Tracking Down Dynamic Feature Code Changes against Python Software Evolution

2016 ◽  
Author(s):  
Zhifei Chen ◽  
Wanwangying Ma ◽  
Wei Lin ◽  
Lin Chen ◽  
Baowen Xu
Keyword(s):  
Software Evolution ◽  
Dynamic Feature ◽  
Code Changes ◽  
Feature Code

scholarly journals A study of repetitiveness of code changes in software evolution

2013 ◽  
Author(s):  
Hoan Anh Nguyen ◽  
Anh Tuan Nguyen ◽  
Tung Thanh Nguyen ◽  
Tien N. Nguyen ◽  
Hridesh Rajan
Keyword(s):  
Software Evolution ◽  
Code Changes

scholarly journals A study of code change patterns for adaptive maintenance with AST analysis

2020 ◽  
Vol 10 (3) ◽  
pp. 2719
Author(s):  
Omar Meqdadi ◽  
Shadi Aljawarneh
Keyword(s):  
Open Source ◽  
Software Evolution ◽  
Source Code ◽  
Transformation Rule ◽  
Primary Concern ◽  
Adaptive Changes ◽  
Code Change ◽  
History Of ◽  
Code Changes ◽  
Open Source Systems

Example-based transformational approaches to automate adaptive maintenance changes plays an important role in software research. One primary concern of those approaches is that a set of good qualified real examples of adaptive changes previously made in the history must be identified, or otherwise the adoption of such approaches will be put in question. Unfortunately, there is rarely enough detail to clearly direct transformation rule developers to overcome the barrier of finding qualified examples for adaptive changes. This work explores the histories of several open source systems to study the repetitiveness of adaptive changes in software evolution, and hence recognizing the source code change patterns that are strongly related with the adaptive maintenance. We collected the adaptive commits from the history of numerous open source systems, then we obtained the repetitiveness frequencies of source code changes based on the analysis of Abstract Syntax Tree (AST) edit actions within an adaptive commit. Using the prevalence of the most common adaptive changes, we suggested a set of change patterns that seem correlated with adaptive maintenance. It is observed that 76.93% of the undertaken adaptive changes were represented by 12 AST code differences. Moreover, only 9 change patterns covered 64.69% to 76.58% of the total adaptive change hunks in the examined projects. The most common individual patterns are related to initializing objects and method calls changes. A correlation analysis on examined projects shows that they have very similar frequencies of the patterns correlated with adaptive changes. The observed repeated adaptive changes could be useful examples for the construction of transformation approaches

scholarly journals Commit Message Generation for Source Code Changes

2019 ◽  
Author(s):  
Shengbin Xu ◽  
Yuan Yao ◽  
Feng Xu ◽  
Tianxiao Gu ◽  
Hanghang Tong ◽  
...  
Keyword(s):  
Software Evolution ◽  
State Of The Art ◽  
Source Code ◽  
Real Data ◽  
Program Comprehension ◽  
Sources Of Information ◽  
Structure Information ◽  
Code Structure ◽  
Code Changes ◽  
Source Code Changes

Commit messages, which summarize the source code changes in natural language, are essential for program comprehension and software evolution understanding. Unfortunately, due to the lack of direct motivation, commit messages are sometimes neglected by developers, making it necessary to automatically generate such messages. State-of-the-art adopts learning based approaches such as neural machine translation models for the commit message generation problem. However, they tend to ignore the code structure information and suffer from the out-of-vocabulary issue. In this paper, we propose CoDiSum to address the above two limitations. In particular, we first extract both code structure and code semantics from the source code changes, and then jointly model these two sources of information so as to better learn the representations of the code changes. Moreover, we augment the model with copying mechanism to further mitigate the out-of-vocabulary issue. Experimental evaluations on real data demonstrate that the proposed approach significantly outperforms the state-of-the-art in terms of accurately generating the commit messages.

scholarly journals The Impact of Co-evolution of Code Production and Test Suites through Software Releases in Open Source Software Systems

2019 ◽  
Vol 9 (1) ◽  
pp. 2737-2739
Keyword(s):  
Open Source Software ◽  
Significant Relationship ◽  
Software Evolution ◽  
High Impact ◽  
Software Systems ◽  
Test Cases ◽  
Code Changes ◽  
The Impact ◽  
Test Suites ◽  
Repair Techniques

The software system evolves and changes with the time, so the test suite must be maintained according to code changes. Maintaining test cases manually is an expensive and time-consuming activity, especially for large test suites, which has motivated the recent development of automated test-repair techniques. Several researchers indicate that software evolution shows a direct impact on test suites evolution, as they have strong relationships and they should be evolved concurrently. This article aims to provide statistical evidence of having this significant relationship between the code production and its associated test suites. Seven systems along with releases are collected and eight metrics were calculated to be used in this study. The result shows how the systems under study are evolving and have a high impact on their test suites, although two metrics provide a negative significant relationship.

The Role of Visual Distractors in the Simon Effect

2017 ◽  
Vol 64 (6) ◽  
pp. 387-397 ◽  
Author(s):  
Luisa Lugli ◽  
Stefania D’Ascenzo ◽  
Roberto Nicoletti ◽  
Carlo Umiltà
Keyword(s):  
Simon Effect ◽  
Simon Task ◽  
Automatic Generation ◽  
Spatial Code ◽  
Attentional Model ◽  
Previous Evidence ◽  
Spatial Stimulus ◽  
Attentional Resources ◽  
Code Changes

Abstract. The Simon effect lies on the automatic generation of a stimulus spatial code, which, however, is not relevant for performing the task. Results typically show faster performance when stimulus and response locations correspond, rather than when they do not. Considering reaction time distributions, two types of Simon effect have been individuated, which are thought to depend on different mechanisms: visuomotor activation versus cognitive translation of spatial codes. The present study aimed to investigate whether the presence of a distractor, which affects the allocation of attentional resources and, thus, the time needed to generate the spatial code, changes the nature of the Simon effect. In four experiments, we manipulated the presence and the characteristics of the distractor. Findings extend previous evidence regarding the distinction between visuomotor activation and cognitive translation of spatial stimulus codes in a Simon task. They are discussed with reference to the attentional model of the Simon effect.

Getting Reimbursed: Testing Code Changes Are Here

2018 ◽  
Author(s):  
Antonio E. Puente ◽  
Neil H. Pliskin
Keyword(s):  
Code Changes

Impact of Software Evolution in Clustering

2012 ◽  
Vol 3 (4) ◽  
pp. 103-104
Author(s):  
CHRISTABEL WILLIAMS ◽  
Keyword(s):  
Software Evolution
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