Multi-Objective Adapted Binary Bat for Test Suite Reduction

Highly Scalable Multi Objective Test Suite Minimisation Using Graphics Cards

Despite claims of “embarrassing parallelism” for many optimisation algorithms, there has been very little work on exploiting parallelism as a route for SBSE scalability. This is an important oversight because scalability is so often a critical success factor for Software Engineering work. This paper shows how relatively inexpensive General Purpose computing on Graphical Processing Units (GPGPU)...

Redundancy Based Test-Suite Reduction

The size of a test-suite has a direct impact on the costs and the effort of software testing. Especially during regression testing, when software is re-tested after some modifications, the size of the testsuite is important. Common test-suite reduction techniques select subsets of test-suites that achieve given test requirements. Unfortunately, not only the test-suite size but also the fault de...

Many Independent Objective (MIO) Algorithm for Test Suite Generation

Using hybrid algorithm for Pareto efficient multi-objective test suite minimisation

Test suite minimisation techniques seek to reduce the effort required for regression testing by selecting a subset of test suites. In previous work, the problem has been considered as a single-objective optimisation problem. However, real world regression testing can be a complex process in which multiple testing criteria and constraints are involved. This paper presents the concept of Pareto e...

An Adapted Non-dominated Sorting Algorithm (ANSA) for Solving Multi Objective Trip Distribution Problem

Trip distribution deals with estimation of trips distributed among origins and destinations and is one of the important stages in transportation planning. Since in the real world, trip distribution models often have more than one objective, multi-objective models are developed to cope with a set of conflict goals in this area. In a proposed method of adapted non-dominated sorting algorithm (ANS...