Software Cybernetics Research Articles

Software reliability assessment: a software cybernetics perspective

Software reliability assessment is a key step that determines whether the software can be delivered for the use or not. Because only limited testing resources are allowed for software reliability assessment, this paper proposes a software cybernetics perspective that introduces feedback and self-adaptive control to guide the software testing process in the software reliability assessment. Also, an adaptive testing strategy based on gradient descent is proposed for software reliability assessment. The theoretical and experimental results show that reliability assessment methods based on software cybernetics can achieve highly precise and stable software-reliability-assessment results using restricted testing resources.

Parameter Adjustment of Test Profile in Dynamic Random Testing

The basic motivation of Dynamic Random Testing (DRT), which is proposed in the context of software cybernetics, is to use test results as the feedback information to realize dynamic adjusting of selection probabilities of all the test cases. It is unreasonable that the profile adjustment in the original DRT is somehow contingent and only utilizes the latest execution result. Moreover, the parameter adjustment of test profile for different subdomains is uniform in original DRT, which may not the best solution to improve the effectiveness of DRT. This paper presents an improved dynamic random testing that based on the function information of test cases (DRT-F) which makes use of correlation among the test cases to improve the performance of the original DRT. In DRT-F, the parameter adjustment is according to the function information of test case classification and makes the DRT adaptive to different classification of its influence on its performance.

Modern software cybernetics: New trends

Classify software cybernetics as Software Cybernetics I and II.Identify the transition from Software Cybernetics I to Software Cybernetics II.Indicate that some new research areas are related to Software Cybernetics II.Highlight new research trends of Software Cybernetics II for further research. Software cybernetics research is to apply a variety of techniques from cybernetics research to software engineering research. For more than fifteen years since 2001, there has been a dramatic increase in work relating to software cybernetics. From cybernetics viewpoint, the work is mainly on the first-order level, namely, the software under observation and control. Beyond the first-order cybernetics, the software, developers/users, and running environments influence each other and thus create feedback to form more complicated systems. We classify software cybernetics as Software Cybernetics I based on the first-order cybernetics, and as Software Cybernetics II based on the higher order cybernetics. This paper provides a review of the literature on software cybernetics, particularly focusing on the transition from Software Cybernetics I to Software Cybernetics II. The results of the survey indicate that some new research areas such as Internet of Things, big data, cloud computing, cyber-physical systems, and even creative computing are related to Software Cybernetics II. The paper identifies the relationships between the techniques of Software Cybernetics II applied and the new research areas to which they have been applied, formulates research problems and challenges of software cybernetics with the application of principles of Phase II of software cybernetics; identifies and highlights new research trends of software cybernetic for further research.

WITHDRAWN: Modern software cybernetics: Trends with new cybernetics

Software cybernetics research is to apply a variety of techniques from cybernetics research to software engineering research. For more than fifteen years since 2001, there has been a dramatic increase in work on software cybernetics. From cybernetics viewpoint, the work is mainly on the first-order level, namely, the software under observation and control. Beyond the first-order cybernetics, the software, developers/users, and running environments influence each other and thus create feedback to form a more complicated system. We classify software cybernetics as classical software cybernetics based on the first-order cybernetics, and as modern software cybernetics based on the higher order cybernetics (new cybernetics). This paper provides a review of literature on software cybernetics, especially focuses on the transition from classical software cybernetics to modern software cybernetics. The results of the survey indicate that some new research areas such as Internet of Things, big data, cloud computing, cyber-physical systems, and even creative computing are related to modern software cybernetics. The paper identifies the relationships between the techniques of new cybernetics applied and the new research areas to which they have been applied; formulates research problems and challenges of software cybernetics with the application of principles of new cybernetics; identifies and highlights new research trends of modern software cybernetic for further research.

Self-adaptive architecture evolution with model checking: A software cybernetics approach

We apply cybernetics theory to control software behaviors in architecture-level.We propose Breeze/ADL to specify the self-adaptive architecture.We design a learning algorithm to derive feedbacks to adjust the architecture.We extend tool - Breeze to support our framework. Display Omitted The cloud computing era requires software architecture to be self-adaptive to the dynamic environment. This autonomous feature brings uncertainty and makes software behavior difficult to control. The uncontrollable behavior is caused by ill-defined architecture and might lead to system disruption. To address this problem, we propose a novel framework which applies software cybernetics to guide self-adaptive architecture evolution. In our framework, we formulate the architecture evolution process as a feedback control process. In the process, we take the self-adaptive architecture model and the model checking technique as the controlled object and controller, respectively. First, the self-adaptive architecture is specified by Breeze/ADL. Second, the framework leverages model checking to validate adaptive Breeze/ADL specifications. Third, a learning algorithm is designed to regulate validation results to generate feedback rules - Productions to guide the architecture evolution. A smart phone application example is chosen to demonstrate the feasibility of our framework. The results show that our framework facilitates architects to detect undesired states which are caused by error-prone adaptation rules.

Software cybernetics in BPM: Modeling software behavior as feedback for evolution by a novel discovery method based on augmented event logs

Interpret business process management (BPM) with the view of cybernetics.Discuss the relation between software cybernetics and BPM.Analyze the role of process discovery in software cybernetics in context of BPM.Propose a novel process discovery method based on a kind of augmented event logs.All implicit places and implicit dependencies can be found. Business Process Management (BPM) is a quickly developing management theory in recent years. The goal of BPM is to improve corporate performance by managing and optimizing the businesses process in and among enterprises. The goal is easier to achieve with the closed-loop feedback mechanism from business process execution to redesign in BPM life cycle, where the business process itself and the set of activities in BPM are viewed as a controlled object and a controller respectively. In this feedback control system, process mining plays an important role in generating feedback of process execution for redesign. However, the existing discovery methods cannot mine certain special structures from execution logs (e.g., implicit dependency, implicit place and short loops) correctly and their mining efficiencies cannot meet the requirements of online process mining. In this paper, we propose a novel discovery method to overcome these challenges based on a kind of augmented event log that will also bring new research directions for process discovery. A case study is presented for introducing how the mined model can be used in business process evolution. Results of experiments are described to show the improvements of the proposed algorithm compared with others.

A software cybernetics approach to self-tuning performance of on-line transaction processing systems

We construct two layer fuzzy rules based on the collected data.We develop algorithms from software cybernetics view to reconfigure the performance control parameters.We show self-tuning performance for On-Line Transaction Processing. Self-tuning performance of On-Line Transaction Processing (OLTP) Systems is a challenging and time-consuming task since multiple performance parameters are needed to be automatically configured in Database Management Systems (DBMSs). In this paper, we present a software cybernetics approach to self-tune the performance of DBMSs. A DBMS is designed with an adaptive control based on fuzzy logic such that it has the capability to control objects, i.e., the performance parameters, and update the controller itself, i.e., a set of fuzzy rules in our case. The principles and concepts in software cybernetics are applied to guide the synthesis of software controllers for monitoring and adapting system behaviors. Experimental results for On-Line Transaction Processing using TPC-C, a benchmark of the Transaction Processing Performance Council, show that the proposed method is feasible and effective.

The verification of program relationships in the context of software cybernetics

Software Cybernetics is adopted by our method to improve reliability of software.A nested control system is established to manage the process of verification.A model is built from requirements to formalize expected behaviors of software.Internal relationships of program are abstracted gradually to construct a model.The feedback is represented by a form of intermediate code. Software cybernetics aims at improving the reliability of software by introducing the control theory into software engineering domain systematically. A key issue in software verification is to improve the reliability of software by inspecting whether the software can achieve its expected behaviors. In this paper, the thought of software cybernetics is applied in the process of verification to address this issue and a nested control system is established. The proposed method verifies functional requirements in a dynamic environment with constantly changing user requirements, in which the program serves as a controlled object, and the verification strategy determined by software behavioral model (SBM) serves as a controller. The main contribution of this paper includes: (1) SBM is established in software design phase, and a concern-based construction approach is proposed, which starts from obtaining the software expected functionality extracted from a requirement text; (2) Program abstract-relationship model (PARM) is constructed basing on a process of gradual abstract to be a controlled object; (3) Feedback in a form of intermediate code is generated in the process of verification. The proposed method is validated by our case study.

모바일 상황인식 서비스의 추론 결과 적응을 지원하기 위한 MADA 피드백 프레임워크

The high portability and mobility of mobile devices have given rise to critical concerns with regard to mobile situation-aware services that utilize user situation information in the mobile domain. Mobile situation-aware services for mobile devices are provided by collecting and analyzing data, from which the user situation is inferred through an inference system. However, the high mobility of the mobile domain has made it difficult to infer the required results. In addition, previous studies have not identified a systematic approach to modifying and adapting. In this paper, we propose a systematic feedback process model based on software cybernetics in order to address the abovementioned problems. Further, we propose a MADA(Monitoring, Analysis, Determinating, Adaptation) framework for the feedback process model. Thus, the proposed approach supports the development of self-adaptive mobile situation-aware services that can infer appropriate results and manage the inferred results systematically.

An EFSM Approach to Software Design Based on the Supervisory Control Theory

The research of software design, based on the supervisory control theory, is an important content in software cybernetics. The existing software model used in the software design with the supervisory control theory is Polynomial Dynamic System (PDS), which is transformed from SIGNAL files. This obstructs its widespread application. Extended Finite State Machine (EFSM) model is widely applied in software engineering field and it may alleviate the state explosion problem of Finite State Machine (FSM) to some extent. In this paper, the EFSM model is suggested to study software design problem. This paper proposed two kinds of software design problems based on EFSM model. For the first problem, a necessary and sufficient condition for software existence is obtained. For the second problem, a necessary and sufficient condition for software existence and an optimal algorithm to such software design are presented.

Special section on software cybernetics

This special section on software cybernetics deals with novel results and new methodologies that bring together software engineering and discrete event control theory ideas. Papers treating distinct issues and techniques regarding software engineering, such as component based and secure development, using various control theory approaches, relevant to the interplay between software engineering and control, were solicited. After careful reviewing the following paper was selected from a large list of papers under consideration: Changyan Zhou and Ratnesh Kumar: Semantic Translation of Simulink Diagrams to Input/Output Extended Finite Automata We would like to thank the editors of this special section, Joao Cangusu, Ron Kennett, and Ratnesh Kumar, for their efforts in putting together this special section.

GUEST EDITORS' INTRODUCTION

International Journal of Software Engineering and Knowledge EngineeringVol. 19, No. 05, pp. 625 (2009) Featured Topic: Software Cybernetics, Guest Editors: João W. Cangussu and Aditya P. MathurNo AccessGUEST EDITORS' INTRODUCTIONJOÃO W. CANGUSSU and ADITYA P. MATHURJOÃO W. CANGUSSUUniversity of Texas at Dallas, USA and ADITYA P. MATHURPurdue University, USAhttps://doi.org/10.1142/S0218194009004350Cited by:0 Next AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsRecommend to Library ShareShare onFacebookTwitterLinked InRedditEmail Remember to check out the Most Cited Articles! Check out our titles in C++ Programming! FiguresReferencesRelatedDetails Recommended Vol. 19, No. 05 Metrics History PDF download

ON THE ONLINE PARAMETER ESTIMATION PROBLEM IN ADAPTIVE SOFTWARE TESTING

Software cybernetics is an emerging area that explores the interplay between software and control. The controlled Markov chain (CMC) approach to software testing supports the idea of software cybernetics by treating software testing as a control problem, where the software under test serves as a controlled object modeled by a controlled Markov chain and the software testing strategy serves as the corresponding controller. The software under test and the corresponding software testing strategy form a closed-loop feedback control system. The theory of controlled Markov chains is used to design and optimize the testing strategy in accordance with the testing/reliability goal given explicitly and a priori. Adaptive software testing adjusts and improves software testing strategy online by using the testing data collected in the course of software testing. In doing so, the online parameter estimations play a key role. In this paper, we study the effects of genetic algorithm and the gradient method for doing online parameter estimation in adaptive software testing. We find that genetic algorithm is effective and does not require prior knowledge of the software parameters of concern. Although genetic algorithm is computationally intensive, it leads the adaptive software testing strategy to an optimal software testing strategy that is determined by optimizing a given testing goal, such as minimizing the total cost incurred for removing a given number of defects. On the other hand, the gradient method is computationally favorable, but requires appropriate initial values of the software parameters of concern. It may lead, or fail to lead, the adaptive software testing strategy to an optimal software testing strategy, depending on whether the given initial parameter values are appropriate or not. In general, the genetic algorithm should be used instead of the gradient method in adaptive software testing. Simulation results show that adaptive software testing does work and outperforms random testing.

Adaptive software testing with fixed-memory feedback

Adaptive software testing is the counterpart of adaptive control in software testing. It means that software testing strategy should be adjusted on-line by using the testing data collected during software testing as our understanding of the software under test is improved. In this paper we propose a new strategy of adaptive software testing in the context of software cybernetics. This new strategy employs fixed-memory feedback for on-line parameter estimations and is intended to circumvent the drawbacks of the assumption that all remaining defects are equally detectable at constant rate and to reduce the underlying computational complexity of on-line parameter estimations. A comprehensive case study with the Space program demonstrates that the new adaptive testing strategy can really work in practice and may noticeably outperform the purely-random testing strategy and the random-partition testing strategy (or collectively, the random testing strategies) in terms of the number of tests used to detect and remove a given number of defects in a single process of software testing and the corresponding standard deviation. In addition, the case study shows that the input domain of the software under test should be partitioned non-evenly for the adaptive testing strategy.

Optimal software testing in the setting of controlled Markov chains

The controlled Markov chains (CMC) approach to software testing treats software testing as a control problem, where the software under test serves as a controlled object that is modeled as controlled Markov chain, and the software testing strategy serves as the corresponding controller. In this paper we extend the CMC approach to software testing to the case that the number of tests that can be applied to the software under test is limited. The optimal testing strategy is derived if the true values of all the software parameters of concern are known a priori. An adaptive testing strategy is employed if the true values of the software parameters of concern are not known a priori and need to be estimated on-line during software testing by using testing data. A random testing strategy ignores all the related information (true values or estimates) of the software parameters of concern and follows a uniform probability distribution to select a possible test case. Simulation results show that the performance of an adaptive testing strategy cannot compete that of the optimal testing strategy, but should be better than that of a random testing strategy. This paper further justifies the idea of software cybernetics that is aimed to explore the interplay between software theory/engineering and control theory/engineering.

Optimal and adaptive testing for software reliability assessment

Optimal software testing is concerned with how to test software such that the underlying testing goal is achieved in an optimal manner. Our previous work shows that the optimal testing problem for software reliability growth can be treated as closed-loop or feedback control problem, where the software under test serves as a controlled object and the software testing strategy serves as the corresponding controller. More specifically, the software under test is modeled as controlled Markov chains (CMCs) and the control theory of Markov chains is used to synthesize the required optimal testing strategy. In this paper, we show that software reliability assessment can be treated as a feedback control problem and the CMC approach is also applicable to dealing with the optimal testing problem for software reliability assessment. In this problem, the code of the software under test is frozen and the software testing process is optimized in the sense that the variance of the software reliability estimator is minimized. An adaptive software testing strategy is proposed that uses the testing data collected on-line to estimate the required parameters and selects next test cases. Simulation results show that the proposed adaptive software testing strategy can really work in the sense that the resulting variance of the software reliability estimate is much smaller than that resulting from the random testing strategies. The work presented in this paper is a contribution to the new area of software cybernetics that explores the interplay between software and control.

On the polynomial dynamic system approach to software development

In this paper the development of reactive software is transformed into a control problem, and the supervisory control theory for discrete event dynamic systems is suggested to solve this control problem. The operating environment under consideration is viewed as a controlled plant, the software under development as the corresponding controller, and the software requirements as the corresponding control objective. This idea leads to a constructive approach of software design, which ensures properties required a priori of the software under development. In this way the validation of the software under development is reduced to the validation of properties independent of implementation process. We reveal the inconsistence in using the concept of reachability to specify software requirements and clarify six different definitions of reachability. Two different definitions of invariance for specifying software requirements are also clarified. We then show how to synthesize the required controller or obtain software design solutions if the underlying software requirements are specified by several new combinations of reachability and invariance. The topic of this paper falls into the scope of software cybernetics that explores the interplay between software and control.

Optimal stopping of multi-project software testing in the context of software cybernetics

Software cybernetics explores the interplay between control theory/engineering and software theory/engineering. The controlled Markov chains (CMC) approach to software testing follows the idea of software cybernetics and treats software testing as a control problem. The software under test serves as a controlled object and the software testing strategy serves as the corresponding controller. The software under test and the software testing strategy make up a closed-loop feedback control system, and the theory of controlled Markov chains can be used to design and optimize software testing strategies in accordance with testing/reliability goals given a priori. In this paper we apply the CMC approach to the optimal stopping problem of multi-project software testing. The problem under consideration assumes that a single stopping action can stop testing of all the software systems under test simultaneously. The theoretical results presented in this paper describe how to test multiple software systems and when to stop testing in an optimal manner. An illustrative example is used to explain the theoretical results. The study of this paper further justifies the effectiveness of the CMC approach to software testing in particular and the idea of software cybernetics in general.

Optimal software testing and adaptive software testing in the context of software cybernetics

Software cybernetics explores the interplay between software theory/engineering and control theory/engineering. Following the idea of software cybernetics, the controlled Markov chains (CMC) approach to software testing treats software testing as a control problem. The software under test serves as a controlled object, and the (optimal) testing strategy determined by the theory of controlled Markov chains serves as a controller. This paper analyzes the behavior of the corresponding optimal test profile determined by the CMC approach to software testing and introduces adaptive software testing. It is shown that in some cases the optimal test profile is Markovian, whereas in some other cases the optimal test profile demonstrates a different scenario. The adaptive software testing adjusts software testing strategy on-line by using testing data collected during software testing in response to changes in our understanding of the software under test. Simulation results show that the adaptive strategy of software testing is feasible and significantly reduces the number of test cases required to detect and remove a certain number of software defects in comparison with the random strategy of software testing.