Testing refinements by refining tests

One of the potential benefits of formal methods is that they offer the possibility of reducing the costs of testing. A specification acts as both the benchmark against which any implementation is tested, and also as the means by which tests are generated. There has therefore been interest in developing test generation techniques from formal specifications, and a number of different methods have been derived for state based languages such as Z, B and VDM. However, in addition to deriving tests from a formal specification, we might wish to refine the specification further before its implementation. The purpose of this paper is to explore the relationship between testing and refinement. As our model for test generation we use a DNF partition analysis for operations written in Z, which produces a number of disjoint test cases for each operation. In this paper we discuss how the partition analysis of an operation alters upon refinement, and we develop techniques that allow us to refine abstract tests in order to generate test cases for a refinement. To do so we use (and extend existing) methods for calculating the weakest data refinement of a specification

Formal mutation testing for Circus

International audienceContext: The demand from industry for more dependable and scalable test-development mechanisms has fostered the use of formal models to guide the generation of tests. Despite many advancements having been obtained with state-based models, such as Finite State Machines (FSMs) and Input/Output Transition Systems (IOTSs), more advanced formalisms are required to specify large, state-rich, concurrent systems. Circus, a state-rich process algebra combining Z, CSP and a refinement calculus, is suitable for this; however, deriving tests from such models is accordingly more challenging. Recently, a testing theory has been stated for Circus, allowing the verification of process refinement based on exhaustive test sets. Objective: We investigate fault-based testing for refinement from Circus specifications using mutation. We seek the benefits of such techniques in test-set quality assertion and fault-based test-case selection. We target results relevant not only for Circus, but to any process algebra for refinement that combines CSP with a data language. Method: We present a formal definition for fault-based test sets, extending the Circus testing theory, and an extensive study of mutation operators for Circus. Using these results, we propose an approach to generate tests to kill mutants. Finally, we explain how prototype tool support can be obtained with the implementation of a mutant generator, a translator from Circus to CSP, and a refinement checker for CSP, and with

Developing a pressure ulcer risk factor minimum data set and risk assessment framework

AIM: To agree a draft pressure ulcer risk factor Minimum Data Set to underpin the development of a new evidenced-based Risk Assessment Framework.BACKGROUND: A recent systematic review identified the need for a pressure ulcer risk factor Minimum Data Set and development and validation of an evidenced-based pressure ulcer Risk Assessment Framework. This was undertaken through the Pressure UlceR Programme Of reSEarch (RP-PG-0407-10056), funded by the National Institute for Health Research and incorporates five phases. This article reports phase two, a consensus study.DESIGN: Consensus study.METHOD: A modified nominal group technique based on the Research and Development/University of California at Los Angeles appropriateness method. This incorporated an expert group, review of the evidence and the views of a Patient and Public Involvement service user group. Data were collected December 2010-December 2011.FINDINGS: The risk factors and assessment items of the Minimum Data Set (including immobility, pressure ulcer and skin status, perfusion, diabetes, skin moisture, sensory perception and nutrition) were agreed. In addition, a draft Risk Assessment Framework incorporating all Minimum Data Set items was developed, comprising a two stage assessment process (screening and detailed full assessment) and decision pathways.CONCLUSION: The draft Risk Assessment Framework will undergo further design and pre-testing with clinical nurses to assess and improve its usability. It will then be evaluated in clinical practice to assess its validity and reliability. The Minimum Data Set could be used in future for large scale risk factor studies informing refinement of the Risk Assessment Framework

Does microbicide use in consumer products promote antimicrobial resistance? A critical review and recommendations for a cohesive approach to risk assessment

The increasing use of microbicides in consumer products is raising concerns related to enhanced microbicide resistance in bacteria and potential cross resistance to antibiotics. The recently published documents on this topic from the European Commission have spawned much interest to better understand the true extent of the putative links for the benefit of the manufacturers, regulators, and consumers alike. This white paper is based on a 2-day workshop (SEAC-Unilever, Bedford, United Kingdom; June 2012) in the fields of microbicide usage and resistance. It identifies gaps in our knowledge and also makes specific recommendations for harmonization of key terms and refinement/standardization of methods for testing microbicide resistance to better assess the impact and possible links with cross resistance to antibiotics. It also calls for a better cohesion in research in this field. Such information is crucial to developing any risk assessment framework on microbicide use notably in consumer products. The article also identifies key research questions where there are inadequate data, which, if addressed, could promote improved knowledge and understanding to assess any related risks for consumer and environmental safety

Interview Protocol Refinement: Fine-Tuning Qualitative Research Interview Questions for Multi-Racial Populations in Malaysia

A reliable interview protocol is the key to obtain good quality interview data. However, developing a valid interview protocol is not a simple task, especially for beginner-level researchers. Extensive understanding of the research topic is no guarantee to quality interview findings because many other factors may affect the interview process. In our study among injured workers in Malaysia, researchers face additional challenge of interviewing multi-ethnic and multi-cultural study population. Most of them are also from lower socioeconomic status and education level. The objective of this study is to refine the pre-constructed interview protocol to address these challenges for valid data collection. The protocol must be easily understood and cover all research objectives to gain insights of the worker’s return to work experience. This article demonstrated the use of the 4-step Interview Protocol Refinement (IPR) Framework on the interview questionnaire. The steps were (1) ensuring alignment between interview questions and research questions, (2) constructing an inquiry-based conversation, (3) receiving feedback on interview protocols and (4) pilot testing of the interview questions. The IPR framework is an effective tool for improving the interview protocol reliability and validity. The refinement processes corrected some shortcoming in the pre-refined questionnaires and the pilot testing ensured that the refined questions were understood by the respondent and able to obtain the intended answers based on the research objectives. Research quality can be further enhanced by applying additional strategies during the stages of research tools validation and data analysis

Log-based Evaluation of Label Splits for Process Models

Process mining techniques aim to extract insights in processes from event logs. One of the challenges in process mining is identifying interesting and meaningful event labels that contribute to a better understanding of the process. Our application area is mining data from smart homes for elderly, where the ultimate goal is to signal deviations from usual behavior and provide timely recommendations in order to extend the period of independent living. Extracting individual process models showing user behavior is an important instrument in achieving this goal. However, the interpretation of sensor data at an appropriate abstraction level is not straightforward. For example, a motion sensor in a bedroom can be triggered by tossing and turning in bed or by getting up. We try to derive the actual activity depending on the context (time, previous events, etc.). In this paper we introduce the notion of label refinements, which links more abstract event descriptions with their more refined counterparts. We present a statistical evaluation method to determine the usefulness of a label refinement for a given event log from a process perspective. Based on data from smart homes, we show how our statistical evaluation method for label refinements can be used in practice. Our method was able to select two label refinements out of a set of candidate label refinements that both had a positive effect on model precision.Comment: Paper accepted at the 20th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, to appear in Procedia Computer Scienc