Non-functional Properties Research Articles

On Throughput Approximation of Resource-Allocation Systems by Bottleneck Regrowing

Complex systems, such as manufacturing, logistics, or Web services, are commonly modeled as discrete event systems dealing with the resource-allocation problem. In particular, Petri nets (PNs) are a widely used formalism to model these systems. Although their functional properties have been extensively studied in the literature, their nonfunctional properties (such as throughput) have usually been ignored. In this brief, we focus on a PN subclass useful for modeling concurrent sequential processes with shared resources, termed $S^{4}PR$ nets. For these nets, we present an iterative strategy that makes intensive use of mathematical programming problems to approximate system throughput. Initially, our strategy selects the slowest part (a subsystem) of the net. Then, the next slowest parts are considered. In each step, the throughput is computed solving analytically the underlying continuous-time Markov chain when feasible (or by simulation, otherwise). Since only certain subsystems are considered, the state-explosion problem inherent to the increasing net size is mitigated. We evaluate our strategy in a set of randomly generated $S^{4}PR$ nets. Our findings show that the throughput improves the upper throughput bound computation by almost 20% and that small portions of the net are enough to approximate system throughput.

Information Recommendation Based on Domain Knowledge in App Descriptions for Improving the Quality of Requirements

Apps have concentrated sale platforms, in which there often exist some products similar to the new App to be developed. The main features of these products are given in their introductions, providing an important resource for developers to improve the quality of the requirements of their own App. In this paper, we propose an approach to gain and recommend requirements related information from App descriptions to help developers use the resource efficiently. First, we construct a model by mining domain knowledge from App descriptions with the method proposed in our previous work and use initial requirements to retrieve their related information from the model. Then, we analyze the information and recommend them from three aspects: static information of the existing Apps for identifying the priorities of requirements; functional features and non-functional properties of features for giving the detailed design of the Apps in requirements; and the combinations of features for enriching the requirements. To validate the proposed approach, we conducted experiments and a survey based on the data in Google Play. The results show that our approach can identify the existing products with initial requirements reasonably, and also indicate that the developers confirm the usefulness of the recommended information in practice.

Privacy-Preserving Reengineeringof Model-View-Controller ApplicationArchitectures Using Linked Data

When a legacy system's software architecture cannot be redesigned, implementing additional privacy requirements is often complex, unreliable and costly to maintain. This paper presents a privacy-by-design approach to reengineer web applications as linked data-enabled and implement access control and privacy preservation properties. The method is based on the knowledge of the application architecture, which for the Web of data is commonly designed on the basis of a model-view-controller pattern. Whereas wrapping techniques commonly used to link data of web applications duplicate the security source code, the new approach allows for the controlled disclosure of an application's data, while preserving non-functional properties such as privacy preservation. The solution has been implemented and compared with existing linked data frameworks in terms of reliability, maintainability and complexity.

Side-Channel Analysis via Symbolic Execution and Model Counting

An important problem in computer security is the detection of side-channel vulnerabilities. Information gained by observing nonfunctional properties of program executions (i.e., sidechannels such as execution time or memory usage) can enable attackers to infer secrets that the program accesses (such as a password). In this talk, I will discuss how symbolic execution, combined with a model counting constraint solver, can be used for quantifying side- channel leakage in Java programs. I will also discuss automata-based model counting techniques. We have implemented these techniques by integrating our modelcounting constraint solver, called Automata-Based model Counter (ABC), with the symbolic execution tool Symbolic Path Finder (SPF).

Effective Search-Based Approach for Testing Non-Functional Properties in Software System: an Empirical Review

Effective Search-Based Approach for Testing Non-Functional Properties in Software System: an Empirical Review

Mutation-Based Harmony Search Algorithm for Hybrid Testing of Web Service Composition.

Web service composition is a method of developing a new web service from an existing one based on business goals. Web services selected for composition should provide accurate operational results and reliable applications. However, most alternative service providers have not yet fulfilled users' needs in terms of services and processes. Service providers, in fact, have focused on enhancing nonfunctional attributes, such as efficiencies of time, cost, and availability, which still face limitations. Furthermore, it remains advantageous to compose services and suitably plan them around business plans. Thus, this study introduces hybrid testing using a combination of the functional and nonfunctional testing approaches. The former was used to design a test case through the equivalence class partitioning technique, and the latter was used to select suitable services for the test results. We find defects and appropriate solutions for combining services based on business requirements. The mutation-based harmony search (MBHS) algorithm is proposed to select web services and to compose with minimum defects. The results of this study reveal that MBHS can support a combination of various services more efficiently and dramatically than other metaheuristic methodologies. Additionally, it helps find appropriate solutions to compose services based on business plans.

ASSESSING PERFORMANCE OF AGENTS IN A MAS: AN EXPERIMENTAL STUDY

A Multi-Agent System (MAS) is understood as a system consisting of interacting autonomous agents. Research on MAS is mainly concerned with functional properties such as coordination, rationality, and knowledge modeling. A very less attention is paid for the research activity on the nonfunctional properties performance, scalability and reliability of the MAS. However, as the MAS technologies have gradually matured to be exploited in building practical distributed applications, the non-functional properties have become increasingly important, and it is now vital to pay attention to the issues of nonfunctional characteristics of agents. We propose to access the performance of agents in MAS and the system is implemented using JADE. The experimental study provides the opportunity for cause and effect relationships. We considered a tiered architecture for the MAS. A tiered design can lessen the overall impact of changes to the application and allows modifying a component without disturbing the next Tier. So with the help of a good deployment plan, we can distribute the layers over multiple physical tiers in distributed computing to implement a better architecture of the system. The case study considered for illustration is Supply-Chain Management and the results obtained are validated with the tool SMTQA.

Constraint programming heuristics for configuring optimal products in multi product lines

Nowadays, complex application domains require configuring multi-product lines where product features and constraints among them are specified in several variability models. These variability models are enriched with inter-model constraints representing the existing relations among domain concerns, and with non-functional properties modeled as attributes attached to product features. Multiple techniques use constraint programming to automate the cumbersome task of manually configuring a suitable product. Currently, there are some proposals to improve the performance of constraint solvers when configuring single-model product lines, however configuration scenarios with multiple interrelated and attributed models are not yet targeted. This paper proposes and evaluates three search heuristics used to configure optimal products regarding multi-objective criteria. Results are compared against the default search strategy of the Choco constraint solver. We evaluated the performance for configuring optimal products in four state-of-the-art product lines and 130 generated variability models representing multi-product lines that scale up to 6400 features and 960 constraints. As a result, we observe that the proposed heuristics perform better than the default solver strategy when the variability models scale in terms of features. In contrast, the default strategy and one of the proposed heuristics perform better as the number of interdependencies between variability models increases.

A promise checked is a promise kept: inspection testing

Occasionally, developers need to ensure that the compiler treats their code in a specific way that is only visible by inspecting intermediate or final compilation artifacts. This is particularly common with carefully crafted compositional libraries, where certain usage patterns are expected to trigger an intricate sequence of compiler optimizations – stream fusion is a well-known example. The developer of such a library has to manually inspect build artifacts and check for the expected properties. Because this is too tedious to do often, it will likely go unnoticed if the property is broken by a change to the library code, its dependencies or the compiler. The lack of automation has led to released versions of such libraries breaking their documented promises. This indicates that there is an unrecognized need for a new testing paradigm, inspection testing , where the programmer declaratively describes non-functional properties of an compilation artifact and the compiler checks these properties. We define inspection testing abstractly, implement it in the context of the Haskell Compiler GHC and show that it increases the quality of such libraries.

On the impact of code smells on the energy consumption of mobile applications

Context. The demand for green software design is steadily growing higher especially in the context of mobile devices, where the computation is often limited by battery life. Previous studies found how wrong programming solutions have a strong impact on the energy consumption. Objective. Despite the efforts spent so far, only a little knowledge on the influence of code smells, i.e.,symptoms of poor design or implementation choices, on the energy consumption of mobile applications is available. Method. To provide a wider overview on the relationship between smells and energy efficiency, in this paper we conducted a large-scale empirical study on the influence of 9 Android-specific code smells on the energy consumption of 60 Android apps. In particular, we focus our attention on the design flaws that are theoretically supposed to be related to non-functional attributes of source code, such as performance and energy consumption. Results. The results of the study highlight that methods affected by four code smell types, i.e.,Internal Setter, Leaking Thread, Member Ignoring Method, and Slow Loop, consume up to 87 times more than methods affected by other code smells. Moreover, we found that refactoring these code smells reduces energy consumption in all of the situations. Conclusions. Based on our findings, we argue that more research aimed at designing automatic refactoring approaches and tools for mobile apps is needed.

Formalization of business workflow with typed attributed graph

Purpose Business process workflow is a design conceptualization to automate the sequence of activities to achieve a business goal with involved participants and a predefined set of rules. Regarding this, a formal business workflow model is a prime requisite to implement a consistent and rigorous business process. In this context, majority of the existing research works are formalized structural features and have not focused on functional and behavioral design aspects of business processes. To address this problem, this paper aims to propose a formal model of business process workflow called as business process workflow using typed attributed graph (BPWATG) enriched with structural, functional and behavioral characteristics of business processes. Design/methodology/approach Typed attributed graph (ATG) and first-order logic have been used to formalize proposed BPWATG to provide rigorous syntax and semantics towards business process workflows. This is an effort to execute a business workflow on an automated machine. Further, the proposed BPWATG is illustrated using a case study to show the expressiveness of proposed model. Besides, the proposed graph is initially validated using generic modelling environment (GME) case tool. Moreover, a comparative study is performed with existing formal approaches based on several crucial features to exhibit the effectiveness of proposed BPWATG. Findings The proposed model is capable of facilitating structural, functional and behavioral aspects of business process workflows using several crucial features such as dependency conceptualization, timer concepts, exception handling and deadlock detection. These features are used to handle real-world problems and ensure the consistency and correctness of business workflows. Originality/value BPWATG is proposed to formalize a business workflow that is required to make a model of business process machine-readable. Besides, formalizations of dependency conceptualization, exception handling, deadlock detection and time-out concepts are specified. Moreover, several non-functional properties (reusability, scalability, flexibility, dynamicity, reliability and robustness) are supported by the proposed model.

An extensible framework for software configuration optimization on heterogeneous computing systems: Time and energy case study

Context: Application of component based software engineering methods to heterogeneous computing (HC) enables different software configurations to realize the same function with different non–functional properties (NFP). Finding the best software configuration with respect to multiple NFPs is a non–trivial task.Objective: We propose a Software Component Allocation Framework (SCAF) with the goal to acquire a (sub–) optimal software configuration with respect to multiple NFPs, thus providing performance prediction of a software configuration in its early design phase. We focus on the software configuration optimization for the average energy consumption and average execution time.Method: We validated SCAF through its instantiation on a real–world demonstrator and a simulation. Firstly, we verified the correctness of our model through comparing the performance prediction of six software configurations to the actual performance, obtained through extensive measurements with a confidence interval of 95%. Secondly, to demonstrate how SCAF scales up, we performed software configuration optimization on 55 generated use–cases (with solution spaces ranging from 1030 to 3070) and benchmark the results against best performing random configurations.Results: The performance of a configuration as predicted by our framework matched the configuration implemented and measured on a real–world platform. Furthermore, by applying the genetic algorithm and simulated annealing to the weight function given in SCAF, we obtain sub–optimal software configurations differing in performance at most 7% and 13% from the optimal configuration (respectfully).Conclusion: SCAF is capable of correctly describing a HC platform and reliably predict the performance of software configuration in the early design phase. Automated in the form of an Eclipse plugin, SCAF allows software architects to model architectural constraints and preferences, acting as a multi–criterion software architecture decision support system. In addition to said, we also point out several interesting research directions, to further investigate and improve our approach.

An exploratory study on the evolution of Android malware quality

AbstractIn the context of software engineering, product software quality measures how well a software artifact is designed and coded. Software products must satisfy nonfunctional properties (eg, reliability, usability, understandability, and maintainability), in order to make maintenance and evolution sustainable in the long period. Software evolution is an issue of interest for the malware writers, too, for 2 reasons. First, to evade detection with the minimum effort, malware writers use to produce “variants,” which are obtained by applying little changes to existing malware. Morevoer, recent studies demonstrated that malware is increasingly improving evasion strategies and infection mechanisms and is using more and more complex payloads. This suggests that malware writers are devoting relevant efforts and skills for producing high‐quality software. For this reason, we wonder whether malware writers are devoting effort to improve the structural quality of their code, too, as it happens in the development of goodware. To investigate this question, we (1) characterize a dataset containing about 20 000 Android applications, divided into goodware and malware ones, relying on the Android API version they require, and (2) compute software quality metrics, divided into 4 categories (ie, dimensional, complexity, object‐oriented, and Android‐oriented metrics) for apps belonging to each population. We then identify evolution trends of these metrics in malware and goodware. The results of our study demonstrate that goodware and malicious applications exhibit similar evolution trends for some of the quality indicators, suggesting that malware writers care about the overall quality of their code. Code quality could be considered an indirect measure of how many and how fast variants of existing malware will be released in the wild.

Keep your laziness in check

We introduce StrictCheck: a property-based random testing framework for observing, specifying, and testing the strictness of Haskell functions. Strictness is traditionally considered a non-functional property; StrictCheck allows it to be tested as if it were one, by reifying demands on data structures so they can be manipulated and examined within Haskell. Testing strictness requires us to 1) precisely specify the strictness of functions, 2) efficiently observe the evaluation of data structures, and 3) correctly generate functions with random strictness. We tackle all three of these challenges, designing an efficient generic framework for precise dynamic strictness testing. StrictCheck can specify and test the strictness of any Haskell function---including higher-order ones---with only a constant factor of overhead, and requires no boilerplate for testing functions on Haskell-standard algebraic data types. We provide an expressive but low-level specification language as a foundation upon which to build future higher-level abstractions. We demonstrate a non-trivial application of our library, developing a correct specification of a data structure whose properties intrinsically rely on subtle use of laziness: Okasaki's constant-time purely functional queue.

A systematic literature review on the semi-automatic configuration of extended product lines

Product line engineering has become essential in mass customisation given its ability to reduce production costs and time to market, and to improve product quality and customer satisfaction. In product line literature, mass customisation is known as product configuration. Currently, there are multiple heterogeneous contributions in the product line configuration domain. However, a secondary study that shows an overview of the progress, trends, and gaps faced by researchers in this domain is still missing. In this context, we provide a comprehensive systematic literature review to discover which approaches exist to support the configuration process of extended product lines and how these approaches perform in practice. Extend product lines consider non-functional properties in the product line modelling. We compare and classify a total of 66 primary studies from 2000 to 2016. Mainly, we give an in-depth view of techniques used by each work, how these techniques are evaluated and their main shortcomings. As main results, our review identified (i) the need to improve the quality of the evaluation of existing approaches, (ii) a lack of hybrid solutions to support multiple configuration constraints, and (iii) a need to improve scalability and performance conditions.

Effective BigData-Space Service Selection over Trust and Heterogeneous QoS Preferences

As the number of Cloud services is growing at a tremendous speed, there is an increasing number of service providers offering similar functionalities. Selecting services with user desired non-functional properties (NFPs) becomes of significant importance but triggers a number of Big Data related research issues. First, the selection decision should deal with a large volume of service NFPs data. Second, service selection needs to reflect diverse user preferences, including both qualitative and quantitative ones. Third, the uncertainty of the network and service load leads to high variability in NFPs. Fourth, as the trust values of service NFPs are collected via historic user's feedbacks,it brings the veracity dimension to the NFPs of services. Fifth, multiple and sometimes conflicting decision objectives for optimal service selection should be balanced. An effective service selection mechanism is in demand that can tackle all the above Big Data challenges in an integrated way to handle the highly diverse QoS with significant variability along with the trust related issues giving rise to data veracity. Existing investigations focus on either users’ QoS preferences or their trust concerns but fail to provide a systematic solution to integrate both criteria in the selection process. In this paper, we tackle heterogeneous preference- and trust-based service selection by developing a novel multi-objective optimization approach to make trade-off decision between service's trust value and user's QoS preference to rank candidate Cloud services based on their match degrees with users’ requirements. We conduct extensive experiments to evaluate the effectiveness and efficiency of the proposed approach.

Process Network Models for Embedded System Design Based on the Real-Time BIP Execution Engine

Existing model-based processes for embedded real-time systems support the analysis of various non-functional properties, most notably schedulability, through model checking, simulation or other means. The analysis results are then used for modifying the system's design, so that the expected properties are satisfied. A rigorous model-based design flow differs in that it aims at a system implementation derived from high-level models by applying a sequence of semantics-preserving transformations. Properties established at any design step are preserved throughout the subsequent steps including the executable implementation. We introduce such a design flow using a process network model of computation for application design at a high level, which combines streaming and reactive control processing with task parallelism. The schedulability of the so-called FPPNs (Fixed Priority Process Networks) is well-studied and various solutions have been presented. This article focuses on the design flow's steps for deriving executable implementations on the BIP (Behavior - Interaction - Priority) runtime environment. FPPNs are designed using the TASTE toolset, a convenient architecture description interface. In this way, the developers do not program explicitly low-level real-time OS services and the schedulability properties are guaranteed throughout the design steps by construction. The approach has been validated on the design of a real spacecraft on-board application that has been scheduled for execution on an industrial multicore platform.

Stochastic process algebras and their markovian semantics

There is a long tradition of quantitative modelling in computer and telecommunication systems for performance evaluation and dependability analysis, dating back to the early work of Erlang on telephone exchanges at the beginning of twentieth century [Erlang 1917]. These models are typically stochastic, not because the behaviour of the system under study is inherently random, but because the models usually abstract from data and because interactions with humans are often intrinsic to the system, and both of these give rise to apparently stochastic behaviour. Whilst systems remained of moderate size, models could readily be hand-crafted, and results such as Little's Law were derived and widely-used, for example to optimise job shops [Little 1961]. Much work, like Little's Law, was based on a queueing abstraction, treating the resource in the system as the server of a queue, with users following an appropriate queueing discipline before gaining access to the resource. The more contention there is for the resource, the longer jobs are likely to spend in the queue waiting for access. The queueing paradigm is based on an essentially sequential view of computation and communication, with jobs flowing between resources, completing one task after another. Nevertheless it functioned extremely well until the 1980s, and for many people performance modelling was synonymous with queueing theory. However, the arrival of distributed systems that allowed jobs to access more than one resource at once, and multicast and broadcast communication, broke the assumptions of basic queueing theory making it much harder to carry out quantitative analysis of stochastic systems in order to predict non-functional properties such as performance, availability, reliability and dependability.

A unified algorithm to automatic semantic composition using multilevel workflow orchestration

As a result of state-of-the-art development in service oriented architecture, we need a composition framework and comprehensive algorithm to discover and compose the web services from different environments. In this paper, we present a unified semantic-oriented framework with corresponding algorithm for automatic web service composition that integrates the comprehensive process of modified multistage composition and rigor of web semantics. Our proposed unified algorithm introduces the novel features through modified five stage composition such as transformation of non-functional properties of user requirements to all stages, optimization and semantic validation of abstract workflows using workflow automata, annotating WSDL files with additional ontologies using ontology based service repository, adopting dynamic change of user requirements for discovering candidate services, and selecting most optimal services for concrete composition using non-functional properties are effectively represented. Feasible composition solution obtained for user complex requirements through semantic web service discovery mechanism for discovering and selecting the most suitable service candidates. Furthermore, our unified algorithm can provide a composition solution through wider acceptance of semantics-oriented documents such as web ontology language for services and web service modeling ontology. We evaluate the proposed unified algorithm for automatic generation of composition using our motivating scenario, namely, home loan approval inference process. We also evaluate algorithm for automated and dynamic composition on service repositories of various sizes in increasing the levels of nesting and present the performance results.

Non-functional parameters and automatic generation and publishing for Web service description improvement

The concept of intention is usually addressed only from a service user side. Moreover, the concepts of context and Quality of Service (QoS) are not attributed great importance in the various stages of a Web service life cycle. Consequently, this lack of information in service descriptions leads to a significant semantic loss, which negatively affects the accuracy of their discovery. In order to overcome these problems, we proposed to integrate these nonfunctional properties (context, QoS and intention) within the Web Service descriptions. To automatically generate and publish these descriptions, we propose in this paper a framework called Adaptable Intentional Web Service-Publishing Framework. This framework semantically annotates the OWL-S description by nonfunctional properties. Moreover, we ensure the semantic annotation through an automatic detection method of service intention developed using Natural Language Processing techniques. As for the publication task, we extended the UDDI register so that it encompasses intentional, contextual and QoS information.