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ICSE 2021
Mon 17 May - Sat 5 June 2021
Tue 25 May 2021 12:05 - 12:25 at Blended Sessions Room 4 - 1.2.4. Software Requirements Chair(s): Birgit Penzenstadler
Wed 26 May 2021 00:05 - 00:25 at Blended Sessions Room 4 - 1.2.4. Software Requirements

The identify-assess-control cycle in goal-oriented requirement engineering aims at identifying, assessing, and resolving divergences in which the goals of the requirement cannot be satisfied as a whole. The boundary conditions (BCs) have shown great potential in requirements engineering because a BC captures a particular combination of circumstances, i.e., divergence. Existing researches have attempted to automatically identify lots of BCs. Unfortunately, a large number of identified BCs in the identification stage make the assessment stage and the resolution stage very expensive, and even impractical. We observe that existing identifying methods mainly adopt generality metric in order to filter out redundant BCs. However, a set of general BCs still retains a large number of redundant BCs since the generality metric can be considered as a coarse-grained metric to only filter out less general BCs, and a general BC potentially captures redundant circumstances that do not lead to a divergence. Furthermore, the accuracy of the assessment step based on likelihood is sensitive to redundant circumstances, so a set of general BCs leads to mistakes in the assessment step, which results in costly repeatedly assessing and resolving divergences.

In this paper, we present a novel metric to filter the redundant BCs, which is a fine-grained metric to improve the accuracy of the assessment step. We first introduce the concept of contrasty of BCs from the point of resolving divergences. Intuitively, if two BCs are contrastive, they capture the different divergences of the requirements specifications. We argue that a set of contrastive BCs should be recommended to requirements engineers, rather than a set of general BCs that potentially only indicates the same divergence. Then we design a post-processing framework (PPAc) to produce a set of contrastive BCs. Experimental results show the contrasty metric can filter out all the BCs that capture the same divergence, which dramatically reduces the number of BCs recommended to engineers. Furthermore, experiments also show that the BCs identified by the start-of-the-art method are not contrastive in most cases, which means that the BCs capture the same divergence, which makes the identify-assess-control cycle inefficient. In order to improve efficiency, we propose a joint framework (JAc) to interleave assessing based on the contrasty metric with identifying BCs. The primary intuition behind JAc is that it considers the search bias towards the BCs that capture different divergences. Experiments show that JAc produces the search bias towards contrastive BCs and identifies contrastive BCs more efficiently than PPAc.

Tue 25 May

Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

12:05 - 13:15
12:05
20m
Paper
How to identify Boundary Conditions with Contrasty Metric?Technical Track
Technical Track
Weilin Luo Sun Yat-sen University, Hai Wan School of Data and Computer Science, Sun Yat-sen University, Xiaotong Song School of Data and Computer Science, Sun Yat-sen University, Binhao Yang School of Data and Computer Science, Sun Yat-sen University, Hongzhen Zhong School of Data and Computer Science, Sun Yat-sen University, Yin Chen Department of Computer Science, South China Normal University
Pre-print Media Attached
12:25
20m
Paper
Using Domain-specific Corpora for Improved Handling of Ambiguity in RequirementsArtifact ReusableTechnical TrackArtifact Available
Technical Track
Saad Ezzini University of Luxembourg, Sallam Abualhaija University of Luxembourg, Chetan Arora Deakin University, Mehrdad Sabetzadeh EECS, University of Ottawa, Lionel C. Briand EECS, University Of Ottawa
Pre-print Media Attached
12:45
15m
Paper
Investigating the potential impact of values on requirements and software engineeringSEIS
SEIS - Software Engineering in Society
Alistair Sutcliffe University of Aston, Peter Sawyer Aston University, Wei Liu King's College London, Nelly Bencomo Aston University
Pre-print Media Attached
13:00
15m
Paper
Validation Obligations: A Novel Approach to check Compliance between Requirements and their Formal SpecificationNIER
NIER - New Ideas and Emerging Results
Atif Mashkoor Johannes Kepler University Linz, Michael Leuschel HHU, Alexander Egyed Johannes Kepler University
Pre-print Media Attached

Wed 26 May

Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

00:05 - 01:15
00:05
20m
Paper
How to identify Boundary Conditions with Contrasty Metric?Technical Track
Technical Track
Weilin Luo Sun Yat-sen University, Hai Wan School of Data and Computer Science, Sun Yat-sen University, Xiaotong Song School of Data and Computer Science, Sun Yat-sen University, Binhao Yang School of Data and Computer Science, Sun Yat-sen University, Hongzhen Zhong School of Data and Computer Science, Sun Yat-sen University, Yin Chen Department of Computer Science, South China Normal University
Pre-print Media Attached
00:25
20m
Paper
Using Domain-specific Corpora for Improved Handling of Ambiguity in RequirementsArtifact ReusableTechnical TrackArtifact Available
Technical Track
Saad Ezzini University of Luxembourg, Sallam Abualhaija University of Luxembourg, Chetan Arora Deakin University, Mehrdad Sabetzadeh EECS, University of Ottawa, Lionel C. Briand EECS, University Of Ottawa
Pre-print Media Attached
00:45
15m
Paper
Investigating the potential impact of values on requirements and software engineeringSEIS
SEIS - Software Engineering in Society
Alistair Sutcliffe University of Aston, Peter Sawyer Aston University, Wei Liu King's College London, Nelly Bencomo Aston University
Pre-print Media Attached
01:00
15m
Paper
Validation Obligations: A Novel Approach to check Compliance between Requirements and their Formal SpecificationNIER
NIER - New Ideas and Emerging Results
Atif Mashkoor Johannes Kepler University Linz, Michael Leuschel HHU, Alexander Egyed Johannes Kepler University
Pre-print Media Attached