Arpita Dutta

Java-HCT: An approach to increase MC/DC using hybrid concolic testing for Java programs

Modified Condition / Decision Coverage (MC/DC) is the second strongest coverage criterion in white-box testing. According to DO178C/RTCA criterion it is mandatory to achieve Level A certification for MC/DC. Concolic testing is the combination of Concrete and Symbolic execution. It is a systematic technique that performs symbolic execution but uses randomly-generated test inputs to initialize the search and to allow the tool to execute programs when symbolic execution fails. In this paper, we extend concolic testing by computing MC/DC using the automatically generated test cases. On the other hand Feedback-Directed Random Test Generation builds inputs incrementally by randomly selecting a method call to apply and find arguments from among previously-constructed inputs. As soon as the input is built, it is executed and checked against a set of contracts and filters. In our proposed work, we combine feedback-directed test cases generation with concolic testing to form Java-Hybrid Concolic Testing (Java-HCT). Java-HCT generates more number of test cases since it combines the features of both Feedback- Directed Random Test and Concolic Testing. Hence, through Java-HCT, we achieve high MC/DC. Combinations of approaches represent different tradeoffs of completeness and scalability. We develop Java-HCT using RANDOOP, jCUTE, and COPECA. Combination of RANDOOP and jCUTE creates more test cases. COPECA is used to measure MC/DC% using the generated test cases. Experimental study shows that Java-HCT produces better MC/DC% than individual testing techniques(feedback-directed random testing and concolic testing). We have improved MC/DC by ×1.62 and by ×1.26 for feedback-directed random testing and concolic testing respectively.

GECOJAP: A novel source-code preprocessing technique to improve code coverage

Abstract Safety critical standards such as DO178B/DO178C/ RTCA (Radio Technical Commission for Aeronautics) mandates coverage based testing in Aerospace applications. These standards mandate Level A certification for Modified Condition/Decision Coverage (MC/DC). To perform exhaustive and rigorous testing, concolic testing is used in the testing phase of the software development life cycle. But, still some concolic testers need to improve their performance, so that they can achieve higher coverage. We present an automated Java code transformation technique that can be used as a front-end to concolic testing tool for achieving high coverage. We have developed our tool using four modules. The tool named GEaring COverage for JAva Program (GECOJAP) for implementation of our approach. The first module shows a source code preprocessing technique called JEX-NCT (Java Exclusive-NOR Code Transformer) that inserts dummy branches according to Modified Condition / Decision Coverage (MC/DC) criterion. The second module represents a concolic tester named jCUTE (an open source tool) we used to generate test cases. The third module presents computation of MC/DC% using the generated test cases and original program. The fourth module shows the speed calculator that measures speed of test case generation, GECOJAP is more powerful and efficient in comparison to the existing techniques in terms of code transformation. Using GECOJAP one can, achieve higher code coverage. Also, GECOJAP results in the time and speed of the test case generation process. Our experimentation on ten Java programs for thirty executions shows that our approach achieves higher Branch Coverage and MC/DC over traditional concolic testers by 13.79% and 19% respectively.

Measuring Hit Ratio Metric for SOA-Based Application Using Black-Box Testing

In our proposed work, we discuss how to generate test cases automatically for BPEL processes to compute Hit Ratio percentage of an SOA application. First, we design an SOA-based application using OpenEsb tool. That application is supplied to code converter to get XML code of the designed application. Then, we have supplied this XML code to Tcases tool to generate test cases according to black-box testing technique. These test cases are supplied to Hit Ratio Calculator to compute Hit Ratio percentage. On an average of four SOA-based applications, we achieved Hit Ratio percentage as 63.94%.

Green DRCT: Measuring Energy Consumption of an Enhanced Branch Coverage and Modified Condition/Decision Coverage Technique

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.

COLT: Extending CONCOLIC testing to measure LCSAJ Coverage

In this paper, we propose a method for generating efficient test cases, that ensure the adequacy of software testing using appropriate software metrics such as Branch Coverage and Linear Code Sequence And Jump (LCSAJ). Now a days, automated testing is essential for software testing industries which saves time as well as cost. CONCOLIC testing generates test cases, these test cases can compute code coverage in an automated manner. Since, there exists no such concolic testing approach that computes LCSAJ, therefore in this paper we extend concolic testing to measure LCSAJ coverage. We have used CREST tool to generate test cases. We have developed LCSAJ coverage Analyzer that accepts test cases generated by CREST along with the input C program, and produces LCSAJ Coverage percentage. We have conducted our experiment for fifteen C programs. On an average, for fifteen C programs, we achieved 76.04% of LCSAJ coverage in 3.887 secs of executional time.

Measuring MC/DC at design phase using UML sequence diagram and concolic testing

This work describes Modified Condition/ Decision Coverage (MC/DC) criterion for performing testing of the interactions among a set of collaborating objects. This criterion is based on UML Sequence Diagrams. The sequences of Synchronized and Asynchronized messages in the sequence diagrams are used to define the code coverage goals for the family of criteria. In this paper, first we design an UML Sequence Diagram. XML produces XMI code for the designed UML Sequence Diagram. Next, JAXB converts the XMI code into Java code. To generate test cases using concolic testing for the Java program which is derived from the UML Sequence Diagram, we have used jCUTE. These test cases are then supplied to COPEPCA (COverage PErcentage CAlculator) to measure MC/DC%.

Measuring Branch Coverage for the SOA Based Application Using Concolic Testing

This work describes the working of white-box testing for the Service-Oriented Architecture (SOA) based Application. Now, a days it is very essential to perform code coverage testing to understand the quality of software. This paper deals with the measurement of branch coverage percentage for the BPEL architecture that orchestrates all the services, which are distributed geographically. Here, we are testing the code coverage of BPEL architecture, which actually shows the invocations of services when it is required. This work integrates the existing open source tools, to automate the computation of branch coverage for SOA based application. This paper shows a novel technique for generation of test cases and computing branch coverage through our proposed tool.