scholarly journals Feature Location in Source Code by Trace-Based Impact Analysis and Information Retrieval

2012 ◽  
Vol E95-D (1) ◽  
pp. 205-214
Author(s):  
Zhengong CAI ◽  
Xiaohu YANG ◽  
Xinyu WANG ◽  
Aleksander J. KAVS
Keyword(s):  
Information Retrieval ◽  
Impact Analysis ◽  
Source Code ◽  
Feature Location

scholarly journals A Structure-Driven Method for Information Retrieval-Based Software Change Impact Analysis

2018 ◽  
Vol 2018 ◽  
pp. 1-16
Author(s):  
Yun He ◽  
Tong Li ◽  
Wei Wang ◽  
Wei Lan ◽  
Xiang Li
Keyword(s):  
Information Retrieval ◽  
Impact Analysis ◽  
Contextual Information ◽  
Source Code ◽  
Word Embedding ◽  
Bag Of Words ◽  
Change Impact Analysis ◽  
Software Change ◽  
Change Impact ◽  
Single Method

An important application of information retrieval technology is software change impact analysis. Existing information retrieval-based change impact analysis methods select a single method to transform the source code corpus into vectors in a process known as indexing. The single method is chosen from two primary methods, known as the bag-of-words and word embedding models, each having their specific advantages and disadvantages. The bag-of-words model records every word in the source code but ignores contextual information in the corpus. The word embedding model records the contextual information but loses detail for individual words. To address this problem, we propose a structure-driven method for information retrieval-based change impact analysis (named SDM-CIA). SDM-CIA integrates the bag-of-words and word embedding models based on the software’s structure. Our experiments using a standard benchmark shows that when compared with the existing methods, SDM-CIA improves on precision performance, recall performance, F-score performance, and MRR performance by an average of 3.65%, 3.82%, 3.6%, and 10.28%, respectively. Our experiments confirm the effectiveness of SDM-CIA.

scholarly journals An Integrated Model for Information Retrieval Based Change Impact Analysis

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Wei Wang ◽  
Yun He ◽  
Tong Li ◽  
Jiajun Zhu ◽  
Jinzhuo Liu
Keyword(s):  
Information Retrieval ◽  
Impact Analysis ◽  
Source Code ◽  
Integrated Approach ◽  
Change Impact Analysis ◽  
Cut Points ◽  
Change Impact ◽  
The Individual ◽  
The Impact ◽  
Open Source Systems

The paper presents an approach to combine multiple existing information retrieval (IR) techniques to support change impact analysis, which seeks to identify the possible outcomes of a change or determine the necessary modifications for affecting a desired change. The approach integrates a bag-of-words based IR technique, where each class or method is abstracted as a set of words, and a neural network based IR technique to derive conceptual couplings from the source code of a software system. We report rigorous empirical assessments of the changes of three open source systems: jEdit, muCommander, and JabRef. The impact sets obtained are evaluated at the method level of granularity, and the results show that our integrated approach provides statistically significant improvements in accuracy across several cut points relative to the accuracies provided by the individual methods employed independently. Improvements in F-score values of up to 7.3%, 10.9%, and 17.3% are obtained over a baseline technique for jEdit, muCommander, and JabRef, respectively.

Feature Location Using Probabilistic Ranking of Methods Based on Execution Scenarios and Information Retrieval

2007 ◽  
Vol 33 (6) ◽  
pp. 420-432 ◽  
Author(s):  
Denys Poshyvanyk ◽  
Yann-Gael Gueheneuc ◽  
Andrian Marcus ◽  
Giuliano Antoniol ◽  
Vaclav Rajlich
Keyword(s):  
Information Retrieval ◽  
Feature Location

Tool Support for Software Artefact Traceability in DevOps Practice

2020 ◽  
pp. 130-167
Author(s):  
Iresha Rubasinghe ◽  
Dulani Meedeniya ◽  
Indika Perera
Keyword(s):  
Software Development ◽  
Impact Analysis ◽  
Software Process ◽  
Source Code ◽  
Tool Support ◽  
Management Approach ◽  
Development Method ◽  
Continuous Integration ◽  
Trace Link ◽  
F Measure

Software development in DevOps practice is a widely used approach to cope with the demand for frequent artefact changes. These changes require a well-defined method to manage artefact consistency to ease the continuous integration process. This chapter proposes a traceability management approach for the artefact types in the main phases of the software process including requirements, design, source code, testing, and configuration. This chapter addresses traceability management, including trace link creation, change detection, impact analysis, change propagation, validation, and visualisation. This chapter presents a tool named SAT-Analyser that is applicable for any software development method and designed for continuous integration, multi-user collaboration, and DevOps tool stack compatibility. The SAT-Analyser is assessed using case studies and shown an impact analysis accuracy of 0.93 of F-measure. Further, the feedback by DevOps practitioners has shown the suitability and innovativeness of the proposed approach.

A visual approach to support Change Impact Analysis in object-oriented source code

2020 ◽  
Author(s):  
Renan Pereira Biazini ◽  
Ronaldo Celso Messias Correia ◽  
Danilo Medeiros Eler ◽  
Rogerio Eduardo Garcia
Keyword(s):  
Impact Analysis ◽  
Source Code ◽  
Object Oriented ◽  
Change Impact Analysis ◽  
Visual Approach ◽  
Change Impact

scholarly journals Impact Analysis of Granularity Levels on Feature Location Technique

2014 ◽  
pp. 135-149 ◽  
Author(s):  
Chakkrit Tantithamthavorn ◽  
Akinori Ihara ◽  
Hideaki Hata ◽  
Kenichi Matsumoto
Keyword(s):  
Impact Analysis ◽  
Feature Location

CODE-CHANGE IMPACT ANALYSIS USING COUNTERFACTUALS: THEORY AND IMPLEMENTATION

2013 ◽  
Vol 23 (10) ◽  
pp. 1459-1486
Author(s):  
MANUEL PERALTA ◽  
SUPRATIK MUKHOPADHYAY
Keyword(s):  
Static Analysis ◽  
Theorem Proving ◽  
Program Analysis ◽  
Impact Analysis ◽  
Source Code ◽  
Analysis Framework ◽  
Change Impact Analysis ◽  
Code Change ◽  
Change Impact ◽  
Automated Tool

This article shows a novel program analysis framework based on Lewis' theory of counterfactuals. Using this framework we are capable of performing change-impact static analysis on a program's source code. In other words, we are able to prove the properties induced by changes to a given program before applying these changes. Our contribution is two-fold; we show how to use Lewis' logic of counterfactuals to prove that proposed changes to a program preserve its correctness. We report the development of an automated tool based on resolution and theorem proving for performing code change-impact analysis.

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