Investigation of individual factors impacting the effectiveness of requirements inspections: a replicated experiment

This paper presents a replication of an empirical study regarding the impact of individual factors on the effectiveness of requirements inspections. Experimental replications are important for verifying results and investigating the generality of empirical studies. We utilized the lab package and procedures from the original study, with some changes and additions, to conduct the replication with 69 professional developers in three different companies in Turkey. In general the results of the replication were consistent with those of the original study. The main result from the original study, which is supported in the replication, was that inspectors whose degree is in a field related to software engineering are less effective during a requirements inspection than inspectors whose degrees are in other fields. In addition, we found that Company, Experience, and English Proficiency impacted inspection effectiveness.     

Perspective-based Usability Inspection: An Empirical Validation of Efficacy

Inspection is a fundamental means of achieving software usability. Past research showed that the current usability inspection techniques were rather ineffective. We developed perspective-based usability inspection, which divides the large variety of usability issues along different perspectives and focuses each inspection session on one perspective. We conducted a controlled experiment to study its effectiveness, using a post-test only control group experimental design, with 24 professionals as subjects. The control group used heuristic evaluation, which is the most popular technique for usability inspection. The experimental design and the results are presented, which show that inspectors applying perspective-based inspection not only found more usability problems related to their assigned perspectives, but also found more overall problems. Perspective-based inspection was shown to be more effective for the aggregated results of multiple inspectors, finding about 30% more usability problems for 3 inspectors. A management implication of this study is that assigning inspectors more specific responsibilities leads to higher performance. Internal and external threats to validity are discussed to help better interpret the results and to guide future empirical studies.     

A family of experiments to investigate the effects of groupware for software inspection

It is widely accepted that the inspection of software artifacts can find defects early in the development process and gather information on the quality of the evolving product. However, the inspection process is resource-intensive and involves tedious tasks, such as searching, sorting, and checking. Tool support for inspections can help accelerating these tasks and allows inspectors to concentrate on tasks particularly needing human attention. Only few tools are available for inspections. We have thus developed a set of groupware tools for both individual defect detection and inspection meetings to lower the effort of inspections and to increase their efficiency. This paper presents the Groupware-supported Inspection Process (GrIP) and describes tools for inspecting software requirements. As only little empirical work exists that directly compares paper-based and tool-based software inspection, we conducted a family of experiments in an academic environment to empirically investigate the effect of tool support regarding defect detection and inspection meetings. The main results of our family of experiments regarding individual defect detection are promising: The effectiveness of inspectors and teams is comparable to paper-based inspection without tool support; the inspection effort and defect overlap decreases significantly with tool support, while the efficiency of inspection teams increases considerably. Regarding tool support for inspection meetings the main findings of the experiments are that tool support considerably lowers the meeting effort, supports inspectors in identifying false positives, and reduces the number of true defects lost during a meeting. The number of unidentified false positives is still quite high.     

Visual lobe shape characteristics of experienced industrial inspectors and inexperienced subjects

This article reports research on visual lobe shape differences between experienced industrial inspectors and inexperienced students and the effects of years of inspection experience on lobe‐shape characteristics. Comparison of the visual lobes of students and inspectors showed that lobe roundness of the inspectors was higher than that of the students. Also, marked improvement in lobe roundness and regularity for inspectors was evident in those inspectors who had relatively long experience in inspection work, indicating that daily inspection practice did not seem to be an effective way of improving lobe‐shape characteristics. The increased lobe roundness level did not change, however, even when the inspectors had not performed an inspection job for a long period of time. This finding suggests that the improved lobe‐roundness level could be maintained even without any follow‐up inspection practice. It seems that intensive lobe training rather than inspection practice may be required to improve lobe‐shape characteristics in a short time. No relationship was found between lobe‐shape parameters and the ranked inspection performance of the inspectors, which indicated that, for the inspectors, better search performance may be related more to their better decision making rather than to their higher lobe‐roundness level or inspection speed. © 2010 Wiley Periodicals, Inc.     

Gender issues and computers: college computer science education in Taiwan

This study investigated gender differences for college computer science majors in Taiwan. Subjects were college students enrolled in five universities offering computer science programs. A total of 940 valid questionnaires were collected, including 796 males (85%) and 144 females (15%). Significant gender differences were not found for most of the College Entrance Examination (CEE) scores, prior computer experience and the prediction models of college performance. However, female students achieved significantly higher scores in CEE language component. Females were also found to outperform males in academic achievement at both the high school and college levels, including math courses. The results seem to suggest that, in Taiwan, female students who decided to enroll in the computer science programs might be more confident in their ability to compete with males in this male-dominated field, due to appropriate amount of math discipline and computer experience they gained prior to entering college.     

A collaborative augmented reality annotation tool for the inspection of prefabricated buildings

The inspection of prefabricated buildings involves different stages and tasks such as the collection of measurements, the visual inspection of components and the written annotation of defects. Traditionally, inspectors have documented the process, the kind of defects and the proposed correction measures in paper format, hindering the collaboration with other experts (either simultaneously or asynchronously) and the collection of other types of annotations (e.g. images, 3D elements). In this paper, we present an AR tool designed to aid inspectors during this process. The tool has many benefits, as it allows simultaneously performing a collaborative inspection, taking multitype and geolocated annotations, their monitoring and edition, and performing in situ augmented visualizations. The quantitative and qualitative user evaluation carried out with our tool in a real environment (including usability and satisfaction evaluations) shows the relevance that such a technology might bring to the field and prove that our tool is usable and fulfils most of the inspectors’ expectations.

     

分层次的计算机网络课程体系建设

针对不同专业学生对学习计算机网络知识的需求,我们研究和设计了分层次的计算机网络课程体系。文章提出网络工程专业注重网络设计、分析和研究,计算机科学与技术类专业侧重网络基本理论和组网技术,全校其他专业侧重网络基础知识和因特网应用的研究思路;设计针对不同专业、能力和要求的分层次教学大纲,提出"计算机网络理论、技术与应用相融合"的教学方法。     

A comprehensive evaluation of capture-recapture models forestimating software defect content

An important requirement to control the inspection of software artifacts is to be able to decide, based on more objective information, whether the inspection can stop or whether it should continue to achieve a suitable level of artifact quality. A prediction of the number of remaining defects in an inspected artifact can be used for decision making. Several studies in software engineering have considered capture-recapture models to make a prediction. However, few studies compare the actual number of remaining defects to the one predicted by a capture-recapture model on real software engineering artifacts. The authors focus on traditional inspections and estimate, based on actual inspections data, the degree of accuracy of relevant state-of-the-art capture-recapture models for which statistical estimators exist. In order to assess their robustness, we look at the impact of the number of inspectors and the number of actual defects on the estimators' accuracy based on actual inspection data. Our results show that models are strongly affected by the number of inspectors, and therefore one must consider this factor before using capture-recapture models. When the number of inspectors is too small, no model is sufficiently accurate and underestimation may be substantial. In addition, some models perform better than others in a large number of conditions and plausible reasons are discussed. Based on our analyses, we recommend using a model taking into account that defects have different probabilities of being detected and the corresponding Jackknife Estimator. Furthermore, we calibrate the prediction models based on their relative error, as previously computed on other inspections. We identified theoretical limitations to this approach which were then confirmed by the data     

高职计算机类专业文理生源综合素质比较

针对高职计算机类专业实行文理科兼招后综合素质是否存在显著差异的问题,跟踪调研2007级计算机类专业学生(文理科生源)在校3年的综合素质,选择"u检验"方法和Excel软件对调研数据分别进行统计分析。根据调查结果,进一步分析文科生源学生综合素质整体高于理科生源学生的原因。结果显示,高职计算机类专业实行文理科兼招可行,对高职计算机类专业可持续发展有利。     

计算机科学与技术专业学生创新能力的培养分析

现代社会已经步入电子信息科学时代,计算机科学和技术的发展要求学生具有一定的创新能力。作为培养计算机科学与技术专业学生的院校,针对时代的对人才的培养提出的要求,我们可以通过加强对教师资源建设、对专业人才的培养方案做出更符合要求的改革、导师的相关项目引导学生积极参与,此外还可以组织课内外的兴趣小组等相关的措施来提高教学方面的改革,以促进学生的创新能力和创新意识的形成。     

Using track changes and word processor to provide corrective feedback to learners in writing

This study investigated the effect of computer‐mediated corrective feedback types in an English as a foreign language (EFL) intact class over time. The participants were 64 English majors who were assigned randomly into three treatment conditions that gave and received computer‐mediated corrective feedback while writing (track changes, word processor, and track changes and word processor) and one control group that neither gave nor received writing corrective feedback. Students sat to a pre‐test (week 1), immediate post‐test (week 8) and delayed post‐test (week 12) in writing. Results showed decrease in mean error and mean feedback in students' writing performance related to correcting 11 major error types on immediate and delayed post‐tests, indicating that there was a significant effect for feedback type in favour of the group that used a combination of track changes and word processor. There was also a significant effect for the computer‐mediated corrective feedback over the control group. Moreover, results showed that both mean error and mean feedback decreased significantly from pre‐test to post‐test (week 1–week 8), indicating that overall, there was a significant change over time.     

A sensor planning system for automated headlamp lens inspection

Usually, the automated systems for quality control based on computer vision have been centered on the design of algorithms for detecting different types of defects. Nevertheless, the issues related to planning suitable sensor poses for the inspection task have received less attention. In addition, the applications where a vision sensor can only sample a portion of a part from a single viewpoint, the sensor planning problem becomes critically important. This is the case of the automated inspection of vehicle headlamp lens, that due to its geometry and dimensions, requires multiple sensor poses to observe the whole part. Moreover, the customer requirements that define the maximum defect size should also be taken into account in the inspection process.This paper presents a vision sensor planning system applied to the quality control of headlamp lenses. The system uses the lens CAD, a vision sensor model and the customer requirements, included through a fuzzy approach, to achieve an optimal set of viewpoints. To compute the number and distribution of the viewpoints, a genetic algorithm is used. Experimental results demonstrate the effectiveness of the sensor planning system on commercial lenses.     

Eight maxims for software inspectors

Software inspections are an intensely people‐centric activity. Even though this is routinely recognized in industry, much of the research focuses on inspection mechanics. During three years of inspection experiments, even though the main purpose of the experiments was to investigate the effectiveness of a particular technique, the inspectors involved provided broad comments on many other aspects of inspections. Their comments were collected and organized into themes. These themes are presented here as a set of maxims that cover all the topics that the inspectors felt were important as they endeavoured to do good inspections. Copyright © 2004 John Wiley & Sons, Ltd.     

Evaluating capture-recapture models with two inspectors

Capture-recapture (CR) models have been proposed as an objective method for controlling software inspections. CR models were originally developed to estimate the size of animal populations. In software, they have been used to estimate the number of defects in an inspected artifact. This estimate can be another source of information for deciding whether the artifact requires a reinspection to ensure that a minimal inspection effectiveness level has been attained. Little evaluative research has been performed thus far on the utility of CR models for inspections with two inspectors. We report on an extensive Monte Carlo simulation that evaluated capture-recapture models suitable for two inspectors assuming a code inspections context. We evaluate the relative error of the CR estimates as well as the accuracy of the reinspection decision made using the CR model. Our results indicate that the most appropriate capture-recapture model for two inspectors is an estimator that allows for inspectors with different capabilities. This model always produces an estimate (i.e., does not fail), has a predictable behavior (i.e., works well when its assumptions are met), will have a relatively high decision accuracy, and will perform better than the default decision of no reinspections. Furthermore, we identify the conditions under which this estimator will perform best     

The performance of the N-fold requirement inspection method

Faults in system requirements can be very harmful. It is therefore often required that the inspection achieves a high fault detection ratio (FDR). To achieve this, a large number of inspectors is required. Large teams are known to be inefficient. Therefore, the N-fold requirements inspection method divides the inspectors intoN small efficient teams. All temas inspect the same requirements document. Experiments with both information and real-time systems demonstrate that the different teams detect different faults such that they achieve together a higher FDR value. The analysis suggests that the FDR is primarily a function of the level of expertise of the inspectors and of the number of teams. A quite simple probabilistic model that matches the experimental results enables the prediction of the FDR as a function of these two parameters. A diagram based on the model enables a fast estimation of the FDR and of the most effective number of inspections teams money-wise. The model may also be employed for measuring the efficiency of requirement inspection methods.     

A method of evaluating inspector's performance differences and job requirements

Large individual differences are among the most consistent findings in the study of industrial inspection. From a statistical point of view, a large proportion of the variation in inspection performance is attributed to this individual factor. Based on the conclusions obtained from the review of previous papers, the relations between subjects' cognitive factors and inspection performance were shown to be in need of further exploration. The objective of this paper is to introduce a method that can explore this large proportion of variation by concentrating on individuals' cognitive attributes and how each contributes to the efficiency and effectiveness of inspection performance. In an experiment, three inspection tasks and 11 cognitive pretests were included. Through factor analysis and Pearson correlations, some significant predictive relationships were found. The findings can be applied to set up selection criteria as well as training schemes for industrial inspectors.     

高职医学专业计算机课程体系改革研究与实践

针对目前医疗卫生行业信息化以及医学信息化对医学人才的需求,在研究医学专业对计算机课程需求特点的基础上,结合作者对计算机课程体系多年的改革实践,并借鉴兄弟院校的经验,提出针对高职医学专业计算机课程体系改革的系列措施。     

Anomaly detection of defects on concrete structures with the convolutional autoencoder

This paper reports the application of deep learning for implementing the anomaly detection of defects on concrete structures, so as to facilitate the visual inspection of civil infrastructure. A convolutional autoencoder was trained as a reconstruction-based model, with the defect-free images, to rapidly and reliably detect defects from the large volume of image datasets. This training process was in the unsupervised mode, with no label needed, thereby requiring no prior knowledge and saving an enormous amount of time for label preparation. The built anomaly detector favors minimizing the reconstruction errors of defect-free images, which renders high reconstruction errors of defects, in turn, detecting the location of defects. The assessment shows that the proposed anomaly detection technique is robust and adaptable to defects on wide ranges of scales. Comparison was also made with the segmentation results produced by other automatic classical methods, revealing that the results made by the anomaly map outperform other segmentation methods, in terms of precision, recall, F₁ measure and F₂ measure, without severe under- and over-segmentation. Further, instead of merely being a binary map, each pixel of the anomaly map is represented by the anomaly score, which acts as a risk indicator for alerting inspectors, wherever defects on concrete structures are detected.     

Evaluation of best system performance: Human,automated, and hybrid inspection systems

Recently, 100% inspection with automated systems has seen more frequent application than traditional sampling inspection with human inspectors. Nevertheless, humans still outperform machines in most attribute inspection tasks. Because neither humans nor automation can achieve superior inspection system performance, hybrid inspection systems where humans work cooperatively with machines merit study. In response to this situation, this research was conducted to evaluate three of the following different inspection systems: (1) a human inspection system, (2) a computer search/human decision‐making inspection system, and (3) a human/computer share search/decision‐making inspection system. Results from this study showed that the human/computer share search/decision‐making system achieve the best system performance, suggesting that both should be used in the inspection tasks rather than either alone. Furthermore, this study looked at the interaction between human inspectors and computers, specifically the effect of system response bias on inspection quality performance. These results revealed that the risky system was the best in terms of accuracy measures. Although this study demonstrated how recent advances in computer technology have modified previously prescribed notions about function allocation alternatives in a hybrid inspection environment, the adaptability of humans was again demonstrated, indicating that they will continue to play a vital role in future hybrid systems. © 2003 Wiley Periodicals, Inc. Hum Factors Man 13: 137–152, 2003.