#### Filter Results:

- Full text PDF available (24)

#### Publication Year

2011

2017

- This year (1)
- Last 5 years (31)
- Last 10 years (33)

#### Publication Type

#### Co-author

#### Journals and Conferences

#### Key Phrases

Learn More

- Harsh Bhasin, Neha Singla, Shruti Sharma
- ACM SIGSOFT Software Engineering Notes
- 2013

Manual Test Data Generation is an expensive, error prone and tedious task. Therefore, there is an immediate need to make the automation of this process as efficient and effective as possible. The work presented intends to automate the process of Test Data Generation with a goal of attaining maximum coverage. A Cellular Automata system is discrete in space… (More)

This Genetic Algorithms (GAs) are a type of optimization algorithms which combine survival of the fittest and a simplified version of Genetic Process .It has as yet not been proved whether machine learning can be considered as a problem apt for applying GAs. Therefore the work explores the use of GAs in Machine learning. A detailed study on the success of… (More)

Rule generation in an expert system requires heuristics and selection procedures which are not just accurate but are also efficient. This premise makes Genetic Algorithms (GAs) a natural contender for the rule selection process. The work analysis the previous attempts of applying GAs to rule selection and proposes major changes in the clustering algorithms… (More)

Maximum Clique Problem (MCP) is an NP Complete problem which finds its application in diverse fields. The work suggests the solution of above problem with the help of Genetic Algorithms (GAs). The work also takes into consideration, the various attempts that have been made to solve this problem and other such problems. The intend is to develop a generic… (More)

Test Data Generation is an intricate process which requires intensive manual labor and thus a lot of project time. There is an immediate need of finding out an effective technique for automating the process as manual Test Data Generation escalates the project cost. The paper proposes the use of Artificial Life in generating and minimizing the Test Cases.… (More)

- Harsh Bhasin, Neha Singla
- ACM SIGSOFT Software Engineering Notes
- 2013

Test Data Generation is the soul of automated testing. The dream of having efficient and robust automated testing software can be fulfilled only if the task of designing a robust automated test data generator can be accomplished. In the work we explore the gaps in the existing techniques and intend to fill these gaps by proposing new algorithms. The… (More)

Regression testing is an immensely important process in the maintenance phase. The prioritization of test case becomes all the more important owing to the fact that it is not feasible to run all the test cases after each and every change. The proposed work dwells on the power of fuzzy expert system to make decisions which are better than the normal expert… (More)

- Harsh Bhasin, Neha Singla
- 2012

Subset Sum Problem (SSP) is an NP Complete problem which finds its application in diverse fields. The work suggests the solution of above problem with the help of genetic Algorithms (GAs). The work also takes into consideration, the various attempts that have been made to solve this problem and other such problems. The intent is to develop a generic… (More)

- Harsh Bhasin, Geetanjli Ahuja
- 2012

The problem of finding a minimum vertex cover is an NP hard optimization problem. Some approximation algorithms for the problem have been proposed but most of them are neither optimal nor complete. The work proposes the use of the theory of natural selection via Genetic Algorithms (GAs) for solving the problem. The proposed work has been tested for some… (More)

Maximum clique problem is one of the most important NP-hard problems which find its applications in numerous fields ranging from networking to the determination of the structure of a protein molecule. The present work carries forward one of our earlier works and examines the effect of variation of parameters for achieving optimization. The results obtained… (More)