157,690 research outputs found
An empirical study on code comprehension: DCI compared to OO
Comprehension of source code affects software development, especially its maintenance where reading code is the most time consuming performed activity. A programming paradigm imposes a style of arranging the source code that is aligned with a way of thinking toward a computable solution. Then, a programming paradigm with a programming language represents an important factor for source code comprehension. Object-Oriented (OO) is the dominant paradigm today. Although, it was criticized from its beginning and recently an alternative has been proposed. In an OO source code, system functions cannot escape outside the definition of classes and their descriptions live inside multiple class declarations. This results in an obfuscated code, a lost sense the run-time, and in a lack of global knowledge that weaken the understandability of the source code at system level. A new paradigm is emerging to address these and other OO issues, this is the Data Context Interaction (DCI) paradigm. We conducted the first human subject related controlled experiment to evaluate the effects of DCI on code comprehension compared to OO. We looked for correctness, time consumption, and focus of attention during comprehension tasks. We also present a novel approach using metrics from Social Network Analysis to analyze what we call the Cognitive Network of Language Elements (CNLE) that is built by programmers while comprehending a system. We consider this approach useful to understand source code properties uncovered from code reading cognitive tasks. The results obtained are preliminary in nature but indicate that DCI-trygve approach produces more comprehensible source code and promotes a stronger focus the attention in important files when programmers are reading code during program comprehension. Regarding reading time spent on files, we were not able to indicate with statistical significance which approach allows programmers to consume less time
Understanding object-oriented source code from the behavioural perspective
Comprehension is a key activity that underpins a variety of software maintenance and engineering tasks. The task of understanding object-oriented systems is hampered by the fact that the code segments that are related to a user-level function tend to be distributed across the system. We introduce a tool-supported code extraction technique that addresses this issue. Given a minimal amount of information about a behavioural element of the system that is of interest (such as a use-case), it extracts a trail of the methods (and method invocations) through the system that are needed in order to achieve an understanding of the implementation of the element of interest. We demonstrate the feasibility of our approach by implementing it as part of a code extraction tool, presenting a case study and evaluating the approach and tool against a set of established criteria for program comprehension tools
A Linear Logic Programming Language for Concurrent Programming over Graph Structures
We have designed a new logic programming language called LM (Linear Meld) for
programming graph-based algorithms in a declarative fashion. Our language is
based on linear logic, an expressive logical system where logical facts can be
consumed. Because LM integrates both classical and linear logic, LM tends to be
more expressive than other logic programming languages. LM programs are
naturally concurrent because facts are partitioned by nodes of a graph data
structure. Computation is performed at the node level while communication
happens between connected nodes. In this paper, we present the syntax and
operational semantics of our language and illustrate its use through a number
of examples.Comment: ICLP 2014, TPLP 201
Dual Language and ENL Comprehension: A First Grade Study for Students at Risk for Delayed English Language Development
This research began by asking how dual language programming impacts English comprehension for ENL students. Research was conducted within one first grade dual language cohort with five bilingual students. The data was collected by interviewing teachers and students, utilizing historical comprehension data, observing read alouds, and assessing student comprehension. Findings revealed that comprehension in a participantās first language was positively related to English comprehension. However, individual student differences impacted the extent of the correlation. Furthermore, dual language teachers implemented common instructional practices to scaffold ENL student comprehension. Therefore, the data implied that native language instruction is integral, student backgrounds and differences need to be analyzed, and dual language educators need adequate professional development to best aid ENL comprehension
Reify Your Collection Queries for Modularity and Speed!
Modularity and efficiency are often contradicting requirements, such that
programers have to trade one for the other. We analyze this dilemma in the
context of programs operating on collections. Performance-critical code using
collections need often to be hand-optimized, leading to non-modular, brittle,
and redundant code. In principle, this dilemma could be avoided by automatic
collection-specific optimizations, such as fusion of collection traversals,
usage of indexing, or reordering of filters. Unfortunately, it is not obvious
how to encode such optimizations in terms of ordinary collection APIs, because
the program operating on the collections is not reified and hence cannot be
analyzed.
We propose SQuOpt, the Scala Query Optimizer--a deep embedding of the Scala
collections API that allows such analyses and optimizations to be defined and
executed within Scala, without relying on external tools or compiler
extensions. SQuOpt provides the same "look and feel" (syntax and static typing
guarantees) as the standard collections API. We evaluate SQuOpt by
re-implementing several code analyses of the Findbugs tool using SQuOpt, show
average speedups of 12x with a maximum of 12800x and hence demonstrate that
SQuOpt can reconcile modularity and efficiency in real-world applications.Comment: 20 page
- ā¦