This article gives a short overview of the main characteristics of mutation tools. If a test suite finds all the artificial errors inserted in the mutants and finds no fault in the original, it's likely that the program under test is free of them. Obviously, the validity of this affirmation depends on the nature of the artificial fault: some of them are better than others. This testing technique has been used in the research arena to check the effectiveness of new proposed testing techniques, but it hasn't been used until recently in industry due to its costs and the lack of knowledge and industrial tools.

Mutation Testing

Traditionally, mutation testing generates an abundance of small deviations of a program, called mutants. At industrial systems the scale and size of Facebook's, doing this is infeasible. We should not create mutants that the test suite would likely fail on or that give no actionable signal to developers. To tackle this problem, in this paper, we semi-automatically learn error-inducing patterns from a corpus of common Java coding errors and from changes that caused operational anomalies at Facebook specifically. We combine the mutations with instrumentation that measures which tests exactly visited the mutated piece of code. Results on more than 15,000 generated mutants show that more than half of the generated mutants survive Facebook's rigorous test suite of unit, integration, and system tests. Moreover, in a case study with 26 developers, all but two expressed that the mutation exposed a lack of testing in principle. As such, almost half of the 26 would actually act on the mutant presented to them by adapting an existing or creating a new test. The others did not for a variety of reasons often outside the scope of mutation testing. It remains a practical challenge how we can include such external information to increase the true actionability rate on mutants.

What It Would Take to Use Mutation Testing in Industry—A Study at Facebook

Traditionally, mutation testing generates an abundance of small deviations of a program, called mutants. At industrial systems the scale and size of Facebook's, doing this is infeasible. We should not create mutants that the test suite would likely fail on or that give no actionable signal to developers. To tackle this problem, in this paper, we semi-automatically learn error-inducing patterns from a corpus of common Java coding errors and from changes that caused operational anomalies at Facebook specifically. We combine the mutations with instrumentation that measures which tests exactly visited the mutated piece of code. Results on more than 15,000 generated mutants show that more than half of the generated mutants survive Facebook's rigorous test suite of unit, integration, and system tests. Moreover, in a case study with 26 developers, all but two found information of automatically detected test holes interesting in principle. As such, almost half of the 26 would actually act on the mutant presented to them by adapting an existing or creating a new test. The others did not for a variety of reasons often outside the scope of mutation testing. It remains a practical challenge how we can include such external information to increase the true actionability rate on mutants.

What It Would Take to Use Mutation Testing in Industry--A Study at Facebook

Two-Level Genetic Algorithm for Clustered Traveling Salesman Problem with Application in Large-Scale TSPs

Higher order mutation testing: A Systematic Literature Review

Mutation testing is a technique in which all possible faulty versions of a program are generated for mutation analysis and to assess the test suit adequacy. In literature, most research on mutation testing has been focused on traditional programming paradigm. Some of the traditional mutation-operators are incorporated in mutation testing of object oriented systems. Recently class level mutation operators are also defined, which is the main focus of this article with particular consideration of the OO programming (OOP) language JAVA. A number of automated tools have been developed to generate the defective versions of program and to execute them against test suit. Classification, evaluation of the mutation operators against some proposed parameters and identification of some research areas is a result of this survey.

Mutation operators for object-oriented systems: A survey

The Generalized Travelling Salesman Problem (GTSP) is a special instance of the well-known travelling salesman problem which belongs to NP-hard class of problems. In the GTSP problem which is being addressed in this research we split the set of nodes (e.g. cities) into non-overlapping subsets; where the optimal solution is a minimum cost tour visiting exactly one node from each subset. In this paper a genetic algorithm with new and innovative way of generating initial population is presented. Concepts like cluster segmentation, partially greedy crossover, greedy insert mutation and enhanced swap mechanisms are also introduced. An initial analysis of the proposed algorithm shows enhanced results in terms of optimality and computational time as compared to existing approaches.

/pdf/a-novel-genetic-algorithm-for-gtsp-4u4mk6q0yt.pdf

A Novel Genetic Algorithm for GTSP

The classical 0�1 knapsack problem is one of the mo re studied combinatorial optimization problem which belong to the NP class of algorithms. A number of its generalized forms have been addressed by various researchers using different designing techniques. In this paper, we design and analyze the Multiple Knapsack Problems (MKP) by using genetic algorithms. A modified Genetic Algorithm (mGA) is developed with the key focus on efficient encoding scheme for binary string representation and a competent dynamic programming based method for initial population generation. Furthermore transposition is applied in mGA instead of crossover for maintaining the population diversity. Performance analysis of the mGA, justifies our claims that the population incorporates adequate quality and diversity to reach a near optimal solution and transposition reduces the overall computation time.

/pdf/a-dynamic-programming-based-ga-for-0-1-modified-knapsack-2eu6uwunoz.pdf

A Dynamic Programming based GA for 0-1 Modified Knapsack Problem

Road traffic efficiency may be improved by developing an integrated network for cooperative driving provision (CDP) among vehicles on the road. In a dance urban traffic scenario, the quality of service may be compromised when required bandwidth is not provided by the existing network architecture that impacts negatively on the cooperative behaviour of the vehicles. To solve these problems, a network architecture with better scheduling of resources that meet the quality of service (QoS) is required. So, we proposed a fifth-generation (5G) technology-based network architecture that provides the required QoS for CDP. The proposed architecture consists of a resource scheduling mechanism within the 5G network and a scheme for cooperative behaviour among the vehicles on the road. The implementation of the proposed network architecture is done by incorporating it into a well-known vehicular clustering algorithm. The performance of the proposed architecture is compared with existing schemes that show improvement. 

Quality of service enabled resource scheduling for cooperative driving provision in the internet of vehicles

As new aircrafts are inducted into the fleets of commercial airliners the vast airspace is becoming congested on certain routes and commercial hubs. Midair collision risks are increasing with the growth in air traffic volume and therefore; for the sake of safety aircrafts must be technically adept of monitoring the airspace and divert from a predetermined route, when traffic or weather conditions so dictates. In this research a fuzzy based aircraft collision avoidance system is proposed which is capable of generating an alert of a potential midair collision. In addition, the proposed system is competent of protecting the aircraft by taking its control, if no preventive action is taken within specified time. The intension is that the collision avoidance scheme can be achieved by monitoring and avoiding the intersection of guarding spheres between aircrafts. The concepts of aircraft domain and advisory areas are used in the proposed system to compute a guarding sphere, radical axis and automatic control region for the collision avoidance system. The proposed system can be integrated with existing collision avoidance systems for enhanced air traffic security.

http://www.wseas.us/e-library/conferences/2009/moscow/AIC/AIC56.pdf

A fuzzy based aircraft collision avoidance system

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