ImReMuDF: Redundant Mutants Identification Method Based on Definition and Reference of Variables

Mutation testing is an effective defect-based software testing method, but a large number of mutants lead to expensive testing costs, which hinders the application of variation testing in industrial engineering. To solve this problem and enable mutation testing to be applied in industrial engineering, this paper improves the method of identifying redundant mutants based on data flow analysis and proposes the inclusion relationship between redundant mutants, so that the redundancy rate of mutants is reduced. In turn, the cost of mutation testing can be reduced. The redundant mutants identification method based on definition and reference of variables (ImReMuDF) was validated and evaluated using 8 C programs. The minimum improvement in redundant mutant identification rate was 34.0%, and the maximum improvement was 71.3% in the 8 C programs tested, and the verification results showed that the method is feasible and effective and has been improved in reducing redundant mutants and effectively reducing the execution time of mutation testing.

Static detection of silent misconfigurations with deep interaction analysis

The behavior of large systems is guided by their configurations: users set parameters in the configuration file to dictate which corresponding part of the system code is executed. However, it is often the case that, although some parameters are set in the configuration file, they do not influence the system runtime behavior, thus failing to meet the user’s intent. Moreover, such misconfigurations rarely lead to an error message or raising an exception. We introduce the notion of silent misconfigurations which are prohibitively hard to identify due to (1) lack of feedback and (2) complex interactions between configurations and code. This paper presents ConfigX, the first tool for the detection of silent misconfigurations. The main challenge is to understand the complex interactions between configurations and the code that they affected. Our goal is to derive a specification describing non-trivial interactions between the configuration parameters that lead to silent misconfigurations. To this end, ConfigX uses static analysis to determine which parts of the system code are associated with configuration parameters. ConfigX then infers the connections between configuration parameters by analyzing their associated code blocks. We design customized control- and data-flow analysis to derive a specification of configurations. Additionally, we conduct reachability analysis to eliminate spurious rules to reduce false positives. Upon evaluation on five real-world datasets across three widely-used systems, Apache, vsftpd, and PostgreSQL, ConfigX detected more than 2200 silent misconfigurations. We additionally conducted a user study where we ran ConfigX on misconfigurations reported on user forums by real-world users. ConfigX easily detected issues and suggested repairs for those misconfigurations. Our solutions were accepted and confirmed in the interaction with the users, who originally posted the problems.

Actors’ Construction in Building Social Harmony in Tamilouw, Seram Island, Maluku Province

The Conflict in Maluku on January 19th, 1999 affected the harmony of life of the Moluccas universally. As a result, the people of Maluku live segregated in their respective communities. However, there are still groups of people who continue to live in harmony within the framework of diversity, namely the Tamilouw people on Seram-Maluku Island. The social harmony found in Tamilouw which is multi-ethnic and multi-religious is inseparable from the role of actors, and the workings of a systematic social structure. This study aimed to find out how the actors construct in the frame of diversity to achieve social harmony in the daily lives of Tamilouw people. The discipline approach used was the sociology of knowledge, using the reality construction theory of Peter Berger and Luckmann. The research paradigm used was constructivism with a qualitative approach. Key informants were religious leaders, indigenous leaders, community leaders, indigenous people and migrants. Data collection was carried out using observation, interview, and documentation techniques. The techniques of data analysis was the data flow analysis model according to Miles & Huberman. Based on the research findings, data analysis and discussion, it can be concluded that: Social harmony maintained in Tamilouw, Seram-Maluku Island, is the result of the integration of four main actors, namely religious leaders, traditional leaders, government figures and youth leaders. These four actors have a network or bond of trust, work strategies and rules of prevailing norms.

A Unified Model for Context-Sensitive Program Analyses:

Context-sensitive methods of program analysis increase the precision of interprocedural analysis by achieving the effect of call inlining. These methods have been defined using different formalisms and hence appear as algorithms that are very different from each other. Some methods traverse a call graph top-down, whereas some others traverse it bottom-up first and then top-down. Some define contexts explicitly, whereas some do not. Some of them directly compute data flow values, while some first compute summary functions and then use them to compute data flow values. Further, different methods place different kinds of restrictions on the data flow frameworks supported by them. As a consequence, it is difficult to compare the ideas behind these methods in spite of the fact that they solve essentially the same problem. We argue that these incomparable views are similar to those of blind men describing an elephant, called context sensitivity, and make it difficult for a non-expert reader to form a coherent picture of context-sensitive data flow analysis. We bring out this whole-elephant view of context sensitivity in program analysis by proposing a unified model of context sensitivity that provides a clean separation between computation of contexts and computation of data flow values. Our model captures the essence of context sensitivity and defines simple soundness and precision criteria for context-sensitive methods. It facilitates declarative specifications of context-sensitive methods, insightful comparisons between them, and reasoning about their soundness and precision. We demonstrate this by instantiating our model to many known context-sensitive methods.