UniSa - IRIS Institutional Research Information System

PALOMBA, Fabio
 Distribuzione geografica
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Continente #
AS - Asia 11.857
NA - Nord America 6.470
EU - Europa 3.176
SA - Sud America 724
Continente sconosciuto - Info sul continente non disponibili 426
AF - Africa 129
OC - Oceania 15
Totale 22.797
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Nazione #
HK - Hong Kong 8.565
US - Stati Uniti d'America 6.247
IT - Italia 1.511
SG - Singapore 1.478
CN - Cina 627
BR - Brasile 541
VN - Vietnam 473
RU - Federazione Russa 337
DE - Germania 325
FR - Francia 178
BD - Bangladesh 129
IE - Irlanda 120
IN - India 112
UA - Ucraina 107
CA - Canada 103
GB - Regno Unito 99
TR - Turchia 99
FI - Finlandia 98
KR - Corea 79
NL - Olanda 78
SE - Svezia 69
AR - Argentina 64
MX - Messico 57
ES - Italia 48
JP - Giappone 45
IQ - Iraq 44
CZ - Repubblica Ceca 41
ZA - Sudafrica 38
PL - Polonia 35
EC - Ecuador 34
PK - Pakistan 32
ID - Indonesia 29
SA - Arabia Saudita 26
AT - Austria 25
VE - Venezuela 23
NO - Norvegia 18
PH - Filippine 18
CO - Colombia 16
MA - Marocco 16
CL - Cile 15
EG - Egitto 14
RO - Romania 14
KE - Kenya 13
PY - Paraguay 13
UZ - Uzbekistan 13
JM - Giamaica 12
DZ - Algeria 11
AU - Australia 10
CR - Costa Rica 10
TN - Tunisia 10
CH - Svizzera 9
MY - Malesia 9
JO - Giordania 8
NP - Nepal 8
PT - Portogallo 8
TH - Thailandia 8
BE - Belgio 7
DO - Repubblica Dominicana 7
HR - Croazia 7
IL - Israele 7
PE - Perù 7
AL - Albania 6
BG - Bulgaria 6
EE - Estonia 6
GR - Grecia 6
KZ - Kazakistan 6
HN - Honduras 5
TT - Trinidad e Tobago 5
UY - Uruguay 5
BY - Bielorussia 4
IR - Iran 4
NI - Nicaragua 4
NZ - Nuova Zelanda 4
PS - Palestinian Territory 4
SV - El Salvador 4
AE - Emirati Arabi Uniti 3
BO - Bolivia 3
CI - Costa d'Avorio 3
DK - Danimarca 3
ET - Etiopia 3
GE - Georgia 3
GT - Guatemala 3
KW - Kuwait 3
LB - Libano 3
MR - Mauritania 3
OM - Oman 3
PA - Panama 3
PR - Porto Rico 3
SC - Seychelles 3
SK - Slovacchia (Repubblica Slovacca) 3
AZ - Azerbaigian 2
BF - Burkina Faso 2
BN - Brunei Darussalam 2
CY - Cipro 2
LT - Lituania 2
MD - Moldavia 2
QA - Qatar 2
SY - Repubblica araba siriana 2
TW - Taiwan 2
XK - ???statistics.table.value.countryCode.XK??? 2
Totale 22.338
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Città #
Hong Kong 8.549
San Jose 986
Singapore 796
Ashburn 539
Ann Arbor 510
Milan 505
Council Bluffs 366
Chandler 352
Dallas 350
Princeton 310
Woodbridge 231
Beijing 204
The Dalles 189
Munich 175
Rome 172
Ho Chi Minh City 160
Jacksonville 147
Lauterbourg 136
Houston 123
Dublin 117
Wilmington 108
Los Angeles 101
Hanoi 96
Salerno 91
Santa Clara 91
Naples 86
Moscow 76
Memphis 74
New York 70
São Paulo 70
Izmir 68
Helsinki 55
Andover 47
Dong Ket 45
Fisciano 44
Boardman 41
Montreal 41
Tokyo 41
Nuremberg 40
Amsterdam 38
Brno 38
Figino 38
Columbus 36
Orem 36
Nanjing 33
Denver 32
Chennai 31
Pellezzano 31
Frankfurt am Main 30
Warsaw 30
Phoenix 29
Atlanta 27
Brooklyn 26
Washington 26
Chicago 24
Fairfield 24
Turin 24
Barcelona 23
London 23
Mexico City 23
Stockholm 23
Da Nang 19
Toronto 19
Dearborn 18
Haiphong 18
Johannesburg 18
Manchester 18
Poplar 18
Rio de Janeiro 18
Trondheim 18
Norwalk 17
Pune 17
Buffalo 16
Düsseldorf 16
Guangzhou 16
San Francisco 16
Seattle 16
Turku 16
Baghdad 15
Belo Horizonte 15
Nijmegen 15
Changsha 14
Riyadh 14
Mumbai 13
Nairobi 13
Quito 13
Tashkent 13
Bologna 12
Boston 12
Guayaquil 12
Nanchang 12
Nocera Inferiore 12
Redwood City 12
Salvador 12
Seoul 12
Dhaka 11
Montoro 11
Ninh Bình 11
Shenyang 10
Vienna 10
Totale 17.415
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Nome #
An empirical study into the effects of transpilation on quantum circuit smells 889
Dealing With Cultural Dispersion: a Novel Theoretical Framework for Software Engineering Research and Practice 857
CASpER: A Plug-in for Automated Code Smell Detection and Refactoring 763
Software testing and Android applications: a large-scale empirical study 521
QUANTUMOONLIGHT: A low-code platform to experiment with quantum machine learning 504
The Secret Life of Software Vulnerabilities: A Large-Scale Empirical Study 486
Machine learning-based test smell detection 456
Beyond Technical Aspects: How Do Community Smells Influence the Intensity of Code Smells? 446
Software engineering for quantum programming: How far are we? 446
Recommending and Localizing Change Requests for Mobile Apps Based on User Reviews 427
Testing of mobile applications in the wild: A large-scale empirical study on android apps 418
Static test flakiness prediction: How Far Can We Go? 386
Quantum Software Engineering Issues and Challenges: Insights from Practitioners 362
On the effectiveness of manual and automatic unit test generation: Ten years later 355
On the adequacy of static analysis warnings with respect to code smell prediction 326
Unsupervised Labor Intelligence Systems: A Detection Approach and Its Evaluation: A Case Study in the Netherlands 325
A Systematic Literature Review on the Code Smells Datasets and Validation Mechanisms 279
Developer-Driven Code Smell Prioritization 271
Rubbing salt in the wound? A large-scale investigation into the effects of refactoring on security 265
SENEM: A software engineering-enabled educational metaverse 244
Into the ML-Universe: An improved classification and characterization of machine-learning projects 240
Comparing within-and cross-project machine learning algorithms for code smell detection 225
Technical debt in AI-enabled systems: On the prevalence, severity, impact, and management strategies for code and architecture 206
Do developers update third-party libraries in mobile apps? 189
VITRuM: A Plug-In for the Visualization of Test-Related Metrics 181
When and Why Your Code Starts to Smell Bad (and Whether the Smells Go Away) 164
Anti-Pattern Detection: Methods, Challenges, and Open Issues 159
ARIES: An Eclipse plugin to Support Extract Class Refactoring 157
A Textual-based Technique for Smell Detection 153
An Experimental Investigation on the Innate Relationship between Quality and Refactoring 151
Lightweight Assessment of Test-Case Effectiveness using Source-Code-Quality Indicators 151
Enhancing change prediction models using developer-related factors 148
User reviews matter! Tracking crowdsourced reviews to support evolution of successful apps 146
There and back again: Can you compile that snapshot? 145
When and Why Your Code Starts to Smell Bad 142
An empirical study on the performance of vulnerability prediction models evaluated applying real-world labelling 140
Landfill: an Open Datase of Code Smells with Public Evaluation 139
Do they Really Smell Bad? A Study on Developers’ Perception of Bad Code Smells 138
Automatic Test Case Generation: What If Test Code Quality Matters? 138
On the Role of Developer’s Scattered Changes in Bug Prediction 137
Toward Understanding the Impact of Refactoring on Program Comprehension 136
Developer-Related Factors in Change Prediction: An Empirical Assessment 136
An Empirical Investigation into the Nature of Test Smells 135
A large-scale empirical study on the lifecycle of code smell co-occurrences 134
Mining Version Histories for Detecting Code Smells 133
Dynamic Selection of Classifiers in Bug Prediction: An Adaptive Method 131
Meet C4SE: Your New Collaborator for Software Engineering Tasks 129
Investigating code smell co-occurrences using association rule learning: A replicated study 128
Good Fences Make Good Neighbours? On the Impact of Cultural and Geographical Dispersion on Community Smells 124
Understanding developer practices and code smells diffusion in ai-enabled software: A preliminary study 123
Towards Quantum-algorithms-as-a-service 120
Textual Analysis and Software Quality: Challenges and Opportunities 119
Detecting Bad Smells in Source Code using Change History Information 119
Early and Realistic Exploitability Prediction of Just-Disclosed Software Vulnerabilities: How Reliable Can It Be? 117
Software-based energy profiling of Android apps: Simple, efficient and reliable? 117
On the Diffusion of Test Smells in Automatically Generated Test Code: An Empirical Study 114
An Exploratory Study on the Relationship between Changes and Refactoring 114
PETrA: A software-based tool for estimating the energy profile of android applications 113
Lightweight detection of Android-specific code smells: The aDoctor project 113
The Scent of a Smell: An Extensive Comparison between Textual and Structural Smells 113
A Developer Centered Bug Prediction Model 113
Supporting Extract Class Refactoring in Eclipse: The ARIES Project 112
Improving change prediction models with code smell-related information 111
The making of accessible Android applications: an empirical study on the state of the practice 108
Fairness-aware machine learning engineering: how far are we? 108
Transparent Machine Learning for Type 1 Diabetes Diagnosis from Gene Expression Data 107
The do's and don'ts of infrastructure code: A systematic gray literature review 107
Splicing Community Patterns and Smells: A Preliminary Study 106
When code smells meet ML: on the lifecycle of ML-specific code smells in ML-enabled systems 103
Exploring Community Smells in Open-Source: An Automated Approach 103
Extract Package Refactoring in ARIES 102
On the adoption and effects of source code reuse on defect proneness and maintenance effort 101
Comparing heuristic and machine learning approaches for metric-based code smell detection 101
Using Large Language Models to Support Software Engineering Documentation in Waterfall Life Cycles: Are We There Yet? 101
Teaching Mining Software Repositories 100
A preliminary study on the adequacy of static analysis warnings with respect to code smell prediction 99
Smells like Teen Spirit: Improving Bug Prediction Performance using the Intensity of Code Smells 97
Automatic test smell detection using information retrieval techniques 96
AI-Based Emotion Recognition to Study Users’ Perception of Dark Patterns 95
A Multivocal Literature Review of MLOps Tools and Features 95
Third-party libraries in mobile apps: When, how, and why developers update them 95
A graph-based dataset of commit history of real-world Android apps 95
The quantum frontier of software engineering: A systematic mapping study 94
On the impact of code smells on the energy consumption of mobile applications 93
Community Smell Detection and Refactoring in SLACK: The CADOCS Project 92
Just-in-time test smell detection and refactoring: The DARTS project 92
Just-in-time software vulnerability detection: Are we there yet? 92
Not All Bugs Are the Same:Understanding, Characterizing, and Classifying Bug Types 91
Collecting and Implementing Ethical Guidelines for Emotion Recognition in an Educational Metaverse 90
Refactoring android-specific energy smells: A plugin for android studio 90
Machine Learning for Educational Metaverse: How Far Are We? 89
Security Testing in The Wild: An Interview Study 88
Toward granular search-based automatic unit test case generation 87
The Yin and Yang of Software Quality: On the Relationship between Design Patterns and Code Smells 87
Evaluating the adaptive selection of classifiers for cross-project bug prediction 87
How Developers Engage with Static Analysis Tools in Different Contexts 85
Detecting code smells using machine learning techniques: Are we there yet? 84
Gender diversity and women in software teams: How do they affect community smells? 83
How the Experience of Development Teams Relates to Assertion Density of Test Classes 83
WITHIN-PROJECT DEFECT PREDICTION OF INFRASTRUCTURE-AS-CODE USING PRODUCT AND PROCESS METRICS 82
Totale 18.587
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Categoria #
all - tutte 67.379
article - articoli 0
book - libri 0
conference - conferenze 0
curatela - curatele 0
other - altro 0
patent - brevetti 0
selected - selezionate 0
volume - volumi 0
Totale 67.379
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Totale Lug Ago Sett Ott Nov Dic Gen Feb Mar Apr Mag Giu
2021/2022631 0 0 3 6 6 8 67 31 69 65 134 242
2022/2023908 93 90 30 82 106 189 15 70 122 20 58 33
2023/2024705 50 68 66 28 44 133 57 17 16 31 39 156
2024/20251.957 64 45 45 86 74 170 364 228 254 137 240 250
2025/202615.898 2.068 4.334 2.963 828 1.114 423 1.070 288 673 788 418 931
2026/2027793 336 268 189 0 0 0 0 0 0 0 0 0
Totale 22.797