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Are automatically-detected code anomalies relevant to architectural modularity?

Isela Macia, Joshua Garcia, Daniel Popescu, Alessandro Garcia, Nenad Medvidovic, Arndt von Staa
2012 Proceedings of the 11th annual international conference on Aspect-oriented Software Development - AOSD '12  
The outcome of our evaluation suggests that many of the code anomalies detected by the employed strategies were not related to architectural problems.  ...  A number of strategies have been developed for supporting the automatic identification of implementation anomalies when only the source code is available.  ...  Studies have also evaluated the impact of the code anomalies detected by these strategies on maintenance effort [18, 37, 38] .  ... 
doi:10.1145/2162049.2162069 dblp:conf/aosd/BertranGPGMS12 fatcat:o5gamvlnondvrgaot6pmktmqoe

Supporting the identification of architecturally-relevant code anomalies

Isela Macia, Roberta Arcoverde, Elder Cirilo, Alessandro Garcia, Arndt von Staa
2012 2012 28th IEEE International Conference on Software Maintenance (ICSM)  
anomalies to detect the architecturally-relevant ones.  ...  To overcome these shortcomings we propose SCOOP, a tool that includes: (i) architecture-code traces in the analysis of the source code, and (ii) exploits relationships between multiple occurrences of code  ...  By identifying architecturally-relevant code anomalies, developers can invest their refactoring efforts into solving anomalies that could possibly cause architecture problems, improving refactoring effectiveness  ... 
doi:10.1109/icsm.2012.6405348 dblp:conf/icsm/BertranACGS12 fatcat:xa37mj2kdrhnbpzsytoug4sr4q

Visual Detection of Design Anomalies

Karim Dhambri, Houari Sahraoui, Pierre Poulin
2008 Software Maintenance and Reengineering (CSMR), Proceedings of the European Conference on  
We propose a visualization-based approach to detect design anomalies for cases where the detection effort already includes the validation of candidates.  ...  We introduce a general detection strategy that we apply to three types of design anomaly. These strategies are illustrated on concrete examples. Finally we evaluate our approach through a case study.  ...  Case Study To evaluate our approach, we conducted a case study.  ... 
doi:10.1109/csmr.2008.4493326 dblp:conf/csmr/DhambriSP08 fatcat:4kj6sesgcfgmjc6abjfrdixoza

Anomaly-based bug prediction, isolation, and validation

Martin Dimitrov, Huiyang Zhou
2009 Proceeding of the 14th international conference on Architectural support for programming languages and operating systems - ASPLOS '09  
Our experiments with 6 programs and 7 bugs, including a real bug in the gcc 2.95.2 compiler, show that our approach is highly effective at isolating only the relevant anomalies.  ...  Compared to state-of-art debugging techniques, our proposed approach pinpoints the defect locations more accurately and presents the user with a much smaller code set to analyze.  ...  Acknowledgements We thank Luis Ceze and the anonymous reviewers for helping us improve this paper. This research is supported by an NSF CAREER award CCF-0747062.  ... 
doi:10.1145/1508244.1508252 dblp:conf/asplos/DimitrovZ09 fatcat:maqvxh4ll5gjje3gye5qyarqvy

Anomaly-based bug prediction, isolation, and validation

Martin Dimitrov, Huiyang Zhou
2009 SIGARCH Computer Architecture News  
Our experiments with 6 programs and 7 bugs, including a real bug in the gcc 2.95.2 compiler, show that our approach is highly effective at isolating only the relevant anomalies.  ...  Compared to state-of-art debugging techniques, our proposed approach pinpoints the defect locations more accurately and presents the user with a much smaller code set to analyze.  ...  Acknowledgements We thank Luis Ceze and the anonymous reviewers for helping us improve this paper. This research is supported by an NSF CAREER award CCF-0747062.  ... 
doi:10.1145/2528521.1508252 fatcat:5at5zzgpovazpa4roug4imuaai

On the Relevance of Code Anomalies for Identifying Architecture Degradation Symptoms

Isela Macia, Roberta Arcoverde, Alessandro Garcia, Christina Chavez, Arndt von Staa
2012 2012 16th European Conference on Software Maintenance and Reengineering  
A total of 40 versions and 2056 code anomalies were analyzed. Our study revealed that 78% of all architecture problems in the programs were related to code anomalies.  ...  This paper presents an empirical study about the influence of code anomalies on architecture degradation symptoms.  ...  This is the case of code anomalies such as Long Parameter List and Small Class, which presented interesting and distinct effects.  ... 
doi:10.1109/csmr.2012.35 dblp:conf/csmr/BertranAGCS12 fatcat:axtugukfqvcv3gibgo5v47kjle

Anomaly-based bug prediction, isolation, and validation

Martin Dimitrov, Huiyang Zhou
2009 SIGPLAN notices  
Our experiments with 6 programs and 7 bugs, including a real bug in the gcc 2.95.2 compiler, show that our approach is highly effective at isolating only the relevant anomalies.  ...  Compared to state-of-art debugging techniques, our proposed approach pinpoints the defect locations more accurately and presents the user with a much smaller code set to analyze.  ...  Acknowledgements We thank Luis Ceze and the anonymous reviewers for helping us improve this paper. This research is supported by an NSF CAREER award CCF-0747062.  ... 
doi:10.1145/1508284.1508252 fatcat:czxnydydgjd5jieg6qrriljtpu

On the relationship of code-anomaly agglomerations and architectural problems

Willian N. Oizumi, Alessandro F. Garcia, Thelma E. Colanzi, Manuele Ferreira, Arndt V. Staa
2015 Journal of Software Engineering Research and Development  
In our empirical study, we analyzed a total of 5418 code anomalies and 2229 agglomerations within 7 systems.  ...  To overcome this limitation, we are studying the architecture impact of a wide range of code-anomaly agglomerations.  ...  The study by Abbes et al. (2011) brings up the notion of interaction effects across code anomalies.  ... 
doi:10.1186/s40411-015-0025-y fatcat:7ki7g5esbrhlti7ss6deqx4kmi

Unsupervised Anomaly-based Malware Detection using Hardware Features [article]

Adrian Tang, Simha Sethumadhavan, Salvatore Stolfo
2014 arXiv   pre-print
In this work, we propose a new class of detectors - anomaly-based hardware malware detectors - that do not require signatures for malware detection, and thus can catch a wider range of malware including  ...  We also examine the limits and challenges in implementing this approach in face of a sophisticated adversary attempting to evade anomaly-based detection.  ...  Defenses Unlike past anomaly-based detection systems that detect deviations based on the syntactic/semantic structure and code behavior of the malware shellcode, our approach focuses on the architectural  ... 
arXiv:1403.1631v2 fatcat:ozxpdxdjmfbojgjfzczboxfdj4

Monitoring Smartphones for Anomaly Detection

Aubrey-Derrick Schmidt, Frank Peters, Florian Lamour, Sahin Albayrak
2008 Proceedings of the 1st International ICST Conference on Mobile Wireless Middleware, Operating Systems and Applications  
We give examples on how to compute relevant features and introduce the top ten applications used by mobile phone users based on a study in 2005.  ...  In this paper we demonstrate how to monitor a smartphone running Symbian operating system and Windows Mobile in order to extract features for anomaly detection.  ...  In order to be able to learn normality on smartphones, we map actions excerpted from a study on mobile phone usage to different use cases and specify testing scenarios on these.  ... 
doi:10.4108/icst.mobilware2008.2492 dblp:conf/mobilware/SchmidtPLA08 fatcat:mavmbq3lcffbvoaoc77wpuz6ea

Unsupervised Anomaly-Based Malware Detection Using Hardware Features [chapter]

Adrian Tang, Simha Sethumadhavan, Salvatore J. Stolfo
2014 Lecture Notes in Computer Science  
We also examine the limits and challenges in implementing this approach in face of a sophisticated adversary attempting to evade anomaly-based detection.  ...  This allows us to detect a wider range of malware, even zero days.  ...  Opinions, findings, conclusions and recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the US Government or commercial entities.  ... 
doi:10.1007/978-3-319-11379-1_6 fatcat:67z7oo2r5rge7b63tvkmdfmnym

Identifying the provenance of correlated anomalies

Dawood Tariq, Basim Baig, Ashish Gehani, Salman Mahmood, Rashid Tahir, Azeem Aqil, Fareed Zaffar
2011 Proceedings of the 2011 ACM Symposium on Applied Computing - SAC '11  
Identifying when anomalous activity is correlated in a distributed system is useful for a range of applications from intrusion detection to tracking quality of service.  ...  We present an architecture that allows fine-grained auditing on individual hosts, space-efficient representation of anomalous activity that can be centrally correlated, and tracing anomalies back to individual  ...  We therefore studied the effect of increasing the workload duration, as shown in Figure 5 .  ... 
doi:10.1145/1982185.1982236 dblp:conf/sac/TariqBGMTAZ11 fatcat:dpxemmw7efgrzjighu5ofubnki

Anomaly Detection in a Large-scale Cloud Platform [article]

Mohammad Saiful Islam, William Pourmajidi, Lei Zhang, John Steinbacher, Tony Erwin, Andriy Miranskyy
2021 arXiv   pre-print
After running the system for a year, we observed that the proposed solution frees the DevOps team's time and human resources from manually monitoring thousands of Cloud components.  ...  This monitoring system utilizes deep learning neural networks to detect anomalies in near-real-time in multiple Platform components simultaneously.  ...  In that case, on those time intervals on which these data records come on, we re-run the anomaly detection.  ... 
arXiv:2010.10966v2 fatcat:l6moyl3z3jfhfgr7wmrs4sckhq

Big Data Platform for Smart Grids Power Consumption Anomaly Detection

Peter Lipcàk, Martin Macak, Bruno Rossi
2019 Proceedings of the 2019 Federated Conference on Computer Science and Information Systems  
., intrusion and data injection attacks detection, electric device health monitoring). In this paper, we present a big data platform for anomaly detection of power consumption data.  ...  We showcase the application of the platform to a scenario of power consumption anomaly detection, benchmarking different alternative frameworks used at the speed layer level (Flink, Storm, Spark).  ...  There are a plethora of use cases for the application of big data analysis in the context of SGs [5] , [6] , like anomaly detection methods to detect power consumption anomalous behaviours [7] , [8  ... 
doi:10.15439/2019f210 dblp:conf/fedcsis/LipcakM019 fatcat:2624hhnbfrcy3dhuldl3rjptcu

Detection of Anomalies in Large Scale Accounting Data using Deep Autoencoder Networks [article]

Marco Schreyer, Timur Sattarov, Damian Borth, Andreas Dengel, Bernd Reimer
2018 arXiv   pre-print
Experiments on two real-world datasets of journal entries, show the effectiveness of the approach resulting in high f1-scores of 32.93 (dataset A) and 16.95 (dataset B) and less false positive alerts compared  ...  Initial feedback received by chartered accountants and fraud examiners underpinned the quality of the approach in capturing highly relevant accounting anomalies.  ...  We thank Adrian Ulges, all members of the Deep Learning Competence Center at the DFKI, as well as, the PwC Europe's Forensic Services team for their comments and support.  ... 
arXiv:1709.05254v2 fatcat:xsfugembm5au5dxnyz3wcklioy
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