a large Prolog legacy system is
reported. The main conclusion is that refactoring is both a viable technique in
Prolog and a rather desirable one.Comment: To appear in Theory and Practice of Logic Programming (TPLP
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