2012 19th Asia-Pacific Software Engineering Conference最新文献

{"title":"Semi-static Detection of Runtime Type Errors in Component-Based Java Programs","authors":"Xiaowei Zhou, Wen-bo Zhang, Jianhua Zhang","doi":"10.1109/APSEC.2012.46","DOIUrl":"https://doi.org/10.1109/APSEC.2012.46","url":null,"abstract":"The using of multiple custom class loaders in component-based Java programs may lead to more runtime type errors. These errors can happen at various program statements and may be wrapped in different types of exceptions by JVM, therefore posing difficulties for dealing with them. Traditional static analysis approaches only consider static types and thus cannot detect many of them. We propose a semi-static approach based on points-to analysis and dynamically gathered behavior information of Java class loaders to detect runtime type errors in component-based Java programs without running them. We also implement a prototype tool for OSGi-based programs, where OSGi is a typical Java component framework.","PeriodicalId":364411,"journal":{"name":"2012 19th Asia-Pacific Software Engineering Conference","volume":"34 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116667248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Empirical Study on Improving Severity Prediction of Defect Reports Using Feature Selection","authors":"Cheng-Zen Yang, Chun-Chi Hou, Wei-Chen Kao, Ing-Xiang Chen","doi":"10.1109/APSEC.2012.144","DOIUrl":"https://doi.org/10.1109/APSEC.2012.144","url":null,"abstract":"In software maintenance, severity prediction on defect reports is an emerging issue obtaining research attention due to the considerable triaging cost. In the past research work, several text mining approaches have been proposed to predict the severity using advanced learning models. Although these approaches demonstrate the effectiveness of predicting the severity, they do not discuss the problem of how to find the indicators in good quality. In this paper, we discuss whether feature selection can benefit the severity prediction task with three commonly used feature selection schemes, Information Gain, Chi-Square, and Correlation Coefficient, based on the Multinomial Naive Bayes classification approach. We have conducted empirical experiments with four open-source components from Eclipse and Mozilla. The experimental results show that these three feature selection schemes can further improve the predication performance in over half the cases.","PeriodicalId":364411,"journal":{"name":"2012 19th Asia-Pacific Software Engineering Conference","volume":"155 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127354699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient Modelling of Embedded Software Systems and their Formal Verification","authors":"V. Estivill-Castro, R. Hexel, D. Rosenblueth","doi":"10.1109/APSEC.2012.21","DOIUrl":"https://doi.org/10.1109/APSEC.2012.21","url":null,"abstract":"We propose vectors of finite-state machines whose transitions are labeled by formulas of a common-sense logic as the modeling tool for embedded systems software. We have previously shown that this methodology is very efficient in producing succinct and clear models (e.g., in contrast to plain finite-state machines, Petri nets, or Behavior Trees). We show that we can capture requirements precisely and that we can simulate and validate the models. We can, therefore, directly apply Model-Driven Engineering and deploy the models into software for diverse platforms with full tractability of requirements. Moreover, the sequential semantics of our vector of finite-state machines enables model-checking, formally establishing the correctness of the model. Finally, our approach facilitates systematic Failure Modes and Effects Analysis (FMEA) for diverse target platforms. We demonstrate the effectiveness of our methodology with several examples widely discussed in the software engineering literature and compare this with other approaches, showing that we can prove more properties, and that some claims about verification in such approaches have been exaggerated or are incomplete.","PeriodicalId":364411,"journal":{"name":"2012 19th Asia-Pacific Software Engineering Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123223472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PBDDR: Probe-Based Deadlock Detection and Recovery Strategy for Component-Based Systems","authors":"Chen Li, Linpeng Huang, Luxi Chen, Weichao Luo, Xu Li","doi":"10.1109/APSEC.2012.33","DOIUrl":"https://doi.org/10.1109/APSEC.2012.33","url":null,"abstract":"Correctness is a critical requirement for software systems and one of the key factors in correctness is that the system be deadlock-free. In this paper, we present a Probe-Based Deadlock Detection and Recovery (PBDDR) strategy for Component-based System (CBS) which brings four contributions. First, we define a formal semantic model by using Communicating Sequential Processes (CSP) to abstract interaction behavior for statically analyzing deadlock. Second, we propose a Deadlock Detection Algorithm (DDA) to find deadlock loops in a CBS. Third, we consider two qualities of concern, Timeliness (i.e., response time) and DLC (i.e., How many deadlock loops that a component involved in). Then we give a Deadlock Recovery Algorithm (DRA) to evaluate and replace the component to solve the deadlock problem based on above quality concerns. Finally, we implement our approach using the Arch Studio tool. Experimental results show that our approach has reasonable performance.","PeriodicalId":364411,"journal":{"name":"2012 19th Asia-Pacific Software Engineering Conference","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123019455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing the Representativeness of Open Source Projects in Empirical Software Engineering Studies","authors":"Hao Zhong, Ye Yang, J. Keung","doi":"10.1109/APSEC.2012.36","DOIUrl":"https://doi.org/10.1109/APSEC.2012.36","url":null,"abstract":"BACKGROUND: Software engineering researchers have carried out many empirical studies on open source software (OSS) projects to understand the OSS phenomenon, and to develop better software engineering techniques. Many of these studies typically use only a few successful projects as study subjects. Recently, these studies have received criticisms and challenges on their representativeness on OSS projects. AIM: First, we aim to examine to what extent data extracted from successful projects are different from data extracted from the majority. If data extracted from successful projects are quite different from data extracted from the majority, approaches that are effective on successful projects may not be effective in general. Second, we aim to examine whether successful OSS projects are representative to the whole population of OSS. If they are not, conclusions that are drawn from only successful projects may reflect the OSS phenomenon partially. METHODOLOGY: We analyzed 11, 684 OSS projects that are hosted on Source Forge. When researchers select subjects, they typically select successful projects that are attractive to both users and developers. Considering this preference, we clustered these projects into four categories based their attractiveness to users and developers. Here, we use the K-means clustering technique to produce combined result. Furthermore, we selected eight indicators that are used in many existing studies (e.g., team sizes), and compared indicators that are extracted from different categories to investigate to what degree they are different. RESULT: For the first research aim, the result shows that 66.1% projects are under developing projects, 14.7% projects are user-preference projects, 14.2% projects are developer-preference projects, and only 5.0% projects are considered successful. For the second research aim, the result shows that all the eight analyzed indicators are highly unbalanced with the gamma distribution. Furthermore, the result reveals that users and developers of Source Forge have different perceptions on the development status defined by Source Forge. CONCLUSION: We conclude that successful projects are not representative to the whole population of OSS, and data extracted from successful projects are quite different from data extracted from the majority. The result implies that conclusions drawn from only a few successful projects may be challenged. This work is important to allow researchers to refine conclusions of existing studies, and to better understand and to carefully select OSS project subjects for their future empirical experiments.","PeriodicalId":364411,"journal":{"name":"2012 19th Asia-Pacific Software Engineering Conference","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115910906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Case Study on Specifying Quality Requirements Using a Quality Model","authors":"K. Lochmann, Daniel Méndez Fernández, S. Wagner","doi":"10.1109/APSEC.2012.57","DOIUrl":"https://doi.org/10.1109/APSEC.2012.57","url":null,"abstract":"Quality requirements are an often neglected part of requirements engineering. If specified at all, they tend to be either too abstract or very technical and without a rationale. In this paper, we evaluate a quality requirements approach, which makes use of activity-based quality models. To this end, we conduct a comparative case study at Siemens in which we compare the requirements resulting from applying our quality model with the requirements previously used in the same environment. The results indicate an improvement of the requirements regarding, e.g., structured ness and trace ability, but also that the productivity perceived by the industry participants could not be increased. The study thus gives first insights into strengths and limitations of using a quality model in an industrial requirements engineering process.","PeriodicalId":364411,"journal":{"name":"2012 19th Asia-Pacific Software Engineering Conference","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131965094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diffusion of Software Features: An Exploratory Study","authors":"Ferdian Thung, D. Lo, Lingxiao Jiang","doi":"10.1109/APSEC.2012.139","DOIUrl":"https://doi.org/10.1109/APSEC.2012.139","url":null,"abstract":"New features are frequently proposed in many software libraries. These features include new methods, classes, packages, etc. These features are utilized in many open source and commercial software systems. Some of these features are adopted very quickly, while others take a long time to be adopted. Each feature takes much resource to develop, test, and document. Library developers and managers need to decide what feature to prioritize and what to develop next. As a first step to aid these stakeholders, we perform an exploratory study on the diffusion or rate of adoption of features in Java Development Kit (JDK) library. Our empirical study proposes such questions as how many new features are adopted by client applications, how long it takes for a new feature to spread to various software products, what features are diffused quickly, and what features are diffused widely. We perform an exploratory study with new features in Java Development Kit (JDK, from version 1.3 to 1.6) and provide empirical findings to answer the above research questions.","PeriodicalId":364411,"journal":{"name":"2012 19th Asia-Pacific Software Engineering Conference","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132462481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Metrics for Measuring the Quality of Modularization of Scala Systems","authors":"Miguel Nicolas Gubitosi, B. Muddu, A. Asadullah","doi":"10.1109/APSEC.2012.138","DOIUrl":"https://doi.org/10.1109/APSEC.2012.138","url":null,"abstract":"As part of software maintenance, having systems in well modular way brings in lot of advantages. In this regard, measuring quality of modularization of a given system becomes very important. In literature today, there are metrics measuring software modularization quality from object oriented and imperative programming styles, but the literature does not have much work on a functional programming perspective. We propose a set of metrics particularly designed for the Scala programming language. In this process we review the guiding principles for proper software modularization applied to concepts like functional purity, first order functions and multiple inheritance, which are present in many modern programming languages. We test our set of metrics on a set of open source software.","PeriodicalId":364411,"journal":{"name":"2012 19th Asia-Pacific Software Engineering Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130020076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Empirical Study of Reliability Growth of Open versus Closed Source Software through Software Reliability Growth Models","authors":"Najeeb Ullah, M. Morisio","doi":"10.1109/APSEC.2012.80","DOIUrl":"https://doi.org/10.1109/APSEC.2012.80","url":null,"abstract":"The purpose of this study is to analyze the reliability growth of Open Source Software (OSS) versus software developed in-house (i.e. Closed Source Software, CSS) using Software Reliability Growth Model. This study uses 22 datasets containing failure data of CSS and 18 datasets containing defect data of OSS projects. The failure data are modelled by eight SRGM (Musa Okumoto, Inflection S-Shaped, Goel Okumoto, Delayed S-Shaped, Logistic, Gompertz, Yamada Exponential, and Generalized Goel Model). These models are chosen due to their widespread use. The results can be summarized as follows All selected SRGM fit to defect data of the OSS projects in the same manner as that of CSS. OSS reliability grows similarly to that of CSS. Musa Okumoto and Inflection S-Shaped perform well for CSS, while for OSS Inflection S-Shaped and Gompertz are good performers. SRGM can be used for reliability characterization of OSS projects.","PeriodicalId":364411,"journal":{"name":"2012 19th Asia-Pacific Software Engineering Conference","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134192926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Overview of Software Defect Density: A Scoping Study","authors":"S. M. A. Shah, M. Morisio, Marco Torchiano","doi":"10.1109/APSEC.2012.93","DOIUrl":"https://doi.org/10.1109/APSEC.2012.93","url":null,"abstract":"Context: Defects are an ineludible component of software, Defect Density (DD) - defined as the number of defects divided by size - is often used as a related measure of quality. Project managers and researchers alike would benefit a lot from overview DD figures from software projects, the former for decision making the latter for state-of-the-practice assessment. Objective: In this paper, we collect and aggregate DD figures published in literature, in addition we characterize DD as a function of different project factors in terms of central tendency and dispersion. The factors considered include development mode -open vs. closed source-, programming language, size, and age. Results: We were able to identify 19 papers reporting defect density figures concerning 109 software projects. The mean DD for the studied sample of projects is 7.47 post release defects per thousand lines of code (KLoC), the median is 4.3 with a standard deviation of 7.99. Development mode, is characterized by statistically meaningful different DD, the same for Java vs. C. Besides, in the studied sample large projects exhibited lower DD than medium and small projects. Conclusion: The study is a first step in collecting and analyzing DD figures for the purpose of characterizing one important aspect of software quality. These figures can be used both by researchers and project managers interested to evaluate their projects. Further work is needed to extend the data set and to identify predictors of defect density.","PeriodicalId":364411,"journal":{"name":"2012 19th Asia-Pacific Software Engineering Conference","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117326026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}