Process of Designing Robust, Dependable, Safe and Secure Software for Medical Devices: Point of Care Testing Device as a Case Study

This paper presents a holistic methodology for the design of medical device software, which encompasses of a new way of eliciting requirements, system design process, security design guideline, cloud architecture design, combinatorial testing process and agile project management. The paper uses point of care diagnostics as a case study where the software and hardware must be robust, reliable to provide accurate diagnosis of diseases. As software and software intensive systems are becoming increasingly complex, the impact of failures can lead to significant property damage, or damage to the environment. Within the medical diagnostic device software domain such failures can result in misdiagnosis leading to clinical complications and in some cases death. Software faults can arise due to the interaction among the software, the hardware, third party software and the operating environment. Unanticipated environmental changes and latent coding errors lead to operation faults despite of the fact that usually a significant effort has been expended in the design, verification and validation of the software system. It is becoming increasingly more apparent that one needs to adopt different approaches, which will guarantee that a complex software system meets all safety, security, and reliability requirements, in addition to complying with standards such as IEC 62304. There are many initiatives taken to develop safety and security critical systems, at different development phases and in different contexts, ranging from infrastructure design to device design. Different approaches are implemented to design error free software for safety critical systems. By adopting the strategies and processes presented in this paper one can overcome the challenges in developing error free software for medical devices (or safety critical systems).

Towards Improving the Quality of Requirement and Testing Process in Agile Software Development:An Empirical Study

Software testing is a critical phase due to misconceptions about ambiguities in the requirements during specification,which affect the testing process.Therefore,it is difficult to identify all faults in software.As requirement changes continuously,it increases the irrelevancy and redundancy during testing.Due to these challenges;fault detection capability decreases and there arises a need to improve the testing process,which is based on changes in requirements specification.In this research,we have developed a model to resolve testing challenges through requirement prioritization and prediction in an agile-based environment.The research objective is to identify the most relevant and meaningful requirements through semantic analysis for correct change analysis.Then compute the similarity of requirements through case-based reasoning,which predicted the requirements for reuse and restricted to error-based requirements.Afterward,the apriori algorithm mapped out requirement frequency to select relevant test cases based on frequently reused or not reused test cases to increase the fault detection rate.Furthermore,the proposed model was evaluated by conducting experiments.The results showed that requirement redundancy and irrelevancy improved due to semantic analysis,which correctly predicted the requirements,increasing the fault detection rate and resulting in high user satisfaction.The predicted requirements are mapped into test cases,increasing the fault detection rate after changes to achieve higher user satisfaction.Therefore,the model improves the redundancy and irrelevancy of requirements by more than 90%compared to other clustering methods and the analytical hierarchical process,achieving an 80%fault detection rate at an earlier stage.Hence,it provides guidelines for practitioners and researchers in the modern era.In the future,we will provide the working prototype of this model for proof of concept.

Software Test Case Generation with Adequacy Analysis on Scenario-Based Testing

This paper studies the software scenario testing, which is commonly used in black-box testing at present. In the paper, the workflow model based on task-driven, which is very common in scenario testing, is analyzed. According to test adequacy criteria in scenario testing, the model is designed to correspond test cases in the light of logic block(LB). The final test cases that conform to the test adequacy criteria can be obtained through test case combination and test case reduction. In the last part of the paper, example of actual workflow is to design the efficient test case. Therefore the method is proved to be effective.

Software Operational Profile Based Test Case Allocation Using Fuzzy Logic

Software operational profile （SOP） is used in software reliability prediction, software quality assessment, performance analysis of software, test case allocation, determination of ＂when to stop testing,＂ etc. Due to the limited data resources and large efforts required to collect and convert the gathered data into point estimates, reluctance is observed by the software professionals to develop the SOP. A framework is proposed to develop SOP using fuzzy logic, which requires usage data in the form of linguistics. The resulting profile is named fuzzy software operational profile （FSOP）. Based on this work, this paper proposes a generalized approach for the allocation of test cases, in which occurrence probability of operations obtained from FSOP are combined with the criticality of the operations using fuzzy inference system （FIS）. Traditional methods for the allocation of test cases do not consider the application in which software operates. This is intuitively incorrect. To solve this problem, allocation of test cases with respect to software application using the FIS model is also proposed in this paper.

Modified Harris Hawks Optimization Based Test Case Prioritization for Software Testing

Generally,software testing is considered as a proficient technique to achieve improvement in quality and reliability of the software.But,the quality of test cases has a considerable influence on fault revealing capability of software testing activity.Test Case Prioritization(TCP)remains a challenging issue since prioritizing test cases is unsatisfactory in terms of Average Percentage of Faults Detected(APFD)and time spent upon execution results.TCP ismainly intended to design a collection of test cases that can accomplish early optimization using preferred characteristics.The studies conducted earlier focused on prioritizing the available test cases in accelerating fault detection rate during software testing.In this aspect,the current study designs aModified Harris Hawks Optimization based TCP(MHHO-TCP)technique for software testing.The aim of the proposed MHHO-TCP technique is to maximize APFD and minimize the overall execution time.In addition,MHHO algorithm is designed to boost the exploration and exploitation abilities of conventional HHO algorithm.In order to validate the enhanced efficiency of MHHO-TCP technique,a wide range of simulations was conducted on different benchmark programs and the results were examined under several aspects.The experimental outcomes highlight the improved efficiency of MHHO-TCP technique over recent approaches under different measures.

Test case generation based on orthogonal table for software black-box testing

Software testing is an important means to assure the software quality. This paper presents a practicable method to generate test cases of software testing, which is operational and high efficient. We discuss the identification of software specification categories and choices and make a classification tree. Based on the orthogonal array, it is easy to generate test cases. The number of this method is less than that of all combination of the choices.

Optimal Reordering Trace Files for Improving Software Testing Suitcase

An invariant can be described as an essential relationship between program variables.The invariants are very useful in software checking and verification.The tools that are used to detect invariants are invariant detectors.There are two types of invariant detectors:dynamic invariant detectors and static invariant detectors.Daikon software is an available computer program that implements a special case of a dynamic invariant detection algorithm.Daikon proposes a dynamic invariant detection algorithm based on several runs of the tested program;then,it gathers the values of its variables,and finally,it detects relationships between the variables based on a simple statistical analysis.This method has some drawbacks.One of its biggest drawbacks is its overwhelming time order.It is observed that the runtime for the Daikon invariant detection tool is dependent on the ordering of traces in the trace file.A mechanism is proposed in order to reduce differences in adjacent trace files.It is done by applying some special techniques of mutation/crossover in genetic algorithm(GA).An experiment is run to assess the benefits of this approach.Experimental findings reveal that the runtime of the proposed dynamic invariant detection algorithm is superior to the main approach with respect to these improvements.

Scientific Software Installation Testing Using a Plan-Do-Check-Act Methodology： A Case Study

The scientific software installation testing has a main goal： Evaluate if the software meets its requirements and specifications. In this paper, the scientific software installation in six machines is evaluated. The software installation was tested using a PDCA （Plan-Do-Check-Act） approach in 3 machines and were compared with other 3 machines which were installed exclusively based in the installer experience. The software installed on the machines using a PDCA approach for testing, lead to the expected results. Scientific software installation should be tested during the installation and not as a final test. A methodology based on PDCA is recommended for testing scientific software.

Testing Component-Based Software: What It has to do with Design and Component Selection

In a component-based software development life cycle, selection of preexisting components is an important task. Every component that has to be reused has an associated risk of failure of not meeting the functional and non-functional requirements. A component's failure would lead a developer to look for some other alternative of combinations of COTS, in-house and engineered components among possible candidate combinations. This means design itself can readily change. The very process of design of a software system and component selection seems to be heavily dependent on testing results. Instability of design, further, becomes more severe due to requirements change requests. Therefore, this instability of design has to be essentially mitigated by using proper design and testing approaches, otherwise, it may lead to exorbitantly high testing cost due to the repeated testing of various alternatives. How these three activities: Component-based software design, component selection and component-based software testing are interrelated? What process model is most suited to address this concern? This work explores the above questions and their implication in terms of nature of a process model that can be convincing in case of component-based software development.

An Application of Paraconsistent Annotated Logic for Design Software Testing Strategies

Nowadays, application model systems for decision-making based on non-classical logic such as Paraconsistent Logic are used successfully in the treatment of uncertainties. The method presented in this paper is based on the fundamental concepts of Paraconsistent Annotated Logic with annotation of 2 values (PAL2v). In this study, two algorithms based on PAL2v are presented gradually, to extract the effects of the contradiction in signals of information from a database of uncertain knowledge. The Paraconsistent Extractors Algorithms of Contradiction Effect-Para Extrctr is applied to filters of networks of analyses (PANets) of signal information, where uncertain and contradictory signals may be found. Software test case scenarios are subordinated to an application model of Paraconsistent decision-making, which provides an analysis using Paraconsistent Logic in the treatment of uncertainties for design software testing strategies. This quality-quantity criterion to evaluate the software product quality is based on the characteristics of software testability analysis. The Para consistent reasoning application model system presented in this case study, reveals itself to be more efficient than the traditional methods because it has the potential to offer an appropriate treatment to different originally contradicting source information.

文献“Software Testing in Space Programs”点评

作者以他个人的观点,对该文献中重要部分进行了点评,指出:空间软件地面可靠性测试尽管困难重重且有诸多限制,但不能放松甚至放弃执行现有的软件地面测试标准;应从"精神号"火星探测器飞行失败中吸取教训,加强软件地面测试,包括传统软件黑盒和白盒测试方法中的典型测试项目(如:健壮测试、应力测试、极值测试、随机测试等);已经公布的新软件研发标准——Aerospace Report No.TOR-2004(3909)-3537,Software Development Standard for Space Systems值得我们参考。

Real-time embedded software testing method based on extended finite state machine

The reliability of real-time embedded software directly determines the reliability of the whole real-time embedded sys- tem, and the effective software testing is an important way to ensure software quality and reliability. Based on the analysis of the characteristics of real-time embedded software, the formal method is introduced into the real-time embedded software testing field and the real-time extended finite state machine （RT-EFSM） model is studied firstly. Then, the time zone division method of real-time embedded system is presented and the definition and description methods of time-constrained transition equivalence class （timeCTEC） are presented. Furthermore, the approaches of the testing sequence and test case generation are put forward. Finally, the proposed method is applied to a typical avionics real- time embedded software testing practice and the examples of the timeCTEC, testing sequences and test cases are given. With the analysis of the testing result, the application verification shows that the proposed method can effectively describe the real-time embedded software state transition characteristics and real-time requirements and play the advantages of the formal methods in accuracy, effectiveness and the automation supporting. Combined with the testing platform, the real-time, closed loop and automated simulation testing for real-time embedded software can be realized effectively.

On modeling approach for embedded real-time software simulation testing

Modeling technology has been introduced into software testing field. However, how to carry through the testing modeling effectively is still a difficulty. Based on combination of simulation modeling technology and embedded real-time software testing method, the process of simulation testing modeling is studied first. And then, the supporting environment of simulation testing modeling is put forward. Furthermore, an approach of embedded real-time software simulation testing modeling including modeling of cross-linked equipments of system under testing （SUT）, test case, testing scheduling, and testing system service is brought forward. Finally, the formalized description and execution system of testing models are given, with which we can realize real-time, closed loop, mad automated system testing for embedded real-time software.

Empirical Measurement of the Software Testing and Reliability

The meanings of parameters of software reliabi- lity models are investigated in terms of the process of the software testing and in terms of other measurements of software. Based on the investigation, the empirical estimation of the parameters is addressed. On one hand, these empirical estimates are also measurements of the software, which can be used to control and to optimize the process of the software development. On the other hand, by treating these empirical estimates as Bayes priors, software reliability models are extended such that the engineers’ experience can be integrated into and hence to improve the models.

NHPP-based software reliability model considering testing effort and multivariate fault detection rate

In recent decades,many software reliability growth models（SRGMs） have been proposed for the engineers and testers in measuring the software reliability precisely.Most of them is established based on the non-homogeneous Poisson process（NHPP）,and it is proved that the prediction accuracy of such models could be improved by adding the describing of characterization of testing effort.However,some research work indicates that the fault detection rate（FDR） is another key factor affects final software quality.Most early NHPPbased models deal with the FDR as constant or piecewise function,which does not fit the different testing stages well.Thus,this paper first incorporates a multivariate function of FDR,which is bathtub-shaped,into the NHPP-based SRGMs considering testing effort in order to further improve performance.A new model framework is proposed,and a stepwise method is used to apply the framework with real data sets to find the optimal model.Experimental studies show that the obtained new model can provide better performance of fitting and prediction compared with other traditional SRGMs.

Analysis on testing and operational reliability of software

Software reliability was estimated based on NHPP software reliability growth models. Testing reliability and operational reliability may be essentially different. On the basis of analyzing similarities and differences of the testing phase and the operational phase, using the concept of operational reliability and the testing reliability, different forms of the comparison between the operational failure ratio and the predicted testing failure ratio were conducted, and the mathematical discussion and analysis were performed in detail. Finally, software optimal release was studied using software failure data. The results show that two kinds of conclusions can be derived by applying this method, one conclusion is to continue testing to meet the required reliability level of users, and the other is that testing stops when the required operational reliability is met, thus the testing cost can be reduced.

Managing Software Testing Technical Debt Using Evolutionary Algorithms

Technical debt(TD)happens when project teams carry out technical decisions in favor of a short-term goal(s)in their projects,whether deliberately or unknowingly.TD must be properly managed to guarantee that its negative implications do not outweigh its advantages.A lot of research has been conducted to show that TD has evolved into a common problem with considerable financial burden.Test technical debt is the technical debt aspect of testing(or test debt).Test debt is a relatively new concept that has piqued the curiosity of the software industry in recent years.In this article,we assume that the organization selects the testing artifacts at the start of every sprint.Implementing the latest features in consideration of expected business value and repaying technical debt are among candidate tasks in terms of the testing process(test cases increments).To gain the maximum benefit for the organization in terms of software testing optimization,there is a need to select the artifacts(i.e.,test cases)with maximum feature coverage within the available resources.The management of testing optimization for large projects is complicated and can also be treated as a multi-objective problem that entails a trade-off between the agile software’s short-term and long-term value.In this article,we implement a multi-objective indicatorbased evolutionary algorithm(IBEA)for fixing such optimization issues.The capability of the algorithm is evidenced by adding it to a real case study of a university registration process.

An Approach to Event-Driven Software Testing

In this paper, the testing technology of event-driven software is focused. It is first analyzed the difference between event-driven software and the traditional procedure-oriented software, and based on the above analysis, the mechanism of event-driven and the effect of introduction of event-driven mechanism on software testing are unveiled. Then based on the characteristic of the event-driven software, the traditional software testing method is improved, and testing policy of event based test is presented in this paper.Moreover the event coverage criteria are defined and given here. At the same time the event executing rule are further uncovered, such as ordinal event, non-ordinal event, predecessor event and concurrent event etc., and also the methods of testing according to event executing rule are studied.

Research and Practice of Hybrid Teaching for Software Testing based on Interactive Learning

To address the problems of insufficient number of personalized exercises and cases and teachers’lack of grasp of students’weak knowledge points in the current software testing online courses,we study the strategy of establishing and updating intelligent exercise sets and case libraries and analyze the answers and dig out the weak points of knowledge through group intelligence reasoning and interactive machine learning methods.This will help teachers to make uniform and targeted explanations,reduce manual judgment,and achieve intelligent teaching quality reform,and implement the educational concepts of“keeping up with the times”and“teaching according to students’abilities”.