An object-oriented high-level design-based class cohesion metric

ContextClass cohesion is an important object-oriented software quality attribute. Assessing class cohesion during the object-oriented design phase is one important way to obtain more comprehensible and maintainable software. In practice, assessing and controlling cohesion in large systems implies measuring it automatically. One issue with the few existing cohesion metrics targeted at the high-level design phase is that they are not based on realistic assumptions and do not fulfill expected mathematical properties.ObjectiveThis paper proposes a High-Level Design (HLD) class cohesion metric, which is based on realistic assumptions, complies with expected mathematical properties, and can be used to automatically assess design quality at early stages using UML diagrams.MethodThe notion of similarity between pairs of methods and pairs of attribute types in a class is introduced and used as a basis to introduce a novel high-level design class cohesion metric. The metric considers method–method, attribute–attribute, and attribute–method direct and transitive interactions. We validate this Similarity-based Class Cohesion (SCC) metric theoretically and empirically. The former includes a careful study of the mathematical properties of the metric whereas the latter investigates, using four open source software systems and 10 cohesion metrics, whether SCC is based on realistic assumptions and whether it better explains the presence of faults, from a statistical standpoint, than other comparable cohesion metrics, considered individually or in combination.ResultsResults confirm that SCC is based on clearly justified theoretical principles, relies on realistic assumptions, and is an early indicator of quality (fault occurrences).ConclusionIt is concluded that SCC is both theoretically valid and supported by empirical evidence. It is a better alternative to measure class cohesion than existing HLD class cohesion metrics.     

An approach to experimental evaluation of real-time fault-tolerantdistributed computing schemes

A test-based approach to the evaluation of fault-tolerant distributed-computing schemes is discussed. The approach is based on experimental incorporation of system structuring and design techniques into real-time distributed computing testbeds centered around tightly coupled microcomputer networks. The effectiveness of this approach has been experimentally confirmed. Primary advantages of the testbed-based approach include the relatively high accuracy of the data obtained on timing and logical complexity, as well as the relatively high degree of assurance that can be obtained on the practical effectiveness of the scheme evaluated. Various design issues encountered in the course of establishing the basic microcomputer network testbed facilities are discussed, along with their augmentation to support some experiments. The shortcomings of the testbeds that have been recognized are also discussed together with the desired extensions of the testbeds. Some of the desired extensions are beyond the state-of-the-art in microcomputer network implementation     

An initial industrial evaluation of interactive search-based testing for embedded software

Search-based software testing promises the ability to generate and evaluate large numbers of test cases at minimal cost. From an industrial perspective, this could enable an increase in product quality without a matching increase in the time and effort required to do so.Search-based software testing, however, is a set of quite complex techniques and approaches that do not immediately translate into a process for use with most companies.For example, even if engineers receive the proper education and training in these new approaches, it can be hard to develop a general fitness function that covers all contingencies. Furthermore, in industrial practice, the knowledge and experience of domain specialists are often key for effective testing and thus for the overall quality of the final software system. But it is not clear how such domain expertise can be utilized in a search-based system.This paper presents an interactive search-based software testing (ISBST) system designed to operate in an industrial setting and with the explicit aim of requiring only limited expertise in software testing. It uses SBST to search for test cases for an industrial software module, while also allowing domain specialists to use their experience and intuition to interactively guide the search.In addition to presenting the system, this paper reports on an evaluation of the system in a company developing a framework for embedded software controllers. A sequence of workshops provided regular feedback and validation for the design and improvement of the ISBST system. Once developed, the ISBST system was evaluated by four electrical and system engineers from the company (the ‘domain specialists’ in this context) used the system to develop test cases for a commonly used controller module. As well as evaluating the utility of the ISBST system, the study generated interaction data that were used in subsequent laboratory experimentation to validate the underlying search-based algorithm in the presence of realistic, but repeatable, interactions.The results validate the importance that automated software testing tools in general, and search-based tools, in particular, can leverage input from domain specialists while generating tests. Furthermore, the evaluation highlighted benefits of using such an approach to explore areas that the current testing practices do not cover or cover insufficiently.     

Zen-ReqOptimizer: a search-based approach for requirements assignment optimization

At early phases of a product development lifecycle of large scale Cyber-Physical Systems (CPSs), a large number of requirements need to be assigned to stakeholders from different organizations or departments of the same organization for review, clarification and checking their conformance to standards and regulations. These requirements have various characteristics such as extents of importance to the organization, complexity, and dependencies between each other, thereby requiring different effort (workload) to review and clarify. While working with our industrial partners in the domain of CPSs, we discovered an optimization problem, where an optimal solution is required for assigning requirements to various stakeholders by maximizing their familiarity to assigned requirements, meanwhile balancing the overall workload of each stakeholder. In this direction, we propose a fitness function that takes into account all the above-mentioned factors to guide a search algorithm to find an optimal solution. As a pilot experiment, we first investigated four commonly applied search algorithms (i.e., GA, (1 + 1) EA, AVM, RS) together with the proposed fitness function and results show that (1 + 1) EA performs significantly better than the other algorithms. Since our optimization problem is multi-objective, we further empirically evaluated the performance of the fitness function with six multi-objective search algorithms (CellDE, MOCell, NSGA-II, PAES, SMPSO, SPEA2) together with (1 + 1) EA (the best in the pilot study) and RS (as the baseline) in terms of finding an optimal solution using an real-world case study and 120 artificial problems of varying complexity. Results show that both for the real-world case study and the artificial problems (1 + 1) EA achieved the best performance for each single objective and NSGA-II achieved the best performance for the overall fitness. NSGA-II has the ability to solve a wide range of problems without having their performance degraded significantly and (1 + 1) EA is not fit for problems with less than 250 requirements Therefore we recommend that, if a project manager is interested in a particular objective then (1 + 1) EA should be used; otherwise, NSGA-II should be applied to obtain optimal solutions when putting the overall fitness as the first priority.     

An approach to usability evaluation of e-learning applications

Despite recent advances of electronic technologies in e-learning, a consolidated evaluation methodology for e-learning applications is not available. The evaluation of educational software must consider its usability and more in general its accessibility, as well as its didactic effectiveness. This work is a first step towards the definition of a methodology for evaluating e-learning applications. Specific usability attributes capturing the peculiar features of these applications are identified. A preliminary user study involving a group of e-students, observed during their interaction with an e-learning application in a real situation, is reported. Then, the proposal is put forward to adapt to the e-learning domain a methodology for systematic usability evaluation, called SUE. Specifically, evaluation patterns are proposed that are able to drive the evaluators in the analysis of an e-learning application.     

An approach to ergonomics evaluation of hand tools

Based on current knowledge of cumulative trauma disorders in the hand and forearm, related to the use of hand tools, an analysis was undertaken of variables to be considered in ergonomics evaluation of hand tools. Measurement methods were developed and an evaluation station was implemented. Measurement methods are physical, physiological or psychophysical. They focus on the tool, and on the effect of typical use of the tool on the operator. The evaluation station serves as a resource in the development, selection, and testing of tools for a given purpose.     

An approach to evaluation of hierarchical systems performance

An approach to assessment of performance of hierarchical systems with simple subordination is developed with regard to moment characteristics of sequences of random sums. Translated from Kibernetika i Sistemnyi Analiz, No. 4, pp. 70–79, July–August, 2000.     

An integrated search-based approach for automatic testing from extended finite state machine (EFSM) models

Context

The extended finite state machine (EFSM) is a modelling approach that has been used to represent a wide range of systems. When testing from an EFSM, it is normal to use a test criterion such as transition coverage. Such test criteria are often expressed in terms of transition paths (TPs) through an EFSM. Despite the popularity of EFSMs, testing from an EFSM is difficult for two main reasons: path feasibility and path input sequence generation. The path feasibility problem concerns generating paths that are feasible whereas the path input sequence generation problem is to find an input sequence that can traverse a feasible path.

Objective

While search-based approaches have been used in test automation, there has been relatively little work that uses them when testing from an EFSM. In this paper, we propose an integrated search-based approach to automate testing from an EFSM.

Method

The approach has two phases, the aim of the first phase being to produce a feasible TP (FTP) while the second phase searches for an input sequence to trigger this TP. The first phase uses a Genetic Algorithm whose fitness function is a TP feasibility metric based on dataflow dependence. The second phase uses a Genetic Algorithm whose fitness function is based on a combination of a branch distance function and approach level.

Results

Experimental results using five EFSMs found the first phase to be effective in generating FTPs with a success rate of approximately 96.6%. Furthermore, the proposed input sequence generator could trigger all the generated feasible TPs (success rate = 100%).

Conclusion

The results derived from the experiment demonstrate that the proposed approach is effective in automating testing from an EFSM.     

A complexity metric approach to software quality measurement

Traditional statistical quality control for dealing with quality variation during mass production is not appropriate for software quality assessment. Therefore determination and measurement of user desirable software attributes become a subject of research interest. In this paper, software attributes are classified into attributes of subjective judgment, attributes based on complexity metrics, and attributes with rigorous mathematical definition. Methods of measuring those attributes are proposed in the paper. To measure the quality of software as a whole, model that integrates qualitative software attributes and quantitative complexity metrics is also given. Finally, distribution of software life cycle costs in relation to the weighting of software quality attributes is discussed.     

On the evaluation of the Bunch search-based software modularization algorithm

The first part of this paper describes an automatic reverse engineering process to infer subsystem abstractions that are useful for a variety of software maintenance activities. This process is based on clustering the graph representing the modules and module-level dependencies found in the source code into abstract structures not in the source code called subsystems. The clustering process uses evolutionary algorithms to search through the enormous set of possible graph partitions, and is guided by a fitness function designed to measure the quality of individual graph partitions. The second part of this paper focuses on evaluating the results produced by our clustering technique. Our previous research has shown through both qualitative and quantitative studies that our clustering technique produces good results quickly and consistently. In this part of the paper we study the underlying structure of the search space of several open source systems. We also report on some interesting findings our analysis uncovered by comparing random graphs to graphs representing real software systems.     

An intelligent approach to supplier evaluation in automotive sector

During the process of supplier evaluation, selecting the best desirable supplier is one of the most critical problems of companies since improperly selected suppliers may cause losing time, cost and market share of a company. For this multiple-criteria decision making selection problem, in this paper, a fuzzy extension of analytic network process (ANP), which uses uncertain human preferences as input information in the decision-making process, is applied since conventional methods such as analytic hierarchy process cannot accommodate the variety of interactions, dependencies and feedback between higher and lower level elements. The resulting fuzzy ANP enhances the potential of the conventional ANP for dealing with imprecise and uncertain human comparison judgments. In short, in this paper, an intelligent approach to supplier selection problem through fuzzy ANP is proposed by taking into consideration quantitative and qualitative elements to evaluate supplier alternatives, and a case study in automotive sector is presented.     

Extension and experimental evaluation of an event-based state-feedback approach

Event-based control aims at reducing the traffic load of the communication network used to implement feedback control. The communication is invoked only if an event indicates that the control error exceeds a certain threshold. This paper extends a state-feedback approach to event-based control published recently and proves that the extended control loop asymptotically reaches the set-point for arbitrary constant disturbances. This control method is applied to a thermofluid process to illustrate the main characteristics of event-based control and to evaluate the closed-loop performance. Experiments with a pilot plant show that the event-based control scheme is robust against severe model uncertainties.     

An experimental evaluation of ontology-based user profiles

In recent years, a number of research works have been carried out to improve the information retrieval process by exploiting external knowledge, e.g. by employing ontologies. Even though ontologies seem to be a promising technique to improve the retrieval process, hardly any study has been performed to evaluate the use of ontologies over a longer time period to model user interests. In this work we introduce an ontology based video recommender system that exploits implicit relevance feedback to capture users’ evolving information needs. The system exploits a generic ontology to organise users’ interests. We evaluate the recommendations by performing a user-centred multiple time-series study where participants were asked to include the system into their daily news gathering routine. The results of this study suggest that the system can be successfully employed to improve personal information seeking tasks in news domain.     

An integrated approach to concept evaluation in a new product development

A new product development (NPD) process can be thought as a comprehensive process in which the design is progressively detailed through a series of phases. At the end of each phase a design review is held to approve the design and release or not it to the next level. As one of these phases, concept selection aiming to select the most appropriate concept for further development, is conducted earlier in the process. As the further development progresses on a selected concept, it becomes more difficult to make design changes in terms of cost and schedule dimensions, and therefore, selecting the best concept among a set of available alternatives has been an important issue for companies. On the other hand, in the presence of many alternatives and selection criteria, the selection problem becomes a multiple-criteria decision making concept selection problem. To solve this problem, in this work, an integrated approach bringing two popular methods together: the modified technique for order preference by similarity to ideal solution (TOPSIS) and the analytical network process (ANP). The ANP method is used to determine the relative weights of a set of quantitative and qualitative evaluation criteria, as the modified TOPSIS method utilized to rank competing concept alternatives. In addition, a real example is presented to demonstrate the effectiveness and applicability of the proposed approach for potential practitioners and readers.     

Optimization of expression syntax: An experimental approach

Several alternative ways of defining the syntax of expressions in Pascal are compared. Based on experimental observations, measures of syntactic efficiency are calculated for each variant of the syntax. An optimal variant is determined for each such measure.     

An augmented beam search-based algorithm for the circular open dimension problem

In this paper, we discuss the circular open dimension problem (CODP); that is a problem of the cutting/packing family. In CODP, we are given an initial strip of fixed width W and unlimited length, as well as a finite set N of n circular pieces C_i of known radius r_i,i ∈ N. The objective is to search for a global optimum corresponding to the minimum length of the initial strip containing the n pieces. We propose an augmented algorithm for solving the CODP which combines a beam search, a binary search and the well-known multi-start strategy. In addition, in order to increase the efficiency of the algorithm, we incorporate a strategy based on the separate beams instead of the pooled ones. The performance of the proposed algorithm is evaluated on a set of benchmark instances composed of a group taken from the literature and another group of randomly generated instances. The results show that the proposed algorithm is able to improve several best known solutions of the literature and it remains competitive for the new generated ones.     

An effective hybrid harmony search-based algorithm for solving multidimensional knapsack problems

This study presents an effective hybrid algorithm based on harmony search (HHS) for solving multidimensional knapsack problems (MKPs). In the proposed HHS algorithm, a novel harmony improvisation mechanism is developed with the modified memory consideration rule and the global-best pitch adjustment scheme to enhance the global exploration. A parallel updating strategy is employed to enrich the harmony memory diversity. To well balance the exploration and the exploitation, the fruit fly optimization (FFO) scheme is integrated as a local search strategy. For solving MKPs, binary strings are used to represent solutions and two repair operators are applied to guarantee the feasibility of the solutions. The HHS is calibrated based on the Taguchi method of design-of-experiment. Extensive numerical investigations based on well-known benchmark instances are conducted. The comparative evaluations indicate the HHS is much more effective than the existing HS and FFO variants in solving MKPs.