C. Kemerer, S. Slaughter
{"title":"软件维护概要的决定因素:一项实证调查","authors":"C. Kemerer, S. Slaughter","doi":"10.1002/(SICI)1096-908X(199707/08)9:4%3C235::AID-SMR153%3E3.0.CO;2-3","DOIUrl":null,"url":null,"abstract":"Software maintenance is a task that is difficult to manage effectively. In part, this is because software managers have very little knowledge about the types of maintenance work that are likely to occur. If managers could forecast changes to software systems, they could more effectively plan, allocate workforce and manage change requests. But, the ability to forecast software modifications depends on whether there are predictable patterns in maintenance work. We posit that there are patterns in maintenance work and that certain characteristics of software modules are associated with these patterns. \n \nWe examine modification profiles for 621 software modules in five different business systems of a commercial merchandiser. We find that only a small number of modules in these systems is likely to be modified frequently, and that certain maintenance patterns emerge. Modules frequently enhanced are in systems whose functionality is considered strategic. Modules frequently repaired have high software complexity, are large in size, and are relatively older. However, modules that have been code generated are less likely to be repaired. Older and larger modules are restructured and upgraded more frequently. Our results suggest that these characteristics of software modules are associated with predictable maintenance profiles. Such profile information can be used by software managers to predict and plan for maintenance more effectively. In addition, our results suggest the use of code generators as a means of reducing repair maintenance. © 1997 John Wiley & Sons, Ltd.","PeriodicalId":383619,"journal":{"name":"J. Softw. Maintenance Res. Pract.","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"82","resultStr":"{\"title\":\"Determinants of software maintenance profiles: an empirical investigation\",\"authors\":\"C. Kemerer, S. Slaughter\",\"doi\":\"10.1002/(SICI)1096-908X(199707/08)9:4%3C235::AID-SMR153%3E3.0.CO;2-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Software maintenance is a task that is difficult to manage effectively. In part, this is because software managers have very little knowledge about the types of maintenance work that are likely to occur. If managers could forecast changes to software systems, they could more effectively plan, allocate workforce and manage change requests. But, the ability to forecast software modifications depends on whether there are predictable patterns in maintenance work. We posit that there are patterns in maintenance work and that certain characteristics of software modules are associated with these patterns. \\n \\nWe examine modification profiles for 621 software modules in five different business systems of a commercial merchandiser. We find that only a small number of modules in these systems is likely to be modified frequently, and that certain maintenance patterns emerge. Modules frequently enhanced are in systems whose functionality is considered strategic. Modules frequently repaired have high software complexity, are large in size, and are relatively older. However, modules that have been code generated are less likely to be repaired. Older and larger modules are restructured and upgraded more frequently. Our results suggest that these characteristics of software modules are associated with predictable maintenance profiles. Such profile information can be used by software managers to predict and plan for maintenance more effectively. In addition, our results suggest the use of code generators as a means of reducing repair maintenance. © 1997 John Wiley & Sons, Ltd.\",\"PeriodicalId\":383619,\"journal\":{\"name\":\"J. Softw. Maintenance Res. Pract.\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"82\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"J. Softw. Maintenance Res. Pract.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1002/(SICI)1096-908X(199707/08)9:4%3C235::AID-SMR153%3E3.0.CO;2-3\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"J. Softw. Maintenance Res. Pract.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/(SICI)1096-908X(199707/08)9:4%3C235::AID-SMR153%3E3.0.CO;2-3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 82
Determinants of software maintenance profiles: an empirical investigation
Software maintenance is a task that is difficult to manage effectively. In part, this is because software managers have very little knowledge about the types of maintenance work that are likely to occur. If managers could forecast changes to software systems, they could more effectively plan, allocate workforce and manage change requests. But, the ability to forecast software modifications depends on whether there are predictable patterns in maintenance work. We posit that there are patterns in maintenance work and that certain characteristics of software modules are associated with these patterns.
We examine modification profiles for 621 software modules in five different business systems of a commercial merchandiser. We find that only a small number of modules in these systems is likely to be modified frequently, and that certain maintenance patterns emerge. Modules frequently enhanced are in systems whose functionality is considered strategic. Modules frequently repaired have high software complexity, are large in size, and are relatively older. However, modules that have been code generated are less likely to be repaired. Older and larger modules are restructured and upgraded more frequently. Our results suggest that these characteristics of software modules are associated with predictable maintenance profiles. Such profile information can be used by software managers to predict and plan for maintenance more effectively. In addition, our results suggest the use of code generators as a means of reducing repair maintenance. © 1997 John Wiley & Sons, Ltd.