Control flow graphs and code coverage

Control flow graphs and code coverageThe control flow of programs can be represented by directed graphs. In this paper we provide a uniform and detailed formal basis for control flow graphs combining known definitions and results with new aspects. Two graph reductions are defined using only syntactical information about the graphs, but no semantical information about the represented programs. We prove some properties of reduced graphs and also about the paths in reduced graphs. Based on graphs, we define statement coverage and branch coverage such that coverage notions correspond to node coverage, and edge coverage, respectively.

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CREATING AND MANIPULATING CONTROL FLOW GRAPHS WITH MULTILEVEL GROUPING AND CODE COVERAGE

Proceedings of the Eighth International Conference on Enterprise Information Systems ◽

10.5220/0002448802590262 ◽

2006 ◽

Keyword(s):

Control Flow ◽

Code Coverage ◽

Flow Graphs

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Neural reverse engineering of stripped binaries using augmented control flow graphs

Proceedings of the ACM on Programming Languages ◽

10.1145/3428293 ◽

2020 ◽

Vol 4 (OOPSLA) ◽

pp. 1-28 ◽

Cited By ~ 1

Author(s):

Yaniv David ◽

Uri Alon ◽

Eran Yahav

Keyword(s):

Reverse Engineering ◽

Control Flow ◽

Flow Graphs

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Selection of Best Test Cases using Support Vector Machine for ARPT

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.c5166.098319 ◽

2019 ◽

Vol 8 (3) ◽

pp. 4265-4271

Keyword(s):

Support Vector Machine ◽

Software Testing ◽

Support Vector ◽

Test Cases ◽

Testing Strategy ◽

Random Partition ◽

Code Coverage ◽

Time Consumption ◽

Branch Coverage ◽

Selection Of

Software testing is an essential activity in software industries for quality assurance; subsequently, it can be effectively removing defects before software deployment. Mostly good software testing strategy is to accomplish the fundamental testing objective while solving the trade-offs between effectiveness and efficiency testing issues. Adaptive and Random Partition software Testing (ARPT) approach was a combination of Adaptive Testing (AT) and Random Partition Approach (RPT) used to test software effectively. It has two variants they are ARPT-1 and ARPT-2. In ARPT-1, AT was used to select a certain number of test cases and then RPT was used to select a number of test cases before returning to AT. In ARPT-2, AT was used to select the first m test cases and then switch to RPT for the remaining tests. The computational complexity for random partitioning in ARPT was solved by cluster the test cases using a different clustering algorithm. The parameters of ARPT-1 and ARPT-2 needs to be estimated for different software, it leads to high computation overhead and time consumption. It was solved by Improvised BAT optimization algorithms and this approach is named as Optimized ARPT1 (OARPT1) and OARPT2. By using all test cases in OARPT will leads to high time consumption and computational overhead. In order to avoid this problem, OARPT1 with Support Vector Machine (OARPT1-SVM) and OARPT2- SVM are introduced in this paper. The SVM is used for selection of best test cases for OARPT-1 and OARPT-2 testing strategy. The SVM constructs hyper plane in a multi-dimensional space which is used to separate test cases which have high code and branch coverage and test cases which have low code and branch coverage. Thus, the SVM selects the best test cases for OARPT-1 and OARPT-2. The selected test cases are used in OARPT-1 and OARPT-2 to test software. In the experiment, three different software is used to prove the effectiveness of proposed OARPT1- SVM and OARPT2-SVM testing strategies in terms of time consumption, defect detection efficiency, branch coverage and code coverage.

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Generating Functionally Equivalent Programs Having Non-isomorphic Control-Flow Graphs

Secure IT Systems - Lecture Notes in Computer Science ◽

10.1007/978-3-319-70290-2_16 ◽

2017 ◽

pp. 265-279 ◽

Cited By ~ 1

Author(s):

Rémi Géraud ◽

Mirko Koscina ◽

Paul Lenczner ◽

David Naccache ◽

David Saulpic

Keyword(s):

Control Flow ◽

Flow Graphs

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A Unified Software Reengineering Approach towards Model Driven Architecture Environment

Software Evolution with UML and XML ◽

10.4018/978-1-59140-462-0.ch003 ◽

2011 ◽

pp. 55-100

Author(s):

Bing Qiao ◽

Hongji Yang ◽

Alan O’Callaghan

Keyword(s):

Control Flow ◽

Point Of View ◽

Software System ◽

Model Driven Architecture ◽

Unified Framework ◽

Software Reengineering ◽

Model Driven ◽

Incremental Development ◽

Flow Graphs ◽

And Control

When developing a software system, there are a number of principles, paradigms, and tools available to choose from. For a specific platform or programming language, a standard way can usually be found to archive the ultimate system; for example, a combination of an incremental development process, object-oriented analysis and design, and a well supported CASE (Computer-Aided Software Engineering) tool. Regardless of the technology to be adopted, the final outcome of the software development is always a working software system. However, when it comes to software reengineering, there is rather less consensus on either approaches or outcomes. Shall we use black-box or white-box reverse engineering for program understanding? Shall we produce data and control flow graphs, or some kind of formal specifications as the output of analysis? Each of these techniques has its pros and cons of tackling various software reengineering problems, and none of them on its own suffices to a whole reengineering project. A proper integration of various techniques capable of solving a specific issue could be an effective way to unravel a complicated software system. This kind of integration has to be done from an architectural point of view. One of the most exciting outcomes of recent efforts on software architecture is the Object Management Group’s (OMG) Model-Driven Architecture (MDA). MDA provides a unified framework for developing middleware-based modern distributed systems, and also a definite goal for software reengineering. This chapter presents a unified software reengineering methodology based on Model-Driven Architecture, which consists of a framework, a process, and related techniques.

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Green DRCT

International Journal of Knowledge Discovery in Bioinformatics ◽

10.4018/ijkdb.2017010102 ◽

2017 ◽

Vol 7 (1) ◽

pp. 14-29

Author(s):

Sangharatna Godboley ◽

Arpita Dutta ◽

Durga Prasad Mohapatra

Keyword(s):

Energy Consumption ◽

Software Testing ◽

Transformation Method ◽

New Approach ◽

Code Coverage ◽

Coverage Metrics ◽

Branch Coverage ◽

Concolic Testing ◽

Green Software ◽

Environment Sustainability

Being a good software testing engineer, one should have the responsibility towards environment sustainability. By using green principles and regulations, we can perform Green Software Testing. In this paper, we present a new approach to enhance Branch Coverage and Modified Condition/Decision Coverage uses concolic testing. We have proposed a novel transformation technique to improve these code coverage metrics. We have named this new transformation method Double Refined Code Transformer (DRCT). Then, using JoulMeter, we compute the power consumption and energy consumption in this testing process. We have developed a tool named Green-DRCT to measure energy consumption while performing the testing process.

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