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RECKA and RPromF: two Frama-C Plug-ins for Optimizing Registers usage in CUDA, OpenACC and OpenMP Programs 18

RECKA and RPromF: two Frama-C Plug-ins for Optimizing Regist...

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18th ieee International working conference on source code analysis and manipulation (SCAM)

作者： Diarra, Rokiatou Merigot, Alain Vincke, Bastien Univ Paris Saclay SATIE Univ Paris Sud F-94235 Cachan France

ISBN: (纸本)9781538682906

Pointer aliasing still hinders compiler optimizations. The ISO C standard 99 has added the restrict keyword that allows programmer to specify non-aliasing as an aid to the compiler's optimizer. The task of annotating pointers with the restrict keyword is still left to the programmer and this task is, in general, tedious and prone to errors. Scalar replacement is an optimization widely used by compilers. In this paper, we present two new Frama-C plug-ins, RECKA for automatic annotation of CUDA kernels arguments with the restrict keyword, and RPromF for scalar replacement in OpenACC and OpenMP 4.0/4.5 codes for GPU. More specifically, RECKA works as follows: (i) an alias analysis is performed on CUDA kernels and their callers;(ii) if not found any alias then CUDA kernels are cloned, the clones are renamed and their arguments are annotated with the restrict qualifier;and (iii) instructions are added to kernels call sites to perform at runtime a less-than check analysis on kernel actuals parameters and determine if the clone must be called or the original one. RPromF includes five main steps: (i) OpenACC/OpenMP offloading regions are identified;(ii) functions containing these offloading codes and their callers are analyzed to check that there is no alias;(iii) if there is no alias then the offloading codes are cloned;(iv) clone's instructions are analyzed to retrieve data reuse information and perform scalar replacement;and instructions are added to be able to use the optimized clone whenever possible. We have evaluated the two plug-ins on PolyBench benchmark suite. The results show that both scalar replacement and the usage of restrict keyword are effective for improving the overall performance of OpenACC, OpenMP 4.0/4.5 and CUDA codes.

关键词： CUDA OpenACC OpenMP scalar replacement static analysis alias analysis Frama-C

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ACUA: API Change and Usage Auditor 14

ACUA: API Change and Usage Auditor

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14th ieee International working conference on source code analysis and manipulation (SCAM)

作者： Wu, Wei Adams, Bram Gueheneuc, Yann-Gael Antoniol, Giuliano Ecole Polytech DGIGL Montreal PQ H3C 3A7 Canada

ISBN: (纸本)9780769553047

Modern software uses frameworks through their Application Programming Interfaces (APIs). Framework APIs may change while frameworks evolve. Client programs have to upgrade to new releases of frameworks if security vulnerabilities are discovered in the used releases. Patching security vulnerabilities can be delayed by non-security-related API changes when the frameworks used by client programs are not up to date. Keeping frameworks updated can reduce the reaction time to patch security leaks. Client program upgrades are not cost-free, developers need to understand the API usages in client programs and API changes between framework releases before conduct upgrading tasks. In this paper, we propose a tool ACUA to generate reports containing detailed API change and usage information by analyzing the binary code of both frameworks and clients programs written in Java. Developers can use the API change and usage reports generated by ACUA to estimate the work load and decide when to starting upgrading client programs based on the estimation.

关键词： Java application program interfaces safety-critical software source code (software) ACUA API Change-and-Usage Auditor application programming interfaces binary code analysis client program upgrade framework release nonsecurity-related API changes reaction time reduction security leakage patching security vulnerabilities software usage framework work load estimation Abstracts Analytical models Contracts Data models Detection algorithms Security Software API change and usage Software maintenance framework API evolution Application programming interfaces Java Java programming language Frameworks safety-critical software Detection algorithms Software maintenance data models API contract AXIAL POWER INDICATOR American Petroleum Institute Security hole analysis MODELS customers

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TotalADS: Automated Software Anomaly Detection System 14

TotalADS: Automated Software Anomaly Detection System

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14th ieee International working conference on source code analysis and manipulation (SCAM)

作者： Murtaza, Syed Shariyar Hamou-Lhadj, Abdelwahab Khreich, Wael Couture, Mario Concordia Univ Software Behav Anal Res Lab ECE Montreal PQ Canada Def Res & Dev Canada Syst Protect & Countermeasures Valcartier PQ Canada

ISBN: (纸本)9780769553047

When a software system starts behaving abnormally during normal operations, system administrators resort to the use of logs, execution traces, and system scanners (e.g., anti-malwares, intrusion detectors, etc.) to diagnose the cause of the anomaly. However, the unpredictable context in which the system runs and daily emergence of new software threats makes it extremely challenging to diagnose anomalies using current tools. Host-based anomaly detection techniques can facilitate the diagnosis of unknown anomalies but there is no common platform with the implementation of such techniques. In this paper, we propose an automated anomaly detection framework (TotalADS) that automatically trains different anomaly detection techniques on a normal trace stream from a software system, raise anomalous alarms on suspicious behaviour in streams of trace data, and uses visualization to facilitate the analysis of the cause of the anomalies. TotalADS is an extensible Eclipse-based open source framework that employs a common trace format to use different types of traces, a common interface to adapt to a variety of anomaly detection techniques (e.g., HMM, sequence matching, etc.). Our case study on a modern Linux server shows that TotalADS automatically detects attacks on the server, shows anomalous paths in traces, and provides forensic insights.

关键词： Anomaly Detection Trace analysis Software Security

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The Architectural Security Tool Suite - ARCHSEC 19

The Architectural Security Tool Suite - ARCHSEC

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19th ieee International working conference on source code analysis and manipulation (SCAM)

作者： Berger, Bernhard J. Sohr, Karsten Koschke, Rainer Univ Bremen Software Engn Grp Bremen Germany Technol Zentrum Informat & Informat Tech Bremen Germany

ISBN: (纸本)9781728149370

Architectural risk analysis is a risk management process for identifying security flaws at the level of software architectures and is used by large software vendors, to secure their products. We present our architectural security environment (ARCHSEC) that has been developed at our institute during the past eight years in several research projects. ARCHSEC aims to simplify architectural risk analysis, making it easier for small and mid-sized companies to get started. With ARCHSEC, it is possible to graphically model or to reverse engineer software security architectures. The regained software architectures can then be inspected manually or automatically analyzed w.r.t. security flaws, resulting in a threat model, which serves as a base for discussion between software and security experts to improve the overall security of the software system in question, beyond the level of implementation bugs. In the evaluation part of this paper, we demonstrate how we use ARCHSEC in two of our current research projects to analyze business applications. In the first project we use ARCHSEC to identify security flaws in business process diagrams. In the second project, ARCHSEC is integrated into an audit environment for software security certification. ARCHSEC is used to identify security flaws and to visualize software systems to improve the effectiveness and efficiency of the certification process.

关键词： security threat modeling software architecture reverse engineering architectural risk analysis

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On the Accuracy of Forward Dynamic Slicing and its Effects on Software Maintenance 14

On the Accuracy of Forward Dynamic Slicing and its Effects o...

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14th ieee International working conference on source code analysis and manipulation (SCAM)

作者： Jiang, Siyuan Santelices, Raul Grechanik, Mark Cai, Haipeng Univ Notre Dame Notre Dame IN 46556 USA Univ Illinois Chicago IL USA

ISBN: (纸本)9780769553047

Dynamic slicing is a practical and popular analysis technique used in various software-engineering tasks. Dynamic slicing is known to be incomplete because it analyzes only a subset of all possible executions of a program. However, it is less known that its results may inaccurately represent the dependencies that occur in those executions. Some researchers have identified this problem and developed extensions such as relevant slicing, which incorporates static information. Yet, dynamic slicing continues to be widely used, even though the extent of its inaccuracy is not well understood, which can affect the benefits of this analysis. In this paper, we present an approach to assess the accuracy of forward dynamic slices, which are used in software maintenance and evolution tasks. Because finding all actual dependencies is an undecidable problem, our approach instead computes bounds of the precision and recall of forward dynamic slices. Our approach uses sensitivity analysis and execution differencing to find a subset of all program statements that truly depend at runtime on another statement. Using this approach, we studied the accuracy of many forward dynamic slices from a variety of Java applications. Our results show that forward dynamic slicing can have low recall-for dependencies in the analyzed executions-and some potential imprecision. We also conducted a case study that shows how this inaccuracy affects a software maintenance task. To the best of our knowledge, ours is the first work that quantifies the intrinsic limitations of dynamic slicing.

关键词： dynamic slicing precision and recall sensitivity analysis execution differencing software maintenance

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Static JavaScript Call Graphs: a Comparative Study 18

Static JavaScript Call Graphs: a Comparative Study

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18th ieee International working conference on source code analysis and manipulation (SCAM)

作者： Antal, Gabor Hegedus, Peter Toth, Zoltan Ferenc, Rudolf Gyimothy, Tibor Univ Szeged Dept Software Engn Szeged Hungary MTA SZTE Res Grp Artificial Intelligence Szeged Hungary

ISBN: (纸本)9781538682906

The popularity and wide adoption of JavaScript both at the client and server side makes its code analysis more important than ever before. Most of the algorithms for vulnerability analysis, coding issue detection, or type inference rely on the call graph representation of the underlying program. Despite some obvious advantages of dynamic analysis, static algorithms should also be considered for call graph construction as they do not require extensive test beds for programs and their costly execution and tracing. In this paper, we systematically compare five widely adopted static algorithms - implemented by the npm call graph, IBM WALA, Google Closure Compiler, Approximate Call Graph, and Type Analyzer for JavaScript tools - for building JavaScript call graphs on 26 WebKit SunSpider benchmark programs and 6 real-world *** modules. We provide a performance analysis as well as a quantitative and qualitative evaluation of the results. We found that there was a relatively large intersection of the found call edges among the algorithms, which proved to be 100% precise. However, most of the tools found edges that were missed by all others. ACG had the highest precision followed immediately by TAJS, but ACG found significantly more call edges. As for the combination of tools, ACG and TAJS together covered 99% of the found true edges by all algorithms, while maintaining a precision as high as 98%. Only two of the tools were able to analyze up-to-date multi-file *** modules due to incomplete language features support. They agreed on almost 60% of the call edges, but each of them found valid edges that the other missed.

关键词： JavaScript call graph static code analysis comparative study

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A Comparative Study of Bug Patterns in Java Cloned and Non-cloned code 14

A Comparative Study of Bug Patterns in Java Cloned and Non-c...

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14th ieee International working conference on source code analysis and manipulation (SCAM)

作者： Sajnani, Hitesh Saini, Vaibhav Lopes, Cristina V. Univ Calif Irvine Bren Sch Informat & Comp Sci Irvine CA 92697 USA

ISBN: (纸本)9780769553047

code cloning via copy-and-paste is a common practice in software engineering. Traditionally, this practice has been considered harmful, and a symptom that some important design abstraction is being ignored. As such, many previous studies suggest approaches to facilitate the discovery, removal, and refactoring of clones. However, not many studies exist that empirically investigate the relationship of code clones with code quality. In this paper, we conduct an empirical study of 31 open source Java projects (1.7 MSLOC) to explore the relationship between code clones and a set of bug patterns reported by FindBugs. We found that: (i) the defect density in cloned code is 3.7 times less than that of the rest of the code;(ii) 66% of the bug patterns associated with code clones are related to issues in coding style and practice, the two least problematic of the FindBugs categories, while that number is 49% for non-cloned code;and (iii) 75% of the bug patterns in cloned code are duplicated without any changes, while 25% are only present in one of the clones. These results show that, when using FindBugs to detect bug patterns, there is a positive differentiation of cloned code with respect to the rest of the code: the cloned code has considerably less, and less problematic, bug patterns. While our study does not unveil any explanation for this, results from other, more qualitative studies indicate that developers use copy-and-paste intentionally and wisely, which may explain the quantitative observations of our study. Overall, these research results suggest that the practice of code cloning in Java, and possibly in all other object-oriented languages, needs to be given serious consideration on the part of tool designers.

关键词： Java program debugging public domain software software quality source code (software) Java cloned code Java noncloned code bug pattern detection code quality copy-and-paste defect density design abstraction find bugs category object-oriented languages open source Java projects software engineering Cloning Computer bugs Correlation Encoding Google Software bug patterns code clones Java Java programming language bugs codes Object oriented programming languages open source software Debugging Software engineering software quality Bugs Cloning computer software

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BoostNSift: A Query Boosting and code Sifting Technique for Method Level Bug Localization 21

BoostNSift: A Query Boosting and Code Sifting Technique for ...

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21st ieee International working conference on source code analysis and manipulation (SCAM)

作者： Razzaq, Abdul Buckley, Jim Patten, James Vincent Chochlov, Muslim Sai, Ashish Rajendra Univ Limerick Limerick Ireland

ISBN: (纸本)9781665448970

Locating bugs is an important, but effort-intensive and time-consuming task, when dealing with large-scale systems. To address this, Information Retrieval (IR) techniques are increasingly being used to suggest potential buggy source code locations, for given bug reports. While IR techniques are very scalable, in practice their effectiveness in accurately localizing bugs in a software system remains low. Results of empirical studies suggest that the effectiveness of bug localization techniques can be augmented by the configuration of queries used to locate buggy code. However, in most IR-based bug localization techniques, presented by researchers, the impact of the queries' configurations is not fully considered. In a similar vein, techniques consider all code elements as equally suspicious of being buggy while localizing bugs, but this is not always the case either. In this paper, we present a new method-level, information-retrieval-based bug localization technique called "BoostNSift". BoostNSift exploits the important information in queries by 'boost'ing that information, and then 'sift's the identified code elements, based on a novel technique that emphasizes the code elements' specific relatedness to a bug report over its generic relatedness to all bug reports. To evaluate the performance of BoostNSift, we employed a state-of-the-art empirical design that has been commonly used for evaluating file level IR-based bug localization techniques: 6851 bugs are selected from commonly used Eclipse, AspectJ, SWT, and ZXing benchmarks and made openly available for method-level analyses. The performance of BoostNSift is compared with the openly-available state-of-the-art IR-based BugLocator, BLUiR, and BLIA techniques. Experiments show that BoostNSift improves on BLUiR by up to 324%, on BugLocator by up to 297%, and on BLIA up to 120%, in terms of Mean Reciprocal Rank (MRR). Similar improvements are observed in terms of Mean Average Precision (MAP) and Top-N evaluation meas

关键词： Bug localization code analysis Software maintenance Query enhancement Query boosting code Sifting

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Failure of One, Fall of Many: An Exploratory Study of Software Features for Defect Prediction 20

Failure of One, Fall of Many: An Exploratory Study of Softwa...

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20th ieee International working conference on source code analysis and manipulation (SCAM)

作者： dos Santos, Geanderson Esteves Figueiredo, Eduardo Fed Univ Minas Gerais UFMG Dept Comp Sci DCC Belo Horizonte MG Brazil

ISBN: (纸本)9781728192482

Software defect prediction represents an area of interest in both academia and the software industry. Thus, software defects are prevalent in software development and might generate numerous difficulties for users and developers apart. The current literature offers multiple alternative approaches to predict the likelihood of defects in the source code. Most of these studies concentrate on predicting defects from a broad set of software features. As a result, the individual discriminating power of software features is still unknown as some perform well only with specific projects or metrics. In this study, we applied machine learning techniques in a popular dataset. This data has information about software defects in five Java projects, containing 5,371 classes and 37 software features. To this aim, we convey an exploratory investigation that produced hundreds of thousands of machine learning models from a diverse collection of software features. These models are random in the sense that they promptly select the features from the entire pool of features. Even though the immense majority of models are ineffective, we could produce several models that yield accurate predictions, thus classifying defects from Java project classes. Among these accurate models, our results indicate that change metric features are more present than entropy or class-level metrics. We concentrated our analysis on models that rank a randomly chosen defective class higher than a casually selected clean class with over 80% accuracy. We also report and discuss some features contributing to the explanation of model decisions. Therefore, our study promotes reasoning on which features support predicting defects in these projects. Finally, we present the implications of our work to practitioners.

关键词： defect prediction explainability source code metrics

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The Evolution and Decay of Statically Detected source code Vulnerabilities

The Evolution and Decay of Statically Detected Source Code V...

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8th ieee International working conference on source code analysis and manipulation

作者： Di Penta, Massimiliano Cerulo, Luigi Aversano, Lerina Univ Sannio RCOST Dept Engn I-82100 Benevento Italy

ISBN: (纸本)9780769533537

The presence of vulnerable statements in the source code is a crucial problem for maintainers: properly monitoring and, if necessary, removing them is highly desirable to ensure high security and reliability To this aim, a number of static analysis tools have been developed to detect the presence of instructions that can be subject to vulnerability attacks, ranging from buffer overflow exploitations to command injection and cross-site scripting. Based on the availability of existing tools and of data extracted from software repositories, this paper reports an empirical study on the evolution of vulnerable statements detected in three software systems with different static analysis tools. Specifically, the study investigates on vulnerability evolution trends and on the decay time exhibited by different kinds of vulnerabilities.

关键词： software vulnerabilities mining software repositories empirical study

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