Informatics Publishing Limited

Sandeep Dalal ¹, Rajender Chhillar ¹

Affiliations
1 Department of Computer Science and Applications, M.D. University, Rohtak, IN

Abstract

Fault is defined as any inappropriate behaviour of AUT (Application under Test) which could lead to the failure of the software. Fault detection and reporting goes in parallel and effective reporting of faults by tester means that the faults having high severity & priority are taken care appropriately and fixed by developer with quick turn around time & should not inject other faults, because most of the times fixing one fault injects other faults which are generally difficult to find due to lesser regression testing time and strict deadlines. This paper caters to the detailed analysis of fault reporting system which is the most important aspect of software testing life cycle & has direct impact on improvement of software quality. IFRS is proposed fault reporting system which identifies and defines all the elements of an ideal FRS which if followed will optimize the fault reporting, correction and validation process. If quality team can optimize the fault reporting process and report all the valid bugs in time, then it will certainly enhance the reliability of overall software system. A Survey was conducted among the different organizations to make a comparative analysis of fault reporting tools and to identify the major problems during fault reporting.

Keywords

AUT (Application Under Test), Faults Detection, Fault Reporting, FRS (Fault Reporting System), IFRS (Ideal Fault Reporting System).

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Sonia Bansal ¹, Sandeep Dalal ¹

Affiliations
1 DCSA, Maharshi Dayanand University, Rohtak, IN

Abstract

Steganography is the method of hiding the secret information in a medium (such as digital image, audio and video). Steganography comes from the Greek words “stegano” means covered and “graphy” means writing and thus means, covered writing. A medium that is used for hiding information is called a cover medium. After hiding secret information in a cover medium, a stego medium is obtained. The main purpose of steganography is to hide the information inside the cover medium so that it becomes impossible for intruder to detect the secret information present in the cover image.  This paper gives an overview of image steganography and watermarking that will allow transmitting the secret information without any changes on the internet. Watermarking technique provides us the copyright protection and image authentication.

Keywords

Fragile, LSB, MSE, PSNR, Steganography, Stego Image, Watermarking.

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Kamna Solanki ¹, Yudhvir Singh ¹, Sandeep Dalal ¹

Affiliations
1 M. D. University, Rohtak - 124001, Haryana, IN

Abstract

Objectives: Experimental evaluation of “m-ACO” (Modified Ant Colony Optimization) technique for test case prioritization has been performed on two well known software testing problems namely “Triangle Classification Problem” and “Quadratic Equation Problem”.  Apart from these two problems, m-ACO has been experimentally evaluated using open source software JFreeChart. Methods: m-ACO finds the optimized solution to test suite prioritization by modifying the phenomenon used by natural ants to reach to its food source and select the food. This paper attempts to experimentally and comparatively evaluate the proposed m-ACO technique for test case prioritization against some contemporary meta-heuristic techniques using two well known software testing problems and open source problem. Performance evaluation has been measured using two metrics namely APFD (Average Percentage of Faults Detected) and PTR (Percentage of Test Suite Required for Complete Fault Coverage). Findings: The proposed technique m-ACO proves its efficiency on both the parameters. m-ACO achieves higher fault detection rate with minimized test suite as comparative to other meta-heuristic techniques for test case prioritization. Improvements: The proposed technique m-ACO basically works by modifying the food source searching and selection pattern of the real ants. Real ants grab every type food source it comes across; while modified ants evaluate the food fitness and uniqueness before selection. This phenomenon enhances the quality and diversity of deposited food source.

Keywords

Fault Coverage, Genetic Algorithm, Regression Testing, Software Testing, Test Suite Prioritization.

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Kamna Solanki ¹, Yudhvir Singh ¹, Sandeep Dalal ¹

Affiliations
1 M. D. University, Rohtak - 124001, Haryana, IN

Abstract

Objectives: The novel test case prioritization technique “m-ACO” (“Modified Ant Colony Optimization”) for regression testing has been comparatively evaluated. Methods: “m-ACO” prioritize the test cases by altering the food source selection criteria of natural ants to enhance fault diversity. The code for the proposed technique for prioritizing test case “m-ACO” has been implemented in Perl language. This paper makes a comparative evaluation of proposed “m-ACO” technique for prioritization of test cases with GA (“Genetic Algorithm”), BCO (“Bee Colony Optimization”) Algorithms and ACO (“Ant Colony Optimization”) Algorithms using three case studies. Two metrics namely APFD (“Average Percentage of Faults Detected”) and PTR (“Percentage of Test Suite Required for Complete Fault Coverage”) have been used to measure the effectiveness of the proposed “m-ACO” technique. Findings: The proposed technique “m-ACO” produced optimal or near optimal solutions. The proposed “m-ACO” technique proves its efficiency in comparison to GA, BCO and ACO methods individually. Improvements: The proposed technique improves the ACO method by altering food source selection criteria of natural ants. The future work in this direction will comparatively evaluate the proposed “m-ACO” technique using some well known software testing problems and open source software. An automated tool for the proposed technique is being developed.

Keywords

Fault Coverage, Genetic Algorithm, Regression Testing, Software Testing, Test Suite Prioritization.

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Sandeep Dalal ¹, Kamna Solanki ²

Affiliations
1 Department of Computer Science and Applications, Maharshi Dayanand University, Rohtak – 124001, Haryana, IN
2 Department of Computer Science Engineering, UIET, Maharshi Dayanand University, Rohtak - 124001, Haryana, IN

Abstract

Objectives: Algorithms analogous to the natural processes have been employed to optimize the fault detection efficiency and reduce software testing time. Test case selection for software testing is the most critical and time consuming part as exhaustive software testing is not possible. Recently, a novel compound technique BCO-m-GA for test case selection has been proposed based on non-sequential combination of stratified sampling, BCO (Bee Colony Optimization) and GA (Genetic Algorithm). This paper makes a performance evaluation of the proposed BCO-m-GA technique. Methods: This paper attempts to analyse the performance of the BCO-m-GA technique for test case selection against individual non-compounded algorithms GA and BCO. Findings: The results underline the improved performance of BCO-m-GA in comparison to GA and BCO in terms of differential of number of Decision Nodes Covered (DNC) and rate of change of Fitness Score (FS) of the optimal solution. Improvements: The insights obtained in this study would help researchers in improved framing of test case selection procedures.

Keywords

Bee Colony Optimization, Genetic Algorithm, Software Testing, Test Case Optimization, Test Case Selection

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