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Caio A. N. Lima

dblp:03/10404 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2012
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Software engineering, system software, and programming languages
1 paper
Software maintenance and evolution · 77% Empirical software engineering · 23%
Computer graphics and multimedia
1 paper
Visualization and visual analytics · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Visualization and visual analytics
software visualization
0.112012
On the proactive and interactive visualization for feature evolution comprehension: An industrial investigation · ICSE 2012
Software maintenance and evolution
program comprehension
0.112012
On the proactive and interactive visualization for feature evolution comprehension: An industrial investigation · ICSE 2012
Empirical software engineering
controlled experiment
0.012012
On the proactive and interactive visualization for feature evolution comprehension: An industrial investigation · ICSE 2012

Methods — techniques the papers use, named apart from their topics

static analysis · 0.3interactive visualization · 0.3
YearPublicationVenuePosition
2012 On the proactive and interactive visualization for feature evolution comprehension: An industrial investigation
abstract
Program comprehension is a key activity through maintenance and evolution of large-scale software systems. The understanding of a program often requires the evolution analysis of individual functionalities, so-called features. The comprehension of evolving features is not trivial as their implementations are often tangled and scattered through many modules. Even worse, existing techniques are limited in providing developers with direct means for visualizing the evolution of features' code. This work presents a proactive and interactive visualization strategy to enable feature evolution analysis. It proactively identifies code elements of evolving features and provides multiple views to present their structure under different perspectives. The novel visualization strategy was compared to a lightweight visualization strategy based on a tree-structure. We ran a controlled experiment with industry developers, who performed feature evolution comprehension tasks on an industrial-strength software. The results showed that the use of the proposed strategy presented significant gains in terms of correctness and execution time for feature evolution comprehension tasks.
Renato Lima Novais, Camila Nunes, Caio A. N. Lima, Elder Cirilo, Francisco Dantas, Alessandro F. Garcia 0001, Manoel G. Mendonça
ICSE3