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Objective: The aim of this study is to identify common usability problematic patterns that belong to top-50 academic websites as a whole and then ranking of these identified usability problems is also provided. Methods:In this study, a novel approach is proposed that is based upon the integration of conventional usability testing and heuristic evaluation with data-mining knowledge discovery process. An experiment is conducted to evaluate ISO 9241-151 guidelines under 16-different categories by hundred participants who are frequent users of academic websites. After evaluation, the qualitative usability data is collected and different data-mining techniques i.e. association rule and decision tree are applied to recognize fully functional and problematic usability attributes. Identified problematic attributes represent common usability problems patterns related to academic websites from the qualitative viewpoint only. This study further prioritizes these problematic attributes by using the ranking algorithm that represents the order in which usability issues must be resolved. Results:In this study, 16-different categories are considered for usability evaluation of academic websites. The results show that no issues are identified in two-categories i.e. {Headings_Titles_Labels and The Home_Page}. In Scrolling and Paging category, horizontal scrolling is identified as a major issue whereas, in Internationalization category, the users do not identify supported languages on most of the academic websites. Users do not find websites to be highly secured under Security category. Our findings investigate that most of the issues are found in Search and Social Media categories. Furthermore, users easily locate 50.53% guidelines on websites as fully functional whereas, 49.46% of characteristics are considered as problematic usability features that are not functional on the academic website as a whole. Conclusions:Identification of common usability problems at an early stage can lower substantially the development efforts in cost and time. Software developers can restrain from these potential usability problems during the development of novel systems under the same context. Providing appropriate solutions for these problems can become valuable in software development. The proposed approach concludes Sagar and Saha Hum. Cent. Comput. Inf. Sci. (2017) Page 2 of 24 Sagar and Saha Hum. Cent. Comput. Inf. Sci. (2017) 7:29 that conventional usability evaluation methods can go beyond just than testing of systems. The study is a milestone towards identification and prioritizing problematic usability features for academic websites and helps in providing the wholistic approach of usability problematic patterns for web-domain. RESEARCH

Software Defect Prediction (SDP) is one of the most assisting activities of the Testing Phase of SDLC. It identifies the modules that are defect prone and require extensive testing. This way, the testing resources can be used efficiently without violating the constraints. Though SDP is very helpful in testing, it's not always easy to predict the defective modules. There are various issues that hinder the smooth performance as well as use of the Defect Prediction models. In this report, we have distinguished some of the major issues of SDP and studied what has been done so far to address them.

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The incorporation of suitable external data from the World Wide Web offers an effective solution for enriching the data in the data warehouse (DW). However, the main challenge is the quality‐aware selection of web data sources to maintain the quality of the DW. In the previous works, the quality evaluation of web sources is through expert evaluation only, which makes it a very lengthy process. Also, since the quality model consists of mixed quality factors from diverse domains of Web, DW and underlying business, finding an expert possessing an expertise of all these domains is a huge bottleneck in the evaluation process. In order to overcome these existing issues, this study proposes a novel multi‐level approach web source evaluation with multi‐criteria decision‐making and web quality testing tools (WSEMQT) and underlying quality model web quality model for evaluating web sources for the DW. The authors introduce automated web source quality evaluation in the first level of web source based evaluation and multiple dimensions of quality evaluation at the second level of expert‐based evaluation. At both the levels, multi‐criteria decision‐making methods are applied to the evaluation scores obtained to ascertain the ranked list of Web sources. The authors present a real‐world academic web data case study which shows that the proposed approach can be executed successfully for real‐world problems.