A Model to Estimate First-Order Mutation Coverage from Higher-Order Mutation Coverage

The test suite is essential for fault detection during software development. First-order mutation coverage is an accurate metric to quantify the quality of the test suite. However, it is computationally expensive. Hence, the adoption of this metric is limited. In this study, we address this issue by proposing a realistic model able to estimate first-order mutation coverage using only higher-order mutation coverage. Our study shows how the estimation evolves along with the order of mutation. We validate the model with an empirical study based on 17 open-source projects.Comment: 2016 IEEE International Conference on Software Quality, Reliability, and Security. 9 page

Evaluating Random Mutant Selection at Class-Level in Projects with Non-Adequate Test Suites

Mutation testing is a standard technique to evaluate the quality of a test suite. Due to its computationally intensive nature, many approaches have been proposed to make this technique feasible in real case scenarios. Among these approaches, uniform random mutant selection has been demonstrated to be simple and promising. However, works on this area analyze mutant samples at project level mainly on projects with adequate test suites. In this paper, we fill this lack of empirical validation by analyzing random mutant selection at class level on projects with non-adequate test suites. First, we show that uniform random mutant selection underachieves the expected results. Then, we propose a new approach named weighted random mutant selection which generates more representative mutant samples. Finally, we show that representative mutant samples are larger for projects with high test adequacy.Comment: EASE 2016, Article 11 , 10 page

Experimental investigation on materials and lubricants for sliding-vane air compressors

Abstract. Positive-displacement compressors and, among them, sliding-vane rotary machines are widely used in the compressed air sector. As in many other industrial fields, the efficient utilization of energy has become a major goal also in this sector. The aim of the present activity is the experimental investigation on the influence of two vanes materials (cast iron and aluminium with anodized surface) and of four commercial lubricants (characterized by different formulations and additives concentrations) on the performance of a mid-capacity sliding-vane rotary compressor in a number of operating pressures. The performance is identified by both the volume flow rate and the absorbed mechanical power, evaluated according to the international standard ISO 5167 and ISO 1217. The campaign indicates that the considered lubricants do not affect appreciably the volumetric flow rate. On the other hand, the specific lubricants determine a variation of about 1% of the mechanical power for both materials, while the specific material a variation between 0.9% and 2.6%. The best performance is achieved by aluminium vanes and a synthetic poly-α-olefin lubricant

Time evolution and distribution analysis of software bugs from a complex network perspective

Successful software systems are constantly under development. Since they have to be updated when new features are introduced, bug are fixed and the system is kept up to date, they require a continuous maintenance. Among these activities the bug fixing is one of themost relevant, because it is determinant for software quality. Unfortunately, software houses have limited time and developers to address all these issues before the product delivery. For this reason, an efficient allocation of these resources is required to obtain the quality required by the market. The keyword for a correct management of software product process is measure. As De-Marco states “you cannot control what you cannot measure”, and this thesis is mainly devoted to this aspect. This dissertation bears with software measures related to bug proneness and distribution analysis of software bugs. The aim is to describe the bug occurrence phenomena, identify useful metrics related to software bugs proneness and finally to characterize how bug population is distributed and evolve, discussing also the model able to explain this evolution. Studying the relationship between code evolution and bug distribution or bug-proneness, we foresee which software structure will come out. Thus, this research provides information and guidelines tomanagers, helping them to plan, schedule activities and allocate resources, during software development

Context-Aware Performance Benchmarking of a Fleet of Industrial Assets

Industrial assets are instrumented with sensors, connected and continuously monitored. The collected data, generally in form of time-series, is used for corrective and preventive maintenance. More advanced exploitation of this data for very diverse purposes, e.g. identifying underperformance, operational optimization or predictive maintenance, is currently an active area of research. The general methods used to analyze the time-series lead to models that are either too simple to be used in complex operational contexts or too difficult to be generalized to the whole fleet due to their asset-specific nature. Therefore, we have conceived an alternative methodology allowing to better characterize the operational context of an asset and quantify the impact on its performance. The proposed methodology allows to benchmark and profile fleet assets in a context-aware fashion, is applicable in multiple domains (even without ground truth). The methodology is evaluated on real-world data coming from a fleet of wind turbines and compared to the standard approach used in the domain. We also illustrate how the asset performance (in terms of energy production) is influenced by the operational context (in terms of environmental conditions). Moreover, we investigate how the same operational context impacts the performance of the different assets in the fleet and how groups of similarly behaving assets can be determined

An empirical study of social networks metrics in object-oriented software

We study the application to object-oriented software of new metrics, derived from Social Network Analysis. Social Networks metrics, as for instance, the EGO metrics, allow to identify the role of each single node in the information flow through the network, being related to software modules and their dependencies. These metrics are compared with other traditional software metrics, like the Chidamber-Kemerer suite, and software graph metrics. We examine the empirical distributions of all the metrics, bugs included, across the software modules of several releases of two large Java systems, Eclipse and Netbeans. We provide analytical distribution functions suitable for describing and studying the observed distributions. We study also correlations among metrics and bugs. We found that the empirical distributions systematically show fat-tails for all the metrics. Moreover, the various metric distributions look very similar and consistent across all system releases and are also very similar in both the studied systems. These features appear to be typical properties of these software metrics

Modeling And Testing The Thermal Effect Of Lubricating Oil Sprayed In Sliding-Vane Air Compressors Using Pressure-Swirl Nozzles

Positive-displacement compressors and, among them, sliding-vane machines are widely used in the compressed air sector. As in many other industrial fields, the efficient utilization of energy has become a major goal also in this sector. The aim of the present activity is the numerical modeling and the experimental testing of the positive thermal effect due to spraying the lubricating oil inside sliding-vane air compressors using pressure-swirl nozzles. The benefits of proper oil atomization in positive-displacement compressors have been documented already by a number of investigations (Singh and Bowman, 1986; Stosic et al., 1988; Fujiwara and Osada, 1995; Valenti et al., 2013; Cipollone et al. 2014). The novelty of this work resides in the extension of a previous model to describe more accurately the quantity and the diameter distribution of the droplets generated by the nozzles and, consequently, to predict more precisely the heat transfer occurring between the liquid and the gas phase within a compression chamber. The model is applied to a pre-commercial mid-size compressor that is equipped with a number of pressure-swirl nozzles. The numerical data are validated successfully against the measurements of the pressure as a function of the angular position. The results indicate that the specific energy of compression is appreciable reduced with respect to the case of an adiabatic process. The model is applied here to a sliding-vane compressor, but it is general in nature and can be promptly modified for another kind of machine. It may be used also for optimizing type, number and position of the nozzles in order to further improve the performances of air compressors