Pub Date : 2018-09-01DOI: 10.1109/ICSME.2018.00081
Veit Frick, Christoph Wedenig, M. Pinzger
A number of approaches and tools exist that extract and visualize the changes between two versions of a file and thereby help developers to understand them. DiffViz is an interactive visualization tool that visualizes the changes independent from the differencing algorithm. It supports, but is not limited to, a granularity on the level of abstract syntax trees. Furthermore, it provides several new features, such as node matching and the mini-map, to navigate and analyze the changes. A demo of the installation and example usage of the tool is available here: https://youtu.be/RF93ey9GYoc
{"title":"DiffViz: A Diff Algorithm Independent Visualization Tool for Edit Scripts","authors":"Veit Frick, Christoph Wedenig, M. Pinzger","doi":"10.1109/ICSME.2018.00081","DOIUrl":"https://doi.org/10.1109/ICSME.2018.00081","url":null,"abstract":"A number of approaches and tools exist that extract and visualize the changes between two versions of a file and thereby help developers to understand them. DiffViz is an interactive visualization tool that visualizes the changes independent from the differencing algorithm. It supports, but is not limited to, a granularity on the level of abstract syntax trees. Furthermore, it provides several new features, such as node matching and the mini-map, to navigate and analyze the changes. A demo of the installation and example usage of the tool is available here: https://youtu.be/RF93ey9GYoc","PeriodicalId":6572,"journal":{"name":"2018 IEEE International Conference on Software Maintenance and Evolution (ICSME)","volume":"33 1","pages":"705-709"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73706555","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}
Pub Date : 2018-09-01DOI: 10.1109/ICSME.2018.00052
J. Lecerf, J. Brant, T. Goubier, Stéphane Ducasse
Empowering software engineers often requires to let them write code transformations. However existing automated or tool-supported approaches force developers to have a detailed knowledge of the internal representation of the underlying tool. While this knowledge is time consuming to master, the syntax of the language, on the other hand, is already well known to developers and can serve as a strong foundation for pattern matching. Pattern languages with metavariables (that is variables holding abstract syntax subtrees once the pattern has been matched) have been used to help programmers define program transformations at the language syntax level. The question raised is then the engineering cost of metavariable support. Our contribution is to show that, with a GLR parser, such patterns with metavariables can be supported by using a form of runtime reflexivity on the parser internal structures. This approach allows one to directly implement such patterns on any parser generated by a parser generation framework, without asking the pattern writer to learn the AST structure and node types. As a use case for that approach we describe the implementation built on top of the SmaCC (Smalltalk Compiler Compiler) GLR parser generator framework. This approach has been used in production for source code transformations on a large scale. We will express perspectives to adapt this approach to other types of parsing technologies.
{"title":"A Reflexive and Automated Approach to Syntactic Pattern Matching in Code Transformations","authors":"J. Lecerf, J. Brant, T. Goubier, Stéphane Ducasse","doi":"10.1109/ICSME.2018.00052","DOIUrl":"https://doi.org/10.1109/ICSME.2018.00052","url":null,"abstract":"Empowering software engineers often requires to let them write code transformations. However existing automated or tool-supported approaches force developers to have a detailed knowledge of the internal representation of the underlying tool. While this knowledge is time consuming to master, the syntax of the language, on the other hand, is already well known to developers and can serve as a strong foundation for pattern matching. Pattern languages with metavariables (that is variables holding abstract syntax subtrees once the pattern has been matched) have been used to help programmers define program transformations at the language syntax level. The question raised is then the engineering cost of metavariable support. Our contribution is to show that, with a GLR parser, such patterns with metavariables can be supported by using a form of runtime reflexivity on the parser internal structures. This approach allows one to directly implement such patterns on any parser generated by a parser generation framework, without asking the pattern writer to learn the AST structure and node types. As a use case for that approach we describe the implementation built on top of the SmaCC (Smalltalk Compiler Compiler) GLR parser generator framework. This approach has been used in production for source code transformations on a large scale. We will express perspectives to adapt this approach to other types of parsing technologies.","PeriodicalId":6572,"journal":{"name":"2018 IEEE International Conference on Software Maintenance and Evolution (ICSME)","volume":"12 1","pages":"426-436"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87843228","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}
Pub Date : 2018-09-01DOI: 10.1109/ICSME.2018.00076
M. Leemans, Wil M.P. van der Aalst, M. Brand, R. Schiffelers, L. Lensink
Over the last decades, the complexity of high-tech systems, and the software systems controlling them, has increased considerably. In practice, it is hard to keep knowledge and documentation of these ever-evolving software systems up-to-date with their actual realization; we are dealing with legacy software. Clearly, this lack of knowledge, insight, and understanding is more and more becoming a critical issue. Process mining provides an interesting opportunity to improve understanding and analyze software behavior based on observations from the system on the run. However, a concrete software process analysis methodology was lacking. This paper 1) discusses a software process analysis case study at ASML, a large high-tech company, and, based on the lessons learned, 2) presents a concrete methodology for analyzing software processes. The presented methodology actively includes the system under analysis and is based on practical experiences in applying process mining on industrial-scale legacy software.
{"title":"Software Process Analysis Methodology – A Methodology Based on Lessons Learned in Embracing Legacy Software","authors":"M. Leemans, Wil M.P. van der Aalst, M. Brand, R. Schiffelers, L. Lensink","doi":"10.1109/ICSME.2018.00076","DOIUrl":"https://doi.org/10.1109/ICSME.2018.00076","url":null,"abstract":"Over the last decades, the complexity of high-tech systems, and the software systems controlling them, has increased considerably. In practice, it is hard to keep knowledge and documentation of these ever-evolving software systems up-to-date with their actual realization; we are dealing with legacy software. Clearly, this lack of knowledge, insight, and understanding is more and more becoming a critical issue. Process mining provides an interesting opportunity to improve understanding and analyze software behavior based on observations from the system on the run. However, a concrete software process analysis methodology was lacking. This paper 1) discusses a software process analysis case study at ASML, a large high-tech company, and, based on the lessons learned, 2) presents a concrete methodology for analyzing software processes. The presented methodology actively includes the system under analysis and is based on practical experiences in applying process mining on industrial-scale legacy software.","PeriodicalId":6572,"journal":{"name":"2018 IEEE International Conference on Software Maintenance and Evolution (ICSME)","volume":"118 3 1","pages":"665-674"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88821205","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}
Pub Date : 2018-09-01DOI: 10.1109/ICSME.2018.00046
Chris Mills, Jevgenija Pantiuchina, Esteban Parra, G. Bavota, S. Haiduc
Text Retrieval (TR) has been widely used to support many software engineering tasks, including bug localization (i.e., the activity of localizing buggy code starting from a bug report). Many studies show TR's effectiveness in lowering the manual effort required to perform this maintenance task; however, the actual usefulness of TR-based bug localization has been questioned in recent studies. These studies discuss (i) potential biases in the experimental design usually adopted to evaluate TRbased bug localization techniques and (ii) their poor performance in the scenario when they are needed most: when the bug report, which serves as the de facto query in most studies, does not contain localization hints (e.g., code snippets, method names, etc.) Fundamentally, these studies raise the question: do bug reports provide sufficient information to perform TR-based localization? In this work, we approach that question from two perspectives. First, we investigate potential biases in the evaluation of TR-based approaches which artificially boost the performance of these techniques, making them appear more successful than they are. Second, we analyze bug report text with and without localization hints using a genetic algorithm to derive a near-optimal query that provides insight into the potential of that bug report for use in TR-based localization. Through this analysis we show that in most cases the bug report vocabulary (i.e., the terms contained in the bug title and description) is all we need to formulate effective queries, making TR-based bug localization successful without supplementary query expansion. Most notably, this also holds when localization hints are completely absent from the bug report. In fact, our results suggest that the next major step in improving TR-based bug localization is the ability to formulate these near-optimal queries.
{"title":"Are Bug Reports Enough for Text Retrieval-Based Bug Localization?","authors":"Chris Mills, Jevgenija Pantiuchina, Esteban Parra, G. Bavota, S. Haiduc","doi":"10.1109/ICSME.2018.00046","DOIUrl":"https://doi.org/10.1109/ICSME.2018.00046","url":null,"abstract":"Text Retrieval (TR) has been widely used to support many software engineering tasks, including bug localization (i.e., the activity of localizing buggy code starting from a bug report). Many studies show TR's effectiveness in lowering the manual effort required to perform this maintenance task; however, the actual usefulness of TR-based bug localization has been questioned in recent studies. These studies discuss (i) potential biases in the experimental design usually adopted to evaluate TRbased bug localization techniques and (ii) their poor performance in the scenario when they are needed most: when the bug report, which serves as the de facto query in most studies, does not contain localization hints (e.g., code snippets, method names, etc.) Fundamentally, these studies raise the question: do bug reports provide sufficient information to perform TR-based localization? In this work, we approach that question from two perspectives. First, we investigate potential biases in the evaluation of TR-based approaches which artificially boost the performance of these techniques, making them appear more successful than they are. Second, we analyze bug report text with and without localization hints using a genetic algorithm to derive a near-optimal query that provides insight into the potential of that bug report for use in TR-based localization. Through this analysis we show that in most cases the bug report vocabulary (i.e., the terms contained in the bug title and description) is all we need to formulate effective queries, making TR-based bug localization successful without supplementary query expansion. Most notably, this also holds when localization hints are completely absent from the bug report. In fact, our results suggest that the next major step in improving TR-based bug localization is the ability to formulate these near-optimal queries.","PeriodicalId":6572,"journal":{"name":"2018 IEEE International Conference on Software Maintenance and Evolution (ICSME)","volume":"14 1","pages":"381-392"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88634401","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}
Pub Date : 2018-09-01DOI: 10.1109/ICSME.2018.00090
Emad Aghajani
Software developers often do not possess the knowledge needed to understand a piece of code at hand, and the lack of code comments and outdated documentation exacerbates the problem. Asking for the help of colleagues, browsing the official documentation, or accessing online resources, such as Stack Overflow, can clearly help in this "code comprehension" activity that, however, still remains highly time-consuming and is not always successful. Enhancing this process has been addressed in different studies under the subject of automatic documentation of software artifacts. For example, "recommender systems" have been designed with the goal of retrieving and suggesting relevant pieces of information (e.g., Stack Overflow discussions) for a given piece of code inspected in an IDE. However, these techniques rely on limited contextual information, mainly solely source code. Our goal is to build a context-aware proactive recommender system supporting the code comprehension process. The system must be able to understand the context, consider the developer's profile, and help her by generating pieces of documentation at whatever granularity is required, e.g., going from summarizing the responsibilities implemented in a subsystem, to explaining how two classes collaborate to implement a functionality, down to documenting a single line of code. Generated documentation will be tailored for the current context (e.g., the task at hand, the developer's background knowledge, the history of interactions). In this paper we present our first steps toward our goal by introducing the ADANA project, a framework which generates fine-grained code comments for a given piece of code.
{"title":"Context-Aware Software Documentation","authors":"Emad Aghajani","doi":"10.1109/ICSME.2018.00090","DOIUrl":"https://doi.org/10.1109/ICSME.2018.00090","url":null,"abstract":"Software developers often do not possess the knowledge needed to understand a piece of code at hand, and the lack of code comments and outdated documentation exacerbates the problem. Asking for the help of colleagues, browsing the official documentation, or accessing online resources, such as Stack Overflow, can clearly help in this \"code comprehension\" activity that, however, still remains highly time-consuming and is not always successful. Enhancing this process has been addressed in different studies under the subject of automatic documentation of software artifacts. For example, \"recommender systems\" have been designed with the goal of retrieving and suggesting relevant pieces of information (e.g., Stack Overflow discussions) for a given piece of code inspected in an IDE. However, these techniques rely on limited contextual information, mainly solely source code. Our goal is to build a context-aware proactive recommender system supporting the code comprehension process. The system must be able to understand the context, consider the developer's profile, and help her by generating pieces of documentation at whatever granularity is required, e.g., going from summarizing the responsibilities implemented in a subsystem, to explaining how two classes collaborate to implement a functionality, down to documenting a single line of code. Generated documentation will be tailored for the current context (e.g., the task at hand, the developer's background knowledge, the history of interactions). In this paper we present our first steps toward our goal by introducing the ADANA project, a framework which generates fine-grained code comments for a given piece of code.","PeriodicalId":6572,"journal":{"name":"2018 IEEE International Conference on Software Maintenance and Evolution (ICSME)","volume":"8 1","pages":"727-731"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88720232","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}
Pub Date : 2018-09-01DOI: 10.1109/ICSME.2018.00035
Stefan Fischer, L. Linsbauer, Alexander Egyed, R. Lopez-Herrejon
Robust and effective support for the detection and management of software features and their interactions is crucial for many development tasks but has proven to be an elusive goal despite extensive research on the subject. This is especially challenging for variable systems where multiple variants of a system and their features must be collectively considered. Here an important issue is the typically large number of feature interactions that can occur in variable systems. We propose a method that computes, from a set of known source code level interactions of n features, the relevant interactions involving n+1 features. Our method is based on the insight that, if a set of features interact, it is much more likely that these features also interact with additional features, as opposed to completely different features interacting. This key insight enables us to drastically prune the space of potential feature interactions to those that will have a true impact at source code level. This substantial space reduction can be leveraged by analysis techniques that are based on feature interactions (e.g Combinatorial Interaction Testing). Our observation is based on eight variable systems, implemented in Java and C, totaling over nine million LoC, with over seven thousand feature interactions.
{"title":"Predicting Higher Order Structural Feature Interactions in Variable Systems","authors":"Stefan Fischer, L. Linsbauer, Alexander Egyed, R. Lopez-Herrejon","doi":"10.1109/ICSME.2018.00035","DOIUrl":"https://doi.org/10.1109/ICSME.2018.00035","url":null,"abstract":"Robust and effective support for the detection and management of software features and their interactions is crucial for many development tasks but has proven to be an elusive goal despite extensive research on the subject. This is especially challenging for variable systems where multiple variants of a system and their features must be collectively considered. Here an important issue is the typically large number of feature interactions that can occur in variable systems. We propose a method that computes, from a set of known source code level interactions of n features, the relevant interactions involving n+1 features. Our method is based on the insight that, if a set of features interact, it is much more likely that these features also interact with additional features, as opposed to completely different features interacting. This key insight enables us to drastically prune the space of potential feature interactions to those that will have a true impact at source code level. This substantial space reduction can be leveraged by analysis techniques that are based on feature interactions (e.g Combinatorial Interaction Testing). Our observation is based on eight variable systems, implemented in Java and C, totaling over nine million LoC, with over seven thousand feature interactions.","PeriodicalId":6572,"journal":{"name":"2018 IEEE International Conference on Software Maintenance and Evolution (ICSME)","volume":"42 1","pages":"252-263"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88287458","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}
Pub Date : 2018-09-01DOI: 10.1109/ICSME.2018.00041
Shengtao Yue, Qingwei Sun, Jun Ma, Xianping Tao, Chang Xu, Jian Lu
With the rapid development of mobile devices, Android applications (apps) are universally used. However, attackers repackage Android apps and release them to the markets for illegal purposes, which brings great threats to the Android ecosystem. To leverage the popularity of original apps, they keep similar software behaviors to confuse app users. Furthermore, repackaged apps can be obfuscated or encrypted to avoid being detected. Besides, hybrid mobile apps, built by combining web technology and native elements, are becoming a preferred choice for developers. The structure of hybrid apps differs a lot from that of native apps which would raise great challenges to repackaging detection. Existing works still have some limitations in detecting repackaging from obfuscated and encrypted apps. Besides, few of them can deal with hybrid apps. In this paper, we proposed an approach based on the app UI regions extracted from app's runtime UI traces. We also implement a tool named RegionDroid based on the approach. We apply RegionDroid to tree datasets with totally 369 apps. It successfully finds all the 98 obfuscated or encrypted repackaged pairs in dataset S1. It also shows good credibility in distinguishing another 114 commercial apps in dataset S2. We also test our approach in dataset S3 with 157 hybrid apps by comparing them pairwisely and the false positive rate is 0.016%.
{"title":"RegionDroid: A Tool for Detecting Android Application Repackaging Based on Runtime UI Region Features","authors":"Shengtao Yue, Qingwei Sun, Jun Ma, Xianping Tao, Chang Xu, Jian Lu","doi":"10.1109/ICSME.2018.00041","DOIUrl":"https://doi.org/10.1109/ICSME.2018.00041","url":null,"abstract":"With the rapid development of mobile devices, Android applications (apps) are universally used. However, attackers repackage Android apps and release them to the markets for illegal purposes, which brings great threats to the Android ecosystem. To leverage the popularity of original apps, they keep similar software behaviors to confuse app users. Furthermore, repackaged apps can be obfuscated or encrypted to avoid being detected. Besides, hybrid mobile apps, built by combining web technology and native elements, are becoming a preferred choice for developers. The structure of hybrid apps differs a lot from that of native apps which would raise great challenges to repackaging detection. Existing works still have some limitations in detecting repackaging from obfuscated and encrypted apps. Besides, few of them can deal with hybrid apps. In this paper, we proposed an approach based on the app UI regions extracted from app's runtime UI traces. We also implement a tool named RegionDroid based on the approach. We apply RegionDroid to tree datasets with totally 369 apps. It successfully finds all the 98 obfuscated or encrypted repackaged pairs in dataset S1. It also shows good credibility in distinguishing another 114 commercial apps in dataset S2. We also test our approach in dataset S3 with 157 hybrid apps by comparing them pairwisely and the false positive rate is 0.016%.","PeriodicalId":6572,"journal":{"name":"2018 IEEE International Conference on Software Maintenance and Evolution (ICSME)","volume":"34 1","pages":"323-333"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88316467","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}
Pub Date : 2018-09-01DOI: 10.1109/icsme.2018.00097
{"title":"Publisher's Information","authors":"","doi":"10.1109/icsme.2018.00097","DOIUrl":"https://doi.org/10.1109/icsme.2018.00097","url":null,"abstract":"","PeriodicalId":6572,"journal":{"name":"2018 IEEE International Conference on Software Maintenance and Evolution (ICSME)","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88382896","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}
Pub Date : 2018-09-01DOI: 10.1109/ICSME.2018.00042
I. Malavolta, R. Verdecchia, Bojana Filipović, M. Bruntink, P. Lago
Context. Android is the largest mobile platform today, with thousands of apps published and updated in the Google Play store everyday. Maintenance is an important factor in Android apps lifecycle, as it allows developers to constantly improve their apps and better tailor them to their user base. Goal. In this paper we investigate the evolution of various maintainability issues along the lifetime of Android apps. Method. We designed and conducted an empirical study on 434 GitHub repositories containing open, real (i.e., published in the Google Play store), and actively maintained Android apps. We statically analyzed 9,945 weekly snapshots of all apps for identifying their maintainability issues over time. We also identified maintainability hotspots along the lifetime of Android apps according to how their density of maintainability issues evolves over time. More than 2,000 GitHub commits belonging to identified hotspots have been manually categorized to understand the context in which maintainability hotspots occur. Results. Our results shed light on (i) how often various types of maintainability issues occur over the lifetime of Android apps, (ii) the evolution trends of the density of maintainability issues in Android apps, and (iii) an in-depth characterization of development activities related to maintainability hotspots. Together, these results can help Android developers in (i) better planning code refactoring sessions, (ii) better planning their code review sessions (e.g., steering the assignment of code reviews), and (iii) taking special care of their code quality when performing tasks belonging to activities highly correlated with maintainability issues. We also support researchers by objectively characterizing the state of the practice about maintainability of Android apps. Conclusions. Independently from the type of development activity, maintainability issues grow until they stabilize, but are never fully resolved.
{"title":"How Maintainability Issues of Android Apps Evolve","authors":"I. Malavolta, R. Verdecchia, Bojana Filipović, M. Bruntink, P. Lago","doi":"10.1109/ICSME.2018.00042","DOIUrl":"https://doi.org/10.1109/ICSME.2018.00042","url":null,"abstract":"Context. Android is the largest mobile platform today, with thousands of apps published and updated in the Google Play store everyday. Maintenance is an important factor in Android apps lifecycle, as it allows developers to constantly improve their apps and better tailor them to their user base. Goal. In this paper we investigate the evolution of various maintainability issues along the lifetime of Android apps. Method. We designed and conducted an empirical study on 434 GitHub repositories containing open, real (i.e., published in the Google Play store), and actively maintained Android apps. We statically analyzed 9,945 weekly snapshots of all apps for identifying their maintainability issues over time. We also identified maintainability hotspots along the lifetime of Android apps according to how their density of maintainability issues evolves over time. More than 2,000 GitHub commits belonging to identified hotspots have been manually categorized to understand the context in which maintainability hotspots occur. Results. Our results shed light on (i) how often various types of maintainability issues occur over the lifetime of Android apps, (ii) the evolution trends of the density of maintainability issues in Android apps, and (iii) an in-depth characterization of development activities related to maintainability hotspots. Together, these results can help Android developers in (i) better planning code refactoring sessions, (ii) better planning their code review sessions (e.g., steering the assignment of code reviews), and (iii) taking special care of their code quality when performing tasks belonging to activities highly correlated with maintainability issues. We also support researchers by objectively characterizing the state of the practice about maintainability of Android apps. Conclusions. Independently from the type of development activity, maintainability issues grow until they stabilize, but are never fully resolved.","PeriodicalId":6572,"journal":{"name":"2018 IEEE International Conference on Software Maintenance and Evolution (ICSME)","volume":"19 1","pages":"334-344"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89562949","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}
Pub Date : 2018-09-01DOI: 10.1109/ICSME.2018.00030
A. Armaly, Paige Rodeghero, Collin McMillan
Blind programmers use a screen reader to read code aloud. Screen readers force blind programmers to read code sequentially one line at a time. In contrast, sighted programmers are able to skim visually to the most important code areas, assisted by syntax highlighting. However, there is a place where there is a widely adopted approach to skimming a structured document: the web. Modern screen readers employ what is known as a virtual cursor to navigate structural information on webpages such as HTML heading tags. These tags can indicate different sections and subsections in the structure of a page. We harness the existing familiarity of blind computer users with this interface in our approach which we call AudioHighlight. AudioHighlight renders the code inside a web view, either as part of the Eclipse IDE or as a web service. It places HTML heading tags on the structural elements of a source file such as classes, functions and control flow statements. We compare AudioHighlight to the state of the art in code skimming represented by a previous code skimming approach called StructJumper. We also compare to the state of practice in reading code on the web as represented by GitHub. We found that AudioHighlight increased the quality and speed of code comprehension as compared to both approaches.
{"title":"AudioHighlight: Code Skimming for Blind Programmers","authors":"A. Armaly, Paige Rodeghero, Collin McMillan","doi":"10.1109/ICSME.2018.00030","DOIUrl":"https://doi.org/10.1109/ICSME.2018.00030","url":null,"abstract":"Blind programmers use a screen reader to read code aloud. Screen readers force blind programmers to read code sequentially one line at a time. In contrast, sighted programmers are able to skim visually to the most important code areas, assisted by syntax highlighting. However, there is a place where there is a widely adopted approach to skimming a structured document: the web. Modern screen readers employ what is known as a virtual cursor to navigate structural information on webpages such as HTML heading tags. These tags can indicate different sections and subsections in the structure of a page. We harness the existing familiarity of blind computer users with this interface in our approach which we call AudioHighlight. AudioHighlight renders the code inside a web view, either as part of the Eclipse IDE or as a web service. It places HTML heading tags on the structural elements of a source file such as classes, functions and control flow statements. We compare AudioHighlight to the state of the art in code skimming represented by a previous code skimming approach called StructJumper. We also compare to the state of practice in reading code on the web as represented by GitHub. We found that AudioHighlight increased the quality and speed of code comprehension as compared to both approaches.","PeriodicalId":6572,"journal":{"name":"2018 IEEE International Conference on Software Maintenance and Evolution (ICSME)","volume":"30 1","pages":"206-216"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86211013","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}
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