KClone: A Proposed Approach to Fast Precise Code Clone Detection

In all applications of clone detection it is important to have precise and efficient clone identification algorithms. This paper proposes and outlines a new algorithm, KClone for clone detection that incorporates a novel combination of lexical and local dependence analysis to achieve precision, while retaining speed. The paper also reports on the initial results of a case study using an implementation of KClone with which we have been experimenting. The results indi- cate the ability of KClone to find types-1,2, and 3 clones compared to token-based and PDG-based techniques. The paper also reports results of an initial empirical study of the performance of KClone compared to CCFinderX.

Scaleable Code Clone Detection

Code clone detection helps connect developers across projects, if we do it on a large scale. The cornerstones that allow clone detection to work on a large scale are: (1) bad hashing (2) lightweight parsing using regular expressions and (3) MapReduce pipelines. Bad hashing means to determine whether or not two artifacts are similar by checking whether their hashes are identical. We show a bad hashing scheme that works well on source code. Lightweight parsing using regular expressions is our technique of obtaining entire parse trees from regular expressions, robustly and efficiently. We detail the algorithm and implementation of one such regular expression engine. MapReduce pipelines are a way of expressing a computation such that it can automatically and simply be parallelized. We detail the design and implementation of one such MapReduce pipeline that is efficient and debuggable. We show a clone detector that combines these cornerstones to detect code clones across all projects, across all versions of each project.

On Occurrence Of Plagiarism In Published Computer Science Thesis Reports At Swedish Universities

In recent years, it has been observed that software clones and plagiarism are becoming an increased threat for one?s creativity. Clones are the results of copying and using other?s work. According to the Merriam – Webster dictionary, “A clone is one that appears to be a copy of an original form”. It is synonym to duplicate. Clones lead to redundancy of codes, but not all redundant code is a clone.On basis of this background knowledge ,in order to safeguard one?s idea and to avoid intentional code duplication for pretending other?s work as if their owns, software clone detection should be emphasized more. The objective of this paper is to review the methods for clone detection and to apply those methods for finding the extent of plagiarism occurrence among the Swedish Universities in Master level computer science department and to analyze the results.The rest part of the paper, discuss about software plagiarism detection which employs data analysis technique and then statistical analysis of the results.Plagiarism is an act of stealing and passing off the idea?s and words of another person?s as one?s own. Using data analysis technique, samples(Master level computer Science thesis report) were taken from various Swedish universities and processed in Ephorus anti plagiarism software detection. Ephorus gives the percentage of plagiarism for each thesis document, from this results statistical analysis were carried out using Minitab Software.The results gives a very low percentage of Plagiarism extent among the Swedish universities, which concludes that Plagiarism is not a threat to Sweden?s standard of education in computer science.This paper is based on data analysis, intelligence techniques, EPHORUS software plagiarism detection tool and MINITAB statistical software analysis.

Integration of Bridge Damage Detection Concepts and Components (3 volumes), TR-636, 2013

This work is divided into three volumes: Volume I: Strain-Based Damage Detection; Volume II: Acceleration-Based Damage Detection; Volume III: Wireless Bridge Monitoring Hardware. Volume I: In this work, a previously-developed structural health monitoring (SHM) system was advanced toward a ready-for-implementation system. Improvements were made with respect to automated data reduction/analysis, data acquisition hardware, sensor types, and communication network architecture. The statistical damage-detection tool, control-chart-based damage-detection methodologies, were further investigated and advanced. For the validation of the damage-detection approaches, strain data were obtained from a sacrificial specimen attached to the previously-utilized US 30 Bridge over the South Skunk River (in Ames, Iowa), which had simulated damage,. To provide for an enhanced ability to detect changes in the behavior of the structural system, various control chart rules were evaluated. False indications and true indications were studied to compare the damage detection ability in regard to each methodology and each control chart rule. An autonomous software program called Bridge Engineering Center Assessment Software (BECAS) was developed to control all aspects of the damage detection processes. BECAS requires no user intervention after initial configuration and training. Volume II: In this work, a previously developed structural health monitoring (SHM) system was advanced toward a ready-for-implementation system. Improvements were made with respect to automated data reduction/analysis, data acquisition hardware, sensor types, and communication network architecture. The objective of this part of the project was to validate/integrate a vibration-based damage-detection algorithm with the strain-based methodology formulated by the Iowa State University Bridge Engineering Center. This report volume (Volume II) presents the use of vibration-based damage-detection approaches as local methods to quantify damage at critical areas in structures. Acceleration data were collected and analyzed to evaluate the relationships between sensors and with changes in environmental conditions. A sacrificial specimen was investigated to verify the damage-detection capabilities and this volume presents a transmissibility concept and damage-detection algorithm that show potential to sense local changes in the dynamic stiffness between points across a joint of a real structure. The validation and integration of the vibration-based and strain-based damage-detection methodologies will add significant value to Iowa’s current and future bridge maintenance, planning, and management Volume III: In this work, a previously developed structural health monitoring (SHM) system was advanced toward a ready-for-implementation system. Improvements were made with respect to automated data reduction/analysis, data acquisition hardware, sensor types, and communication network architecture. This report volume (Volume III) summarizes the energy harvesting techniques and prototype development for a bridge monitoring system that uses wireless sensors. The wireless sensor nodes are used to collect strain measurements at critical locations on a bridge. The bridge monitoring hardware system consists of a base station and multiple self-powered wireless sensor nodes. The base station is responsible for the synchronization of data sampling on all nodes and data aggregation. Each wireless sensor node include a sensing element, a processing and wireless communication module, and an energy harvesting module. The hardware prototype for a wireless bridge monitoring system was developed and tested on the US 30 Bridge over the South Skunk River in Ames, Iowa. The functions and performance of the developed system, including strain data, energy harvesting capacity, and wireless transmission quality, were studied and are covered in this volume.

Indoor radon measurements and methodologies in Latin American countries

According to the current international guidelines concerning environmental problems, it is necessary to evaluate and to know the indoor radon levels, specially since most of the natural radiation dose to man comes from radon gas and its progeny. Several countries have established National Institutions and National Programs for the study of radon and its connection with lung cancer risk and public health. The aim of this work is to present the indoor radon measurements and the detection methods used for different regions of Latin America (LA) in countries such as Argentina, Brazil, Ecuador, Mexico, Peru and Venezuela. This study shows that the passive radon devices based on alpha particle nuclear track methodology (NTM) is one of the more generalized methods in LA for long term indoor radon measurements, CR-39, LR-115 and Makrofol being the more commonly used detector materials. The participating institutions and the radon level measurements in the different countries are presented in this contribution. (C) 2001 Elsevier B.V. Ltd. All rights reserved.

Semi-selective culture medium for Xanthomonas axonopodis pv. malvacearum detection in cotton seeds (Gossypium hirsutum L.)

The cotton disease known as angular leaf spot, caused by Xanthomonas axonopodis pv. malvacearum (Xam) has been causing cotton losses in several producing regions around the world. Xam is transmitted by seeds, which may be infected both externally and internally. Infected seeds constitute the main long-distance dissemination mode of the pathogen. In view of this, the use of healthy seeds is a must. To accomplish that, detection methodologies for the bacteria must be developed be used in seed health analysis laboratories. This study aimed to develop a semi-selective medium for Xam detection in cotton seeds. The semi-selective culture medium was named MSSXAN and it was consisted of peptone (5.0 g), beef extract (3 g), sucrose (5 g), soluble starch (10 g), agar (15 g), CaCl 2 (0.25 g), Tween 80 (10 mL), distilled water (1,000 mL), crystal violet solution at 1% (150 μL), cephalexin (50 mg 1*), methyl thyophanate (10 mg*) and chlorothalonil (10 mg*) - *added after culture medium autoclaving. This MSSXAN medium shows low repressiveness to Xam and it be used for isolation of this bacteria in cotton seeds health analysis. © 2009 Academic Journals Inc.

Hazelnut Allergens: Molecular Characterisation, Detection and Clinical Relevance

In the last years, special attention has been devoted to food-induced allergies, from which hazelnut allergy is highlighted. Hazelnut is one of the most commonly consumed tree nuts, being largely used by the food industry in a wide variety of processed foods. It has been regarded as a food with potential health benefits, but also as a source of allergens capable of inducing mild to severe allergic reactions in sensitised individuals. Considering the great number of reports addressing hazelnut allergens, with an estimated increasing trend, this review intends to assemble all the relevant information available so far on the main issues: prevalence of tree nut allergy, clinical threshold levels, molecular characterisation of hazelnut allergens (Cor a 1, Cor a 2, Cor a 8, Cor a 9, Cor a 10, Cor a 11, Cor a 12, Cor a 14 and Cor a TLP) and their clinical relevance, and methodologies for hazelnut allergen detection in foods. A comprehensive overview on the current data about the molecular characterisation of hazelnut allergens is presented, relating biochemical classification and biological function with clinical importance. Recent advances on hazelnut allergen detection methodologies are summarised and compared, including all the novel protein- and DNA-based approaches.

Identifying clones in functional programs for refactoring

Clone detection is well established for imperative programs. It works mostly on the statement level and therefore is ill-suited for func- tional programs, whose main constituents are expressions and types. In this paper we introduce clone detection for functional programs using a new intermediate program representation, dubbed Functional Control Tree. We extend clone detection to the identi cation of non-trivial func- tional program clones based on the recursion patterns from the so-called Bird-Meertens formalism

Bananas, Dark Worlds, and AspectH: (Group 5 Discussion)

This report summarises our idea of code clone detection in Haskell code and refactorings based on identified clones as it evolved in our group-of-three discussion

Vibration analysis for Bearing outer race condition diagnostics

This paper investigates defect detection methodologies for rolling element bearings through vibration analysis. Specifically, the utility of a new signal processing scheme combining the High Frequency Resonance Technique (HFRT) and Adaptive Line Enhancer (ALE) is investigated. The accelerometer is used to acquire data for this analysis, and experimental results have been obtained for outer race defects. Results show the potential effectiveness of the signal processing technique to determine both the severity and location of a defect. The HFRT utilizes the fact that much of the energy resulting from a defect impact manifests itself in the higher resonant frequencies of a system. Demodulation of these frequency bands through use of the envelope technique is then employed to gain further insight into the nature of the defect while further increasing the signal to noise ratio. If periodic, the defect frequency is then present in the spectra of the enveloped signal. The ALE is used to enhance the envelope spectrum by reducing the broadband noise. It provides an enhanced envelope spectrum with clear peaks at the harmonics of a characteristic defect frequency. It is implemented by using a delayed version of the signal and the signal itself to decorrelate the wideband noise. This noise is then rejected by the adaptive filter that is based upon the periodic information in the signal. Results have been obtained for outer race defects. They show the effectiveness of the methodology to determine both the severity and location of a defect. In two instances, a linear relationship between signal characteristics and defect size is indicated.

Code clones in program test sequence identification

Code clones are portions of source code which are similar to the original program code. The presence of code clones is considered as a bad feature of software as the maintenance of software becomes difficult due to the presence of code clones. Methods for code clone detection have gained immense significance in the last few years as they play a significant role in engineering applications such as analysis of program code, program understanding, plagiarism detection, error detection, code compaction and many more similar tasks. Despite of all these facts, several features of code clones if properly utilized can make software development process easier. In this work, we have pointed out such a feature of code clones which highlight the relevance of code clones in test sequence identification. Here program slicing is used in code clone detection. In addition, a classification of code clones is presented and the benefit of using program slicing in code clone detection is also mentioned in this work.

Extensive clonal spread and extreme longevity in saw palmetto, a foundation clonal plant

The lack of effective tools have hampered our ability to assess the size, growth and ages of clonal plants. With Serenoa repens (saw palmetto) as a model, we introduce a novel analytical framework that integrates DNA fingerprinting and mathematical modelling to simulate growth and estimate ages of clonal plants. We also demonstrate the application of such life-history information of clonal plants to provide insight into management plans. Serenoa is an ecologically important foundation species in many Southeastern United States ecosystems; yet, many land managers consider Serenoa a troublesome invasive plant. Accordingly, management plans have been developed to reduce or eliminate Serenoa with little understanding of its life history. Using Amplified Fragment Length Polymorphisms, we genotyped 263 Serenoa and 134 Sabal etonia (a sympatric non-clonal palmetto) samples collected from a 20 X 20 m study plot in Florida scrub. Sabal samples were used to assign small field-unidentifiable palmettos to Serenoa or Sabal and also as a negative control for clone detection. We then mathematically modelled clonal networks to estimate genet ages. Our results suggest that Serenoa predominantly propagate via vegetative sprouts and 10000-year-old genets may be common, while showing no evidence of clone formation by Sabal. The results of this and our previous studies suggest that: (i) Serenoa has been part of scrub associations for thousands of years, (ii) Serenoa invasion are unlikely and (ii) once Serenoa is eliminated from local communities, its restoration will be difficult. Reevaluation of the current management tools and plans is an urgent task.

Extensive clonal spread and extreme longevity in saw palmetto, a foundation clonal plant

The lack of effective tools has hampered our ability to assess the size, growth and ages of clonal plants. With Serenoa repens (saw palmetto) as a model, we introduce a novel analytical frame work that integrates DNA fingerprinting and mathematical modelling to simulate growth and estimate ages of clonal plants. We also demonstrate the application of such life-history information of clonal plants to provide insight into management plans. Serenoa is an ecologically important foundation species in many Southeastern United States ecosystems; yet, many land managers consider Serenoa a troublesome invasive plant. Accordingly, management plans have been developed to reduce or eliminate Serenoa with little understanding of its life history. Using Amplified Fragment Length Polymorphisms, we genotyped 263 Serenoa and 134 Sabal etonia (a sympatric non-clonal palmetto) samples collected from a 20 x 20 m study plot in Florida scrub. Sabal samples were used to assign small field-unidentifiable palmettos to Serenoa or Sabal and also as a negative control for clone detection. We then mathematically modelled clonal networks to estimate genet ages. Our results suggest that Serenoa predominantly propagate via vegetative sprouts and 10000-year-old genets maybe common, while showing no evidence of clone formation by Sabal. The results of this and our previous studies suggest that: (i) Serenoa has been part of scrub associations for thousands of years, (ii) Serenoa invasions are unlikely and (ii) once Serenoa is eliminated from local communities, its restoration will be difficult. Reevaluation of the current management tools and plans is an urgent task.

Characterization of fecal contamination targeting 16S rRNA bacteroides molecular markers in the Santa Cruz River, Arizona

Understanding the origins, transport and fate of contamination is essential to effective management of water resources and public health. Individuals and organizations with management responsibilities need to understand the risks to ecosystems and to humans from contact with contamination. Managers also need to understand how key contaminants vary over time and space in order to design and prioritize mitigation strategies. Tumacacori National Historic Park (NHP) is responsible for management of its water resources for the benefit of the park and for the health of its visitors. The existence of microbial contaminants in the park poses risks that must be considered in park planning and operations. The water quality laboratory at the Maricopa Agricultural Center (in collaboration with stakeholder groups and individuals located in the ADEQ-targeted watersheds) identified biological changes in surface water quality in impaired reaches rivers to determine the sources of Escherichia coli (E. coli); bacteria utilizing innovative water quality microbial/bacterial source tracking methods. The end goal was to support targeted watershed groups and ADEQ towards E. coli reductions. In the field monitoring was conducted by the selected targeted watershed groups in conjunction with The University of Arizona Maricopa Agricultural Center Water Quality Laboratory. This consisted of collecting samples for Bacteroides testing from multiple locations on select impaired reaches, to determine contamination resulting from cattle, human recreation, and other contributions. Such testing was performed in conjunction with high flow and base flow conditions in order to accurately portray water quality conditions and variations. Microbial monitoring was conducted by The University of Arizona Water Quality Laboratory at the Maricopa Agricultural Center using genetic typing to differentiate among two categories of Bacteroides: human and all (total). Testing used microbial detection methodologies and molecular source tracking techniques.^