An empirical, path-oriented approach to software analysis and testing

Dynamic impact analysis based on program executions has shown promise in aiding tasks in the life cycle of large-scale systems. Dynamic impact analysis techniques have shown to produce more precise results than static impact analysis [1]. However, current dynamic impact analysis techniques lack important features such as analysis of dependency among program entities and consideration of object-oriented programs ' features. Thus they may produce imprecise results. In this paper, we present a precise dynamic impact analysis approach for object-oriented programs. This approach considers the characteristics of object- oriented programs and performs dependency analysis which may potentially reduce the impact sets by eliminating elements that do not have dependency on the changed elements. Even though our discussion in this paper is based on Java <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">TM</sup> programming language, this approach can be carried out in a language independent manner for broader applications.

A great amount of fault-based testing strategies have been proposed to generate test cases for detecting certain types of faults in Boolean specifications. However, most of the previous studies on these strategies were focused on the Boolean expressions in the disjunctive normal form (DNF), even the irredundant DNF (IDNF)-little work has been conducted to comprehensively investigate their performance on general Boolean specifications. In this study, we conducted a series of experiments to evaluate and compare 18 fault-based testing strategies using over 4000 randomly generated fault-seeded Boolean expressions. In the experiments, a testing strategy is regarded as effective and efficient if it can detect most of the seeded faults using a small number of test cases. Our experimental results show that if a testing strategy is highly effective and efficient when testing the Boolean expressions in the IDNF, it also shows high effectiveness and efficiency on general Boolean expressions. It is found that one family of fault-based testing strategies, namely MUMCUT, normally deliver the best performance among all the 18 strategies. Our study provides an in-depth understanding and insight of fault-based testing for general Boolean expressions.

In comparison with tests conducted on real Li-ion batteries, Battery Management System (BMS) tests conducted on a Hardware-In-the-Loop (HIL) battery simulator may be more cost and time effective, more flexible and traceable, easier to reproduce and safer beyond the normal range of operation. This is particularly the case of tests at early stages in the development process or during fault simulation. However, the use of a HIL battery simulator requires the development of software (SW) and strategies for testing. While the possibilities are immense, it should be noted that the greater the level of complexity of the tests, the higher the demands for ad hoc development of SW and strategies. With regard to the latter, there is not a universal definition and there are different points of view. Therefore different strategies may be followed, which can be classified into many different ways according to the testing level, methods or processes. The aim of this paper is both to introduce the theoretical principles of BMS testing and to present a practical approach to develop ad hoc SW and strategies for BMS testing at system level on a commercial HIL simulator.

Fault-based testing without the need of oracles

The hanging net shielding system, employing a suspended cage-type enclosed structure to restrict the high-voltage transmission wire, has seen increasingly widespread application in transmission line crossing construction. However, the lack of a comprehensive dynamic analysis methodology has limited the standardization of its design and usage. In this investigation, a systematical dynamic modeling and analysis procedure of the hanging net shielding system is proposed based on the absolute nodal coordinate formulation (ANCF). The carrier cable, slings and transmission wire are discretized by the ANCF cable element. The spatial flexible beam–beam contact model and the assumption of a single contact area are adopted to perform the contact searching between the transmission wire and the horizontal pulley. The system dynamics analysis equation is assembled and solved by generalized alpha method. A full-scale model is simulated for the transmission wire impact condition and the variation history of the tension in carrier cable and the sling cable are given. The peak value of the tension in carrier cable could be 110 kN, while the largest tension in sling cable is 9 kN. Results could help to ensure construction safety, shorten the design cycle of the protection system and reduce the development cost at the same time.

With the access of various types of intermittent energy, distribution network begins to face many problems, such as the enhancement of uncertainty, the increasement of power disturbance and the change of dynamic characteristics for continuous changing power flow. In this context, how to properly assess the voltage risk in distribution network and identify the potential critical risk items that can cause adverse effects on voltage has become a significant challenge. This paper uses dynamic power flow analysis based on the fusion of cyber and physics to reveal the complex properties of distribution network operations. A risk assessment model based on former dynamic power flow is also discussed for real-time assessment of voltage risk in distribution network. When the network is under warning state, the voltage optimization adjustment method will be used for voltage recovery based on the types of voltage risk and state transition rules for safe operation. This method can guarantee an efficient operation for distributed generations and improve the reliability of power supply.

Impact analysis determines the effects that program entities of interest, or changes to them, may have on the rest of the program for software measurement, maintenance, and evolution tasks. Dynamic impact analysis could be one major approach to impact analysis that computes smaller impact setsthan static alternatives for concrete sets of executions. However, existing dynamic approaches often produce impact sets that are too large to be useful, hindering their adoption in practice. To address this problem, we propose to exploit static program dependencies to drastically prune false-positive impacts that are not exercised by the set of executions utilized by the analysis, via hybrid dependence approximation. Further, we present a novel dynamic impact analysis called Diver which leverages both the information provided by the dependence graph and method-execution events to identify runtimemethod-level dependencies, hence dynamic impact sets, much more precisely without reducing safety and at acceptable costs. We evaluate Diver on ten Java subjects of various sizes and application domains against both arbitrary queries covering entire programs and practical queries based on changes actually committed by developers to actively evolving software repositories. Our extensive empirical studies show that Diver can significantly improve the precision of impact prediction, with 100-186 percent increase, with respect to a representative existing alternative thus provide a far more effective option for dynamic impact prediction. Following a similar rationale to Diver, we further developed and evaluated an online dynamic impact analysis called DiverOnline which produces impact sets immediately upon the termination of program execution. Our results show that compared to the offline approach, for the same precision, the online approach can reduce the time by 50 percent on average for answering all possible queries in the given program at once albeit at the price of possibly significant increase in runtime overhead. For users interested in one specific query only, the online approach may compute the impact set for that query during runtime without much slowing down normal program operation. Further, the online analysis, which does not incur any space cost beyond the static-analysis phase, may be favored against the offline approach when trace storage and/or related file-system resource consumption becomes a serious challenge or even stopper for adopting dynamic impact prediction. Therefore, the online and offline analysis together offer complementary options to practitioners accommodating varied application/task scenarios and diverse budget constraints.

Travelling salesman problem (TSP) is one of the famous discrete optimization problems. Due to its NP-completeness, the exact methods are not found till now. Here we use a nearest neighbor method to search the approximations with a frequency graph. The frequency graph is computed with a set of local optimal paths derived from a weighted graph. The frequencies on the edges represent the number of edges emulated from the set of local optimal paths. We believe the local optimal paths have more intersections of edges with the best circuit than the general paths do with it. Hence the edges with big frequencies may be included by the best circuit. To reduce the complexity, we use the local optimal paths with four vertices to compute the frequency graphs. These local optimal paths are computed with a four-vertex-three-line inequality. After a frequency graph is computed, we use a nearest neighbor method to find the approximations with it. The experimental results illustrate the nearest neighbor method is able to find the better approximations with the frequency graphs than those with the weighted graphs.

How will China's steel demand develop under the investment-driven patterns? Integrating extended input-output model with dynamic steel flow analysis

Sequential Optimization of Paths in Directed Graphs Relative to Different Cost Functions

Fault-based testing has been proven to be a cost effective testing technique for software logics and rules expressed in Boolean expressions. It can guarantee the elimination of common faults without exhaustive testing. However, average software testing practitioners may not have in-depth knowledge on Boolean algebra and complex logic derivations required to apply existing fault-based testing techniques. In this paper, a dynamic fault visualization tool has been proposed. This tool allows its user to visualize fault-based testing and prioritize test inputs with a simple greedy method. The performance evaluation of this tool has been done on Boolean expressions extracted from a real life aviation tool. The results show that it can achieve significant performance improvements compared to ordinary sequential order test execution and existing static technique. The proposed visualization tool could also identify possible faults to guide the debugging process.

Adaptive software testing is the counterpart of adaptive control in software testing. It means that software testing strategy should be adjusted online by using the testing data collected during software testing as our understanding of the software under test improves. Previous studies on adaptive testing rely on a simplified Controlled Markov Chain (CMC) model for software testing which employs several unrealistic assumptions. In this paper we propose a new adaptive software testing approach in the context of an improved CMC model which aims to eliminate such threats to validity. A new set of basic assumptions on the software testing process is proposed and several unrealistic assumptions are replaced by more common situations in real life software testing. The methodology of a new adaptive testing strategy is also developed and implemented. Experimental data are collected to demonstrate the effectiveness of the new methodology.

Optimal and adaptive testing for software reliability assessment

Conventional techniques to analyze probe-type formation test data have been based on the principle of pressure transient analysis or on the equations of steady-state flow. The typical techniques are those associated with the spherical and cylindrical flow regimes and with steady-state drawdown solutions. Due to the intrinsic features of probe-type formation tests, such as the flow line storage effect, variable rate history, and short test duration, these techniques in practice have proven difficult to apply or inappropriate. A better suited analysis is based on the simultaneous analysis of both pressure transient and formation rate data. One technique proposed earlier is the dynamic flow analysis with the Formation Rate Analysis (FRA1,2). FRA is based on the linear relationship between the measured pressure and the calculated sand-face formation rate during the test. In some complex flow conditions, however, non-linear relationships have been observed in actual probe tests. This paper investigates what conditions could cause the non-linear relationship, propose how to analyze such tests, and provide guidelines for repeat tests. To this end, a number of simulated probe-type tests performed under different practical test conditions are used to generate, typical non-linear pressure versus formation rate plots. These non-linear plots may resemble a skewed ellipse, an upward pointing "hockey stick", a downward pointing hockey stick, or a skewed "figure-8". Actual field tests are combined with simulation test data to investigate the conditions that could give rise to such nonlinear plots. Analytical solutions are used to justify the findings in this paper. A number of effects are investigated, including low permeability (mobility), high compressibility, high permeability anisotropy, permeability heterogeneity, upper and lower shale boundaries near the probe, duration of the drawdown, test operation parameters, and plugging and cleaning-up processes. The methodology and findings presented in this paper can enhance the post-job analysis of formation tests from challenging environments. Based on these findings, test operation parameters can be optimized for repeated tests in real time if the first test reveals pecial non-linear dynamic flow.

eHealth interventions are becoming a part of standard care, with software solutions increasingly created for patients and health care providers. Testing of eHealth software is important to ensure that the software realizes its goals. Software testing, which is comprised of alpha and beta testing, is critical to establish the effectiveness and usability of the software. In this viewpoint, we explore existing practices for testing software in health care settings. We scanned the literature using search terms related to eHealth software testing (eg, "health alpha testing," "eHealth testing," and "health app usability") to identify practices for testing eHealth software. We could not identify a single standard framework for software testing in health care settings; some articles reported frameworks, while others reported none. In addition, some authors misidentified alpha testing as beta testing and vice versa. There were several different objectives (ie, testing for safety, reliability, or usability) and methods of testing (eg, questionnaires, interviews) reported. Implementation of an iterative strategy in testing can introduce flexible and rapid changes when developing eHealth software. Further investigation into the best approach for software testing in health care settings would aid the development of effective and useful eHealth software, particularly for novice eHealth software developers.